Blog - Ibbaka

Pricing and value for category creation

Steven Forth — Tue, 07 Jan 2020 13:25:32 +0000

Artist's concept illustrates a dusty planet-forming disk around a star. NASA/JPL-Caltech

Category creation is emerging as the preferred strategy of many high growth companies. In 2019 we had repeated conversations with companies who wanted to create not a business but a category, and who wanted to know how to price for this strategy. Category creation is for those with big ambitions, and it needs a rigorous framework to deliver.

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The playbook chosen by several of these companies is Play Bigger: How Pirates, Dreamers, and Innovators Create and Dominate Markets by Al Ramadan, Dave Peterson, Christopher Lochhead and Kevin Maney. The first three of these are principles at the Play Bigger consultancy in Santa Clara. They have developed a process for category design that they are applying across industries and scales. The process is robust, see below, but it fails to address the critical connection between value drivers - value metrics - price metrics. This is where Ibbaka can help you.

Before diving into how to connect value to price in category creation, let’s walk through the plays in the Play Bigger playbook. This is just a quick tour, we encourage you to pick up the book and give it a read, then to find a group of fellow travellers online or in your community to trade ideas with.

The Play Bigger playbook walks you through five key plays you need to execute in order to create a new category.

Category Discovery
Developing a Point of View
Mobilizing Your Forces
Market Conditioning
Building a Flywheel

Category discovery is where you find the problem you will fall in love with. This can’t be just any problem. The creative genius in category creation is in finding not just an unmet need, but an unrecognized need. One story told in the Play Bigger book is of Clarence Birdseye and frozen foods. While working in Labrador in the 1920s, he watched Inuit people catch fish and throw them on ice, where they froze almost immediately. The fish could be kept in a state almost like fresh caught for as long as they could be kept frozen. They tasted different, and Clarence thought better, than salt cured, smoked or pickled fish. He used this insight to create a whole new category, frozen food, and he sold the company he founded to do this into what was to become General Foods in 1929 for $22 million dollars (which was a lot of money at that time).

Developing a point of view on how to solve the problem is critical to category creation. Category creators are not “me too” companies. They are not innovating by creating line extensions or by making incremental technical fixes. They have a new solution to a new problem. Google created the category of search advertising by leveraging the social structure of the World Wide Web itself to deliver better search results, unlike the indexing engines it replaced. By uncovering the graph of connections that stitches web content together, Google found a new way to solve search, an approach that no one has been able to displace to date.

Mobilizing your forces to communicate the new category is central to category creation. Everyone in the company from investors to engineers to the people talking to potential customers has to be aligned on why the new category matters.

Once the message starts to get out, and people begin to show interest, it is critical to condition the market to understand how the pain they didn’t know they had was actually eating away at them and that there is now a solution. This is more like market shaping than conventional marketing. An example of this is what medical technology giant Becton Dickinson did with needle sticks and healthcare worker safety. Working with professionals, regulators and thought leaders they helped people understand the risks posed to healthcare workers by needle stick injuries, showed that these injuries are preventable, and then provided solutions to keep people safe and avoid enormous personal and financial costs.

Once the category is established, you need to build a system where the each part of the solution contributes to the others and drives category growth. You have to build a flywheel that builds momentum as it goes (see Design your pricing to keep that flywheel spinning). A category is truly established only when it becomes a system full of the positive feedback loops that drive sustainable growth.

This five step process is powerful, and the authors provide plenty of examples of how it can be applied. Yet as I read the book, I felt something was missing. A category only really comes into existence when a new form of value is created, and with that new value comes opportunities to create new pricing models.

Let’s go back to basics. A the heart of Ibbaka’s approach is the connection between value drivers, value metrics and pricing metrics.

This is the underlying model for how value drivers (how customers perceive value), value metrics (the unit of consumption by which value is delivered) and pricing metrics (the unit of consumption that is priced) are connected. Value drivers have economic, emotional and community aspects. The triple of Value Driver - Value Metric - Pricing Metric define the Market Segmentation and Pricing Model. Pricing Models are designed for target segments.

The key to category creation is to find a new way to connect value drivers, value metrics and pricing metrics and to drive this new way of thinking into the market.

“The place to start is with the value of the category as a whole.” This insight comes from Micah Litow, COO at Kalderos. Kalderos is one of the companies following the Play Bigger approach to category creation. In his work creating a new category, which Kalderos calls drug discount management, he has found that the critical first step is to define the value for solving the problem your category addresses, and not for any one solution in the category. This point bears repeating. “When designing pricing for a new category, begin by defining the value propositions for the category as a whole,” says Litow. “If you simply compare your solution to those of competitors, and are as a result tying your value proposition to a specific solution, then you are not creating a category, but rather are playing in an emerging or existing one.”

This will be a new approach for most pricing experts, who are trained to seek for differentiation between solutions. However, Micah points out “in the case of category creation, there are no alternative solutions to differentiate from.” Value propositions are the ways in which your category (note ‘category’ and NOT ‘solution’) creates value. Value drivers come in three flavors: economic, emotional and community (more on community or social value drivers coming this year). Of course, value drivers are only relevant if someone cares about them, and the challenge in category design is to discover a new set of connected value drivers that some group of people (buyers and users) cares about.

The key idea here is that the value drivers must be connected. They need to form a pattern that people can recognize amidst the noise of their day-to-day life. Value innovation, and category creation, occurs when value drivers are combined in novel ways. In platform businesses (multisided markets) the connection will often be between two or more groups. For example, AirBnB initially connected people with rooms to share with people travelling on a budget (yes, the connections exploded out from this). Connecting value drivers in new ways is the key to innovation.

Once you understand, and can convince people of the value propositions for your new category, you need to define the value metrics. These are the units of consumption that track value delivery. A common example is charging for the number of hours that a jet engine is propelling a plane (rather than for jet engines as pieces of machinery). Or the pay per click advertising model where the click is thought to signal interest and attention, and is thus a better proxy for value than impressions (the number of times people have been exposed to a message). Pricing innovation depends on closer connections of value metrics to pricing metrics.

Before moving on to solutions, it is important to segment the new category. This needs to be a value-based segmentation. One is looking for clusters of potential customers that get value (economic, emotional and community value) in the same way. Almost all categories will contain several different segments. Solutions are designed for segments, and not for the category as a whole. This is why pricing for category creation begins with understanding and communicating the value of the category, and not with coming up with a pricing model for a specific solution.

Once the category is defined in a way that people can care about it, has been segmented based on value, and segment specific solutions proposed, then one can begin working on pricing model design.

This is really a restatement of the classic approach to innovation and pricing, where one begins with value to the customer and ends at cost (and is why cost plus pricing fails when one is working to create a new category).

The Category Creation Value and Pricing Process

Connect value drivers in new ways (that are meaningful to some group of buyers and users) - these patterns define new categories
Segment the category using these value drivers (find clusters that experience value in the same way)
Develop solutions for the target segment(s) (different segments are likely to require different solutions, which is why it is a category and not just a market)
Identify value metrics and map to pricing metrics (the key to pricing innovation, good category innovation deserves pricing innovation)
Design a pricing model (which may be specific to the solution and target segment, but ideally is extensible to other segments and solutions)
Develop the category data model (this is the model that collects and organizes the data created in and about the category)
Understand the new skills that will be needed to make the category successful (these skills will be on the side of providers, buyers and users, and enablers
Deepen understanding of the value driver patterns that are evolving in the category and that connect it to other categories

Category creation is not for everyone. It entails risk, requires imagination, and forces you to ask hard questions about value. It is, though, the most compelling way to drive sustainable growth over time.

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In 2020 develop a portfolio of pricing actions

Steven Forth — Tue, 31 Dec 2019 20:59:06 +0000

Most of us understand the power of pricing to shape markets and categories. We understand that all things being equal, a price increase will have a bigger impact on gross profit than any other action you can take (see as one of many examples this piece by McKinsey). Pricing is where all the different aspects of marketing come together. Your customer probably does not care what segment you think they are in, they may or may not believe your value propositions, but if you can’t agree on a price then you don’t have a customer.

That said, many B2B companies agonize before making a decision about pricing. They dither and worry, go back and forth on what to do, and often end up not making a decision or making a random action.

Why is this? We think there are three reasons.

People do not calculate the impact of a price change on volume, revenues and profits.
Companies lack a process for making pricing decisions.
Pricing is treated as a one time decision, rather than as a portfolio of possible actions.

The impact of a price change

This seems basic. “If I change the price, what will happen to volume, revenue and gross profit?” It is a simple question and it is easy to explore a range of answers. Few people bother to do this though, and it leads them to be too cautious about making price changes. Let’s look at a simple example, using the Ibbaka pricing calculator.

Assume a price of $100 per unit, variable costs of $50 per unit, fixed costs of $5 million and initial volume of 1,000,000. If you increase price by 5% to $105, how much volume can you afford to lose and keep revenue or net profit at the same level? This is one of the foundational pricing questions that everyone involved in sales, marketing and pricing should be able to answer. To save you some time with a spreadsheet, here is the answer.

One can afford to lose 9% of volume and keep profit constant or 5% of volume and keep revenue constant. Let’s assume that we do lose 5% of volume, what will this do to profit? Even with the loss in volume, profit is up more than $2.3 million. One would have to think very carefully before turning down $2.3 million plus in profit.

(Interested in trying out the Ibbaka Pricing Calculator? Contact us at info@ibbaka.com).

Develop a process for pricing actions

The failure of many companies to assess the impact of a price change is part of a larger problem, the lack of a process to make price changes, or rather, to take pricing actions.

Why ‘pricing action’ rather than simply ‘price change’? Price is closely tied to value, or more specifically, to differentiation value. Anything that happens to change your differentiation value should lead you to consider a pricing action.

What is ‘differentiation value’? Basically, it is the economic, emotional or community value that you provide that the alternative does not. The alternative may be a direct competitor, an inhouse developed alternative, or doing nothing! The value that you provide that can also be realized from an alternative is the commoditized value. The price of the commoditized part of your offer is set by the market. The final price is a combination of the commoditized market-based component and the price you claim for your differentiation value.

Pricing actions are more than just price changes. They are anything you do to align value and price with your overall strategy. Pricing actions are changes to

the list price
what is included for the price (change packaging)
the tier architecture and pricing (a specific approach to changing packaging)
the pricing metric (the unit of consumption on which pricing is based)
discounting policies

One can also impact the value-price connection through better marketing. This includes a market segmentation that is based on differences between how different prospects understand value, value propositions that are aligned with these value-based segments and better evidence for the value propositions. Although not pricing actions per se, these should be considered together with any potential pricing action.

How does one know when to consider a pricing action? There are internal and external triggers for action.

Internal triggers for pricing actions

Differentiation value has been enhanced (normally by adding new functionality, services or data)
Market segmentation suggests the need for new or different packages
Company strategy has changed and pricing needs to be aligned with the new strategy
Pricing has not been reviewed or adjusted for more than a year and is no longer in alignment with value or strategy
Discounting is out of control (more than 30-to-50% or inconsistent as shown by pricing dispersions - graphs that map price to the pricing metric)

Competitor triggers for pricing actions

Competitors have added new capabilities that increase their differentiation value (the red area in the above Venn diagram) or reduce your differentiation value (the blue area in the above Venn diagram)
Competitors have changed prices in a way that changes their positioning and either threatens your own positioning or opens up new opportunities for you

Customer triggers for pricing actions

Customers change their business model or add new business models that change their perception of value (this can change both pricing and segmentation)
Customer economics change in ways that change their perception of value (it is worth extending this to your customers’ customers)

In heavily regulated industries, like healthcare or utilities, one also has to consider changes in the regulatory environment which can force pricing changes.

A simple pricing process

One can put all of this together into a simple pricing process.

Check alignment between pricing goals and corporate strategy
Build a value-based market segmentation
Choose target segments that will guide your pricing
Design packages for target segments
Map value metrics to pricing metrics
Choose pricing metrics
Design the pricing model
Set prices
Define the data model that will help you track pricing and value
Set up a discount management system
Track pricing performance (the impact of price on other key business metrics)
Have a review system (monthly or quarterly) that identifies internal, competitor, customer and regulatory triggers for pricing actions
Develop a portfolio of potential pricing actions (see next section)
Take pricing actions regularly and systematically (and measure the outcomes)

Manage pricing actions as a portfolio

Pricing is not a once and done thing. Nor is it a single point action. Pricing actions are part of a system, so to manage pricing effectively you need options. At the same time, pricing is such a critical activity that you generally don’t want to be taking multiple pricing actions in parallel. There are too many unintended consequences that you need to watch for and taking multiple actions at the same time will make it much harder to anticipate and respond to these.

Preparing a pricing action can take time, as the different stakeholders are consulted, systems such as the CRM (customer relationship management system) or billing and financial systems are configured and the financial and legal ramifications worked out. Some pricing actions can be planned and executed on in a manner of weeks, especially if a good process is already in place, others may need months or even years of preparation.

One may also want to research pricing actions that you will hold in reserve, to be prepared to act rapidly in case a certain scenario is realized.

The only way to manage this effectively is to think of your pricing actions as a portfolio, a set of past, present, future and potential actions that are all being worked on. Basically, you should always be

Tracking past pricing actions to see what impact they are having and if they achieved and are still achieving their goals
Taking a current action by
- preparing the company, customers and the market for the action
- executing
- providing immediate back up to marketing, sales and customers
- making any immediate course corrections
Planning future actions at different time horizons (next month, next quarter, next year, future years)
- updating market segmentations
- revising value propositions for each segment
- developing evidence
- modeling possible outcomes
- preparing the company, customers and the market for the action (note how this segues into taking a pricing action)
Developing options for future pricing actions (there is not commitment to taking these actions, but developing options is critical to having a resilient company)
- developing data models for value and pricing and collecting the data
- discussing value metrics with customers
- developing alternate pricing models, levels, discounting strategies
- identifying triggers that would suggest when to move to planning

All this may sound like a lot of work. For 2020 we suggest a simple way to get started.

Test goal alignment
Review all your pricing through the lens of your offer pipeline, your customer needs, your competitors possible actions
Develop a modest portfolio of thee-to-five potential pricing actions
Pick on pricing action and begin to execute (you should always be executing on one pricing action)

We hope 2020 will be a great year for your business!

Push Me Pull You - Your pricing is a system

Steven Forth — Wed, 18 Dec 2019 12:12:38 +0000

Note: The title and image for this article are based on Hugh Lofting's story "Doctor Dolittle Meets the Pushmi-Pullyu".

Pricing changes can be tricky because each price is part of a larger system. Changing a price in one place can cascade across the system causing all sorts of unexpected consequences. You cannot think of a price change as a simple change to a number. That number can connect to all sorts of other things.

The first place to look is at anchoring and framing effects. These are terms from behavioral economics, that part of economics that tries to take into account how people make decisions in the real world. An ‘anchor’ is a value that other values are compared to. Pricing design includes the design of what value will be perceived as an anchor value. This is done by how and when the price is presented during the customer journey and what alternative is presented. Think of your favourite restaurant. What prices are easiest to find? They are likely designed as the anchor prices. When changing a price, ask:

Is this an anchor price?
Will it still be an anchor price after the price change?
How will changing this price change the perception of other prices?

Framing is the larger context in which anchoring takes place. At its most basic it is the definition of the next best competitive alternative. One of our clients had long compared its platform to survey tools. This made it look expensive even for a subscription of under $2,000 per year. This was poor framing as the real competitive alternative was not a survey but expensive and expert consultants, who would choose $50,000 or so for an engagement. By reframing their market, and focussing on a narrow segment where they could outperform consultants (your market segmentation is a key part of your framing) they were able to raise their prices to almost $20,000, a 10X increase. Note that this reframing includes both a narrowing of their target market and a change in the competitive alternative. The result was faster revenue growth and much higher gross profit.

Many SaaS offers come with tiered pricing. We see these on most pricing pages. There is entry pricing on the left, in between pricing in the middle and some form of enterprise pricing on the right. These tiered models are generally kept to a maximum of five tiers. These models have both anchoring and framing effects taking place. One thing we do at Ibbaka when assessing these pricing models is to see if the pricing is linear (on the left below), concave (middle) or convex (right).

In most cases, the linear models suggest that the person setting the price was running on autopilot. Concave pricing is designed (or has evolved) for markets where the lower end of the market is largest or is being targeted. The high price on the right makes the middle price look attractive. Convex pricing is used by companies that want to draw in customers and then upsell them. It works best when the upper end of the market has the most opportunity or is being targeted.

Many large companies are selling multiple solutions. In this case, the system dynamics go beyond the pricing of an individual offer to the role an offer plays in the portfolio. We have been writing about this in our series on Pricing your solution portfolio.

Of course your pricing is part of an even larger system. The marketplace. Some of the most interesting system behaviors here are caused by the interactions between price elasticity of demand (how much aggregate demand is impacted by changes in price) and cross price elasticity (how changes in price lead people to switch from one vendor to another). We have written about these interactions in several places, most recently in How to hire a pricing consultant.

So there are three levels at which pricing acts as a system.

Within the solution, where pricing is part of the anchoring and framing and plays a big role in how price and value play out across the customer journey.
As part of a portfolio, where the offer has a role to play in the overall portfolio and is at a certain point in the technology adoption cycle. (Not all offers are necessarily in the same part of the cycle, some may be targeting early adopters, others may be in rapid growth mode, while others are approaching obsolescence.)
In the market, where pricing and packaging moves by competitors’ impact on your own pricing strategy (Michael Porter’s Five Forces model is a good way to think about what the alternatives are).

Given these complex interactions, pricing needs to be treated as a complex adaptive system. Most people lack experience designing and managing such systems, and as a result they either fall into analysis paralysis, or fail to take pricing actions as often as they should as it gives them a headache to think about it.

Pricing actions are some of the most powerful things you can do to improve your business, so ignoring pricing, pricing by throwing stuff at the wall, or pricing based on what competitors do are all recipes for poor performance. In early stage innovation, they can even kill the new product or service.

What to do? Here are a few simple rules to get you started.

Is the current price acting as an anchor?
Will it still be an anchor after the price change?
How will the anchoring change?
How is pricing currently framed?
Will the framing be changed by the price change?
Do you need to change the framing?
How is pricing framed by your brand?
Will the price change reinforce the brand or undermine it?
How is your tiering system designed?
What role does each tier play? Is it playing that role effectively?
Is your tiered pricing linear, concave or convex? Why?
How will the pricing change impact framing and anchoring within the tiers?
What role does the offer (and its pricing) play in the portfolio?
Consider anchoring and framing effects across the portfolio
Is the role of the offer in the portfolio changing? (Has it moved along the technology adoption cycle?)
How will the price change impact market dynamics?
Which of the four quadrants are you operating in?
How will your competitors respond?
How will your customers respond? (But remember, you can afford to lose some volume as part of a price change, especially when the result is a higher gross margin or lifetime value of a customer.)
Are new alternatives emerging that will reframe your offer and its pricing?
Use the Five Forces model to see where alternatives may emerge.
Clayton Christensen’s disruptive innovation model may provide additional insights.

The three different layers do interact, and this can lead to some unexpected outcomes when you change prices. But don’t let this get in the way of acting. The only way to really understand a complex adaptive system is so observe it as it responds to change. So make changes, observe the outcomes and course correct. Pricing is a dynamic discipline.

Note: The title and image for this article are based on Hugh Lofting's story "Doctor Dolittle Meets the Pushmi-Pullyu".

Dynamic pricing is a two edged sword

Steven Forth — Wed, 27 Nov 2019 20:52:03 +0000

Dynamic pricing is a hot topic in pricing circles these days. Back in October it came up in a number of keynotes at the Professional Pricing Society’s Fall Conference. Some pundits are predicting that dynamic pricing will take over large swaths of the pricing industry over the next decade.

Dynamic pricing is not new. Back in the days where people bought most things through barter and then haggling, all pricing was dynamic pricing. Auctions are another form of dynamic pricing. One that is likely to dominate the future of dynamic pricing.

When pricing software companies talk about dynamic pricing they are generally talking about a system that uses a variety of inputs and calculations to create a near real time price for each buyer based on an estimate of their willingness to pay (WTP). These systems have their roots in revenue management and were originally developed for use by airlines. For airlines load management is a critical issue. Every empty seat is lost revenue, and given the high fixed costs of a flight and the very low variable costs getting those last few people on board can determine if a flight is profitable or not.

You may have seen the add where there is a chicken pecking at a keyboard with the voice over telling you that this is how some airlines set prices. Well the revenue management software is the chicken.

It is a smart chicken, applying a lot of machine learning to a lot of data. The same approach can be extended to any situation where there is data that indicates variability in demand. What these systems do is map variations in the data to build virtual elasticity of demand and cross elasticity of demand curves. Elasticity of demand is the degree to which demand changes when the price changes. Cross price elasticity is the tendency of buyers to change vendors in response to price changes (If Coke raises its prices to what extent do people switch to Pepsi?). These elasticity models are combined with external data of various types to estimate willingness to pay for any particular buyer and use it to predict that customer’s willingness to pay.

Price elasticity of supply and cross price elasticity interact in interesting ways. In many cases they operate on different timelines with price elasticity of demand having long term effects (what to by) and cross price elasticity operating on shorter timelines (which solution to buy). Dynamic pricing works best where either price elasticity of demand or cross price elasticity of demand is high. They serve different purposes in these two different scenarios.

In the upper left (low price elasticity of demand with high cross price elasticity, one is trying to edge out the competition without triggering a price war. One does not want two competing automated dynamic pricing systems inadvertently triggering a price war.

In the lower right quadrant, where price elasticity of demand is high and cross price elasticity is low, one is trying to optimize price and volume to maximize profits or maximize revenues (these are not the same price in most scenarios). Dynamic pricing can be incredibly effective in this scenario and the risks are relatively low.

It is the top right quadrant that is most interesting. Here price elasticity of demand and cross price elasticity are both high. These are the conditions for a chaotic system. It is not clear to me how well dynamic pricing will work in this scenario, especially when multiple market participants are all trying to apply these systems. This will be something to watch closely.

Even here, there are some serious problems. The first is around pricing fairness. People want prices to be fair and have a strong reaction when they think they are being manipulated or taken advantage of. Pricing fairness comes from transparency, consistency and shared value. If you are going to adopt dynamic pricing you will need to be able to explain how it works and why it is fair.

How to explain systems based on machine learning (as the best dynamic pricing systems are) is a general challenge. It is possible. See the ongoing work on xAI (explainable AI) being led by DARPA. These concepts should be applied to dynamic pricing.

In his excellent book The New Invisible Hand, Kyle Westra covers pricing transparency in depth and shows that you can have price transparency or price setting transparency but with dynamic pricing you cannot have both. In certain markets it may be important to provide transparency on both (healthcare comes to mind) and in these markets dynamic pricing is a poor solution.

The conflation of willingness to pay and differentiated value has to come to an end. Willingness to pay is an outcome of the creation, communication and delivery of differentiated value. It is an outcome and not a driver. Pretending that you understand value because you can estimate willingness to pay is wrong headed.

The second challenge to dynamic pricing is dynamic buying. If sellers are going to adopt dynamic pricing en mass then buyers would be well advised to do so to. If sellers want to optimize for willingness to pay - WTP (as a poor substitute for understanding value), then buyers are interested in willingness to sell - WTS and are eager to find the vendor that will cut them the best deal. This is also referred to as M2M (machine to machine) pricing. Assuming that dynamic pricing is widely adopted we should also assume that dynamic buying will also be adopted. We will then have buyers and sellers interacting in a dynamic environment. This sounds like an auction to me. A complex auction in which there are multiple players on both sides. Mechanism design (the design of auction systems) will become a key skill of pricing experts as M2M pricing becomes more common.

No doubt M2M pricing will become a significant part of B2B pricing in the future, just as it already is the dominant mode of pricing financial instruments (with mixed outcomes and the occasional market crash). But is this the only path forward? Dynamic pricing is transactional. it does not help build long-term commitments on either side. In the airline industry, the widespread adoption of dynamic pricing has contributed to weakening brands and reduced customer loyalty. Is this what you want for your company?

The counter to dynamic pricing is likely to be outcome or performance-based pricing. In this approach, buyer and seller share the economic gain. This has often been discussed but it has been hard to execute on, much harder than dynamic pricing in fact. Why has this been hard?

Causality is complex
Data is hard to come by
Risk-reward curves have different shapes for buyer and seller
Timelines are long
Trust is rare

At Ibbaka, we believe that all of these issues can be addressed. There have been technology advances that address the causality and data issues. New pricing designs can build alignment around differing distributions of risk and reward. With transparency around data, risk, reward and pricing mechanisms one can build trust.

Subscribe to this blog follow our work on performance-based pricing or reach out to us at info@ibbaka.com to discuss how we can make this work for you.

How to hire a pricing consultant

Steven Forth — Mon, 18 Nov 2019 21:56:46 +0000

Pricing is the most powerful of the four Ps (product, price, place, promotion) but it is also one of the least understood. In many companies pricing is a frozen accident. Someone came up with a pricing model ‘once upon a time’ and set prices, and people have been living with it ever since. In new product development, pricing is 'often ‘cost plus’ (a sure way to limit profits) or ‘me too’ (not the best way to demonstrate differentiation). Or you can just throw out a number and see if it sticks. This is the throw spaghetti at the wall school of pricing.

CEOs and their boards are increasingly aware of this, and have been reaching out to pricing consulting companies to jolt their organizations into action. Sometimes this does not go much beyond ‘we have to do something about pricing’ or ‘figure out how to raise our prices.’ The direction often falls on the head of sales, marketing or product. Sometimes the CFO is held accountable. In most cases these people need help to move pricing to the next step and the accepted place to look for help is consultants.

What help? Which consultants?

Many people reach out to us with pricing problems. When we peel these back, we find that pricing is often the symptom of some other problem. Pricing is easy for people to complain about. ‘It is too expensive.’ ‘I can get it cheaper.’ ‘That is not how I want to pay.’ Pricing is where challenges with value delivery, value communication, customer success and customer targeting come to the surface. The first step in any pricing engagement is to understand the root causes of the pricing challenge and then to test that challenge for alignment with the organization’s goals.

Pricing consulting patterns

A number of different types of project fall out of this root cause analysis. Here are the types of engagement we most often get involved in.

Research what economic, emotional and social (community) value buyers and users care about
Discover the market structure and target customers
Map value drivers, value metrics and pricing metrics
All of the above are generally in service of the following
Design a pricing model for a new offer
Design a pricing process for a new innovation
Design a pricing intervention in a value chain when the solution is embedded in existing markets
This can lead to some important follow up work
Develop value models and the data collectors and analytical tools that inform them
Build value calculators and pricing calculators that connect sales to customer success
Create pricing playbooks that connect strategy to execution
Train marketing and sales on how to position price in the context of value

That is the Ibbaka approach. It requires a deep understanding of business models, not our customer’s business models but our customer’s customers business models. It is based on research and design rather than optimization and technology. We do use some pretty advanced technology of course, finding hidden market structures, collecting and analyzing data, building value and pricing calculators all require coding. The Ibbaka approach connects business analysts with software engineers, data scientists and designers.

There are a number of other pricing consulting models and there are some companies that are very good at these other approaches.

Determine willingness to pay (WTP). This is the old school approach to pricing work. It assumes that WTP is somehow given and that prices can be optimized to the given level of WTP. If your pricing vendor is using techniques like Gabor Granger or conjoint they are likely taking this approach.
Optimize pricing. The customer wants to know what the ‘right price’ is. Increasingly this is merging with dynamic pricing where the price is adjusted using complex algorithms that use customer and market data.
Systems implementation. There are some fairly complex pricing systems available. They generally need a lot of configuration and work best when they pull data from other systems. This is specialist work that only a few companies are good at. They will have close connections to the pricing systems vendors.

There is one other form of pricing consulting that can be transformational to companies willing to commit to it. This is the triangle of pricing governance, capability building and culture change. This requires very different skill sets from other pricing work. Ibbaka is starting to work in this area. We are developing an Open Competency Model for Pricing Expertise to help with this and hiring people with experience in change management and organizational design.

How do you choose a pricing consultant?

Look at Roger Martin’s cascading choices model and see where you need help.

Which of these five cascading choices will have the biggest impact on your business?

First understand the problem you are trying to solve for. Ask the following questions …

Did the consultant help me understand the possible causes of my pricing challenge?
Did the consultant ask about my customers and how they do business?
Did the consultant probe on our pricing goals and how they support our larger business objectives?

Then imagine what a solution will look like.

Are you creating value for your target customers? Look into value-based market segmentation and customer targeting.
Do you have a fundamental new innovation or are you creating a new category? You need a set of patterns and a process to put them together to create pricing in a dynamic, emergent environment.
Does your solution have clear differentiation and create great value? Have your consultant develop a pricing model that connects value metrics to pricing metrics.
Are you working in an established market with well defined pricing? Work with your consultant to identify pricing actions and how to execute on them.
Does willingness to pay change depending on market conditions and buyer characteristics? Investigate dynamic pricing (you will also most certainly need software to execute on this).
Do you need to implement pricing software, CPQ (configure price quote) software, configure your CRM, marketing automation or customer success software? Use one consultant to help specify and choose systems then a different consultant to implement.
Do you need to know how to price? Work with your consultant to implement pricing competencies in your organization and provide training if needed.
Do you have a large, complex organization where different stakeholders clash on pricing? Work with an organizational design and change management consultant that understands pricing competencies and processes.

Pricing consulting is not one size fits all. A good consultant will tell you if they have the skills, tools and relationships needed to solve your problem. A weak consultant will tell you they can do everything. Even the large firms cannot do everything. The more they try to do so, the weaker they get. Scale does not equal capability. Differentiation is as important for a consulting firm as it is for a product firm. If your consultant does not know its own differentiation, how will they help you to discover yours?

Pricing drives enterprise value: five questions investors should be asking

Steven Forth — Tue, 12 Nov 2019 19:42:39 +0000

Private equity (PE) firms invest in companies so that they can increase their value and sell them on. If a company is perfect, in an attractive market with a clear and differentiated strategy that is being effectively executed, then it is not a good investment for most PE firms. It may be a good venture capital investment, if it is early stage, or a good place to lend money, if it is more mature, but this is not where PE generates value. PE generates value by improving business basics. So the questions is what basics.

Interested in the competencies needed for pricing expertise? Please take this short survey.

Given the famous quote by legendary investor Warren Buffet on pricing power, it is surprising that this is not the first thing that investors look at.

The single most important decision in evaluating a business is pricing power. If you’ve got the power to raise prices without losing business to a competitor, you’ve got a very good business. And if you have to have a prayer session before raising the price by 10 percent, then you’ve got a terrible business.

We have written on what pricing power is, and how to increase it, elsewhere (see What shapes willingness to pay) so the main question is that given the power of the pricing lever, why isn’t it the first one that PE firms pull?

There is some recent research from consulting firm Mckinsey & Co. that helps to answer this question. In Pricing: The next frontier of value creation in private equity, recent research on pricing and private equity is summarized. Many PE firms try to improve business performance by cutting costs. Many are famous for this. Private companies, especially those run by founders or their families, are thought to build up layers of unnecessary spending over the years, and the PE firm can come in with a scalpel (or a cleaver) and cut out costs. This is seen as low risk (but if it destroys the ability to create differentiated value for customers it is a false economy). The next thing in the play book is generally revenue growth. Top line growth is an important metric and it seems to many that if you can cut costs and grow revenues then profits will naturally follow (see our interview with pricing guru Tom Nagle for his thoughts on this). It is well known that pricing is one of the most direct ways to increase profit and that a one percent increase in price will generally drive a bigger increase in profit than a one percent increase in revenues or a one percent cut to costs. Given the importance of pricing, why are so many reluctant to pull the pricing lever? The Mckinsey research provides some answers.

Let’s work through each of these.

Risk of competitive response

One assumes that this means competitors will take advantage of price increases to steal away customers. Is price the only, or even the main reason that your customers stay with you? If so, you have no pricing power and were not a good investment to begin with. The first thing you need to do is to increase your pricing power (and there are only three ways to do this) or move into a market and develop offers where you have differentiated value.

What you should really be afraid of is price cuts. If you cut your prices, what will your competitors do? If they will respond by cutting prices then you are in big trouble. Pricing wars can destroy the value of entire industries.

Price increases generally build value. Price cuts are more likely to destroy value.

Risk of customers deciding not to purchase

We have coached companies through many price increases. If you have a legitimate reason for the increase, communicate it clearly and treat customers fairly, they will generally go along with the increase. Of course you will probably lose some customers. You probably should lose some customers. For some customers you simply do not provide enough value and they should go elsewhere. Other customers are not and will not generate enough customer lifetime value to be worth the investment needed to keep them.

The three ways to increase pricing power mentioned above are …

Increase positive differentiation (economic, emotional and community)
Decrease negative differentiation (those things the next best competitive alternative does better than you, or the unique costs of your own solution)
Increase your pricing power by strengthening your brand, reducing risk for your buyer or restructuring the value chain in your favor.

Lack of visibility into the opportunity

This seems like a weak excuse. There are many ways to explore the impact of pricing actions. Start by interviewing customers, prospects and losses about value (not about price) and get a real understanding of how different parts of your markets, and different stakeholders in the business, actually get value. Use this to segment your customers and design packaging and pricing. Will there be uncertainty? Of course, we live in an uncertain world. But not acting also has risks. The real risks can be explored by building Monte Carlo models of the range of outcomes and exploring what information might actually reduce uncertainty.

Weak supporting systems

We do have some clients where making a price change is almost impossible because of how their accounting, billing or delivery systems are structured. Remember the old joke, “in an ERP implementation you take your business processes and pour concrete over them.” Well pricing can get set in that concrete. One thing that PE investors can do is break through this inability to act and put the right systems in place. Even when the systems are getting in the way, there are usually ways to implement at least some pricing actions while the systems are reconfigured or replaced.

Limited management team bandwidth

If management is not looking at pricing, one of the most important levers of profitability, then what are they spending their time on? Pricing should be on the agenda of every leadership meeting and every board meeting. If necessary, reach out to consultants. At the same time, build internal pricing muscles.

Misaligned frontline incentives

This most likely refers to the fact that most salesforces are compensated on the topline. Sales people do what they are paid to do, they are coin operated, and that is how it should be. Redesign of sales compensation should be part of pricing strategy execution. Compensation should reflect the company’s strategic goals. If the only goal is to grow revenues, and metrics like profit, customer lifetime value, category share are unimportant, carry on. Show your salesforce that pricing increases are very often an effective way to increase revenues, even if one loses a few customers. There is even a metric for this, the Selling Price Index (see below).

What questions should investors ask about pricing?

Ask when the last time a pricing action was taken. Why was it taken? How was it implemented? What was the outcome? Keep on asking this question. Look for changes over time.
Require that the company produce a quarterly Sales Price Index. This is a metric used by pricing leaders like Dick Braun at Parker Hannifin to measure the impact of pricing on revenue. The equation for this is simple: (Average Price This Year – Average Price Last Year) x Volume for the Quarter. Price changes can contribute or take away from revenue. As an investor, or potential investor, you need to understand this at a granular level.
Consider how much is being invested to increase positive differentiation, decrease negative differentiation or increase pricing power. These investments should be balanced (none of them should be zero) and reflect the overall strategy.
Get alignment on the goals of pricing strategy. Is pricing meant to optimize topline revenue, to grow profit margins, to build a new category or claim market share? How does pricing impact overall customer lifetime value? Is pricing being used to manage utilization? There is no effective pricing without alignment on intended outcomes.
Segment the market by value. Good pricing is based on a foundation of value-based market segmentation. A meaningful market segment is one that gets value in the same way and that buys in the same way. Pricing should be designed for the most important target segments and not be broad brush. One size does not fit all.

Investors and their representatives on the board of directors have a responsibility to make sure that companies are executing on pricing. It is one of the most effective ways to increase shareholder value. Put pressure on management to make sure they are executing.

Pricing of design - the case of art jewelry

Steven Forth — Mon, 04 Nov 2019 18:44:18 +0000

To really excel in pricing design it is important to look outside of B2B and see how things work in other parts of the world. We recently looked at the pricing of used books (which are often bought by the pound). Now let’s look at the art jewelry market.

Art jewelry, what is that? According to Wikipedia,

"Art jewelry is one of the names given to jewelry created by studio craftspeople. As the name suggests, art jewelry emphasizes creative expression and design, and is characterized by the use of a variety of materials, often commonplace or of low economic value. In this sense, it forms a counterbalance to the use of "precious materials" (such as gold, silver and gemstones) in conventional or fine jewelry, where the value of the object is tied to the value of the materials from which it is made.

From a pricing perspective there are a number of interesting points here.

Conventional jewelry is priced based on the value of the materials used plus brand. Some would argue that there is also value for the design, but in most cases the value of the design is subsumed into the value of the brand. Few people could differentiate between the design of something from Tiffany and Cartier. Of course the red Cartier boxes are worth more (have a higher brand value) than the light blue Tiffany boxes.

Art jewelry is altogether different. This work is quirky and unique. It is often made from cast off bits and pieces, the flotsam and jetsam of the modern world (bits of wire, broken ceramics, flakes of rock, melted plastic cups, industrial paper). It is formed into jewelry in many different ways. Sometimes traditional metallurgy techniques are used, but so are crocheting and knitting, moulding, assemblage and just about anything else that will cause different types of materials to stick together.

Yoshie Hattori

This sort of work is not of interest to everyone. But people who are interested, a focussed segment, tend to be passionate collectors. It is sold at stores like Velvet Da Vinci in San Francisco, Platina in Stockholm, Ra Gallery in Amsterdam or Collectiva in Porto (yes, this work is given more importance in Europe).

The fact that the value of the materials is often trivial and that the buyers are generally well informed collectors leads to a very different pricing dynamic than for conventional jewelry.

One calculates the price of a conventional piece of jewellery by adding the value of its materials, some gold or silver of various purities (measured in karats) and any jewels included. Then multiply that value by a factor (in practice this can be as low as .7X at a poorly run discounter (inviting opportunities for arbitrage) to as much as 5X for a brand that invests in its image and exclusivity.

Pricing art jewelry is much more like pricing art. One asks

Who else is collecting this artist?
Is the work collected by any major galleries?
Is the design unique?
Is there a coherent story (or idea) behind the work

The top art jewelry can sell for thousands of times more than the value of the materials. In fact, many would say that if the materials are part of the value it is not really art jewelry.

Are there any lessons here for pricing other forms of design?

Perhaps the most important is that you have to understand the dynamics of the market and how it attributes value before you can know how to price. In some markets, price is determined by the value of the inputs. These markets inevitably trend towards commoditization. You can fight this by an investment in brand, but this will require large ongoing investments to sustain. If you are a designer, you probably want to avoid these industries as the price you get paid for your work has little to do with your effort or even its value.

Where should designers work? They will have the most pricing power where their work makes the largest contribution to differentiation value. Differentiation value is the value (economic, emotional and social) unique to your offer and not provided by the next best competitive alternative. Apple creates value through design and pays its designers well. The same is true of top fashion designers. Design, often referred to as User Experience (UX) is becoming more and more important in many industries, and organizations that are trying to differentiate on user experience and customer experience will pay well for these skills.

One question about conventional jewelry versus art jewelry is which will hold value over time? The brand advocates for conventional jewelry will tell you that ‘diamonds are forever.’ Are they? There a more and more sources of diamonds and synthetic diamonds are emerging as a separate market in their own right. Synthetic diamonds get a good part of their value from design. Art jewelry as a distinct market is relatively new. It remains to be seen how well these pieces will hold value over the generations. Tastes change. What was once popular falls into obscurity. At least with conventional jewelry there is the value of the gold. But there are works of art that have held their value and even become more valuable over time. The best art jewelry will probably fall into this category. And as the Internet makes is possible to connect and aggregate small markets, the art jewelry is likely to command higher prices over time.

Yoshie Hattori Biography

Yoshie Hattori is an artist from Japan. She trained as a textile artist at Tama Art University in Tokyo and Handarbetets Vänner in Stockholm. She had a textile design studio in Tokyo and taught weaving. After moving to Vancouver in 1988 she has worked in multimedia production. For the past decade she has focused on photography and making small objects and jewelry. She lives in Kitsilano, Vancouver.

Yoshie Hattori Artist’s Statement

Over the past decade my work has evolved in two directions. Using textile techniques I create small, wearable objects that combine industrial materials (wires, plastics, latex, etc.) with natural objects such as crystals, pearls and corals. Into this I insert scraps and bric a brac found here and there. Bringing together these materials with their different origins represents how we live our lives, dependent as we are on both the products of industrial society and on nature. We live in a society where there is much waste, and where much that is valuable can be found in waste. These objects evoke the potential for change of natural forms, the intimate gestures of the hand and an industrial energy. The textile arts are among the oldest human technologies and the way in which threads and wires combine are closely related to the laws governing natural forms. I think with my hands. Sometimes my hands think for me. But none of this would happen without the energy network I live in and rely on. I am also exploring hidden rhythms, patterns, and textures on my photo blog It Is. The relation of my photo work to my objects is tenuous but important. In both I am exploring and connecting patterns, often implicit and tangential patterns, but patterns that connect. In both these projects I try to find the playfulness and experimentation that are part of an evolving life.

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Pricing for lifetime customer value

Steven Forth — Wed, 30 Oct 2019 17:33:04 +0000

One of the most important metrics for any subscription business is customer lifetime value (LTV). This is the value of the revenue one can expect from a customer over the full life span. This metric was popularized by mobile phone companies, who needed to know how much a subscriber was worth so that they could know how much to invest in winning and keeping a customer. Cable companies also ask this question, and they are especially interested in knowing what combination of services (content mostly) will optimize lifetime value.

Modern SaaS (Software as a Service) companies obsess about this metric. It is one of the key ways they are measured by their investors. In fact, there have even been recent acquisitions in which the total customer lifetime value was a factor in the valuation!

For most of us, it was David Skok’s now classic articles that taught us the basics.

SaaS Metrics 2.0 – Detailed Definitions

Segment the customer base on LTV

Last week we wrote about SePVA or Price Dispersions in Critical Metrics for Pricing Execution - Insights from Dick Braun. If you are in a subscription business, it is critical to segment your customers by LTV. Not all segments are equal and not all customers make the same contribution to LTV.

Start with your estimate of LTV for each customer on the X-axis. It is worth doing this for both Gross LTV and Net LTV. Then experiment with different values for the Y-axis. You are searching for a Y-axis that organizes the LTV distribution in a meaningful way. This could be that the customers distribute themselves onto a nice line of some type with a high r-squared. Or it could be that the customers cluster into well defined groups. It is worth looking for both outcomes.

Some typical LTV Dispersion Graphs

Here are some things to try for the Y-axis:

Churn - It may seem odd to graph churn as churn is a factor in LTV. Some correlation is to be expected. What this does is let you look at the interactions between ARPA and Churn (of course you can also graph ARPA to Churm)
Gross Margin - This is another of those funny ones that can provide surprising insights. Especially when you get clusters rather than correlations.
Engagement - Are your most engaged customers the ones with the highest LTV? If not, why not? What is the relationship between Engagement and Value?
Customer Acquisition Costs (CAC) - This is one of the other critical metrics. Investors will often ask about the ratio of LTV to CAC and will be looking for a ratio greater than 3. Are the customers with the highest CAC the ones with the greatest LTV? If not, is there something wrong with your marketing allocation?
Value to Customer (V2C) - Value to Customer is one of the most important SaaS metrics but it receives little discussion. It is an estimate of how much value the solution is providing to the customer. If LTV > V2C then you do not have a viable business model. Does LTV go up with V2C and is this linear, or some other function (in the real world it is almost never linear).

If there are distinct segments for LTV, and there usually are, you need to think through how to treat each segment. A simple framework for doing this is presented below.

Model the impact of price on ARPA

Once you have segmented your customers by LTV (and V2C if you can) you need to understand the impact of price on ARPA. At the simplest level, price impacts ARPA in three ways.

Price is one input into revenues, as revenues are basically just price x units.
Consider price volume tradeoffs for each segment. Will an increase in price cause the number of units to drop by an amount greater than the aggregate LTV for the segment? Will a price cut (or discounting or a special ‘campaign’ price) generate enough new units to make up for the reduction in price? These behaviors are generally very different for each segment, which is why you need to complete the segmentation first.

Model the impact of price on Churn Rate

Price also impacts the other key input into LTV: the Churn rate. If prices are too high, then churn will increase. This is especially true in for cases where LTV > V2C or even for LTV ~ V2C. It is often useful to construct hypotheses on the impact of price on churn and then to test them on historical data. When we have done this we have generally found only a week correlation between price and churn.

But before you change the renewal price, look at all of the other factors that impact renewals (renewal is just the inverse of churn).

Are customers engaged?
Are customers getting value?
How has the customer’s business changed?
How has the competitive landscape changed?

Yes, one can raise prices so high that churn increases. If this is the customers in the lower left quadrant above, who are provind low LTC and receiving relatively little value, then churn could be a good thing for both parties. In most cases, price is not what is driving churn.

Work out the interactions between ARPA and Churn Rate

ARPA and Churn are not independent of each other. Remember that churn can be greater than 1. This means that you are able to grow your business with your existing accounts. A price increase can

Increase ARPA if the additional revenue from the price increase is greater than the loss in revenue from lower unit sales;
Improve Revenue Churn if the additional revenue for current customers from the price increase is greater than the loss in revenue from increased account churn;

or
Decrease ARPA if the additional revenue from the price increase is smaller than the loss in revenue from lower unit sales;
Increase Revenue Churn if the additional revenue for current customers from the price increase is smaller than the loss in revenue from increased account churn.

Build a model that factors in the effect of price changes on both ARPA and Revenue Churn. Look carefully at the feedback loops and interactions between the impact on ARPA and the impact on Revenue Churn. Test if the model works the same way in each segment.

Consider the impact of price on Customer Acquisition Costs

Price can also impact Customer Acquisition Costs (CAC). The higher the price the higher CAC are likely to be. In our experience, this continues on into customer success investment. High value, high LTV solutions most often come with high Customer Acquisition Costs and require an ongoing investment in customer success.

On the other hand, low Customer Acquisition Costs and low subscription prices are often related to higher churn rates. As price is based on value to customer (if you want to have a sustainable business) one needs to triangulate between Value to Customer (V2C), Customer Lifetime Value (LTV) and Customer Acquisition Costs (CAC) in designing subscription pricing.

A more complicated story

It is a challenge to manage a subscription business and make sure that revenues grow over time. It is much more complicated when a company has two or more offers that can (i) compete for customers but (ii) feed each other customers. In this case one needs to have a clear (and shared) understanding of the role of each of the offers. (For some context on this see Pricing Your Solution Portfolio Part 2: Setting Goals). Once you have alignment on goals, build a predictive model for how different pricing models will impact V2C, LTV and CAC and, here is the fun part, model the interactions.

Take CAC as an example. If one service feeds another it is effectively reducing CAC costs for the second program. It is also providing pipeline. A change to pricing for one service will cascade into the CAC for the second solution.

There are also interactions between LTV. A change in prices for one service will normally cause some redistribution of subscribers between the two solutions. In other words, it will increase churn for one of the solutions, which of course impacts the LTV. Depending on the role and strategic goals for each solution, one can build an optimization model. This model should be predictive. The initial predictions will probably not be all that accurate, but as you gather data and run experiments accuracy will improve over time.

These kinds of interactions also exist in multi sided markets, and building models for this sort of pricing interaction is part of our ongoing research.

Here we have focussed on subscription models, but these concepts are also relevant to other pricing models. Any business where you are building a long-term relationship will benefit from framing pricing strategy in terms of customer lifetime value and the other key metrics for unit economics.

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Critical Metrics for Pricing Execution - Insights from Dick Braun

Steven Forth — Tue, 22 Oct 2019 14:04:22 +0000

The Professional Pricing Society had its Fall Conference last week in Las Vegas. One of the keynote speakers was Dick Braun, Vice President of Strategic Pricing at Parker Hannifin. Dick is one of the most effective pricing executives around, and over the past 15 years he has built a high impact pricing function at his company. His talk was on “Building and Running a Company’s Pricing Program,” and it was chock full of excellent advice.

He introduced a key metric and a key tool in his talk. The tool was SePVA (pronounced ‘sep-vah’) or Segmented Price Variance Analysis. He sees this as one of the core ways he gets his teams thinking about the strategic impact of pricing and helping them target the critical opportunities for pricing actions. Dick has kindly offered this approach for broader use. The metric is the Sales Price Index or SPI, which measures the impact of pricing changes on revenues.

Interested in the competencies needed for pricing expertise? Please take this short survey.

Before looking at at these tools and metrics, it is useful to know that the Parker Hannifin pricing team is distributed, the pricing experts are located in the businesses and are close to the P/L owner. They work closely with sales, product development and the business leaders, and are the glue that holds the different business function together (those are my words, not Dick’s, but I have watched this team in action).

One of the core metrics, that these embedded pricing experts are expected to track, is the Selling Price Index (SPI). This is calculated as follows:

Average Price This Year – Average Price Last Year x Volume for the Quarter

The average price is the average for wherever you are focussing your pricing lens. It could be for a product line, a geography, a segment or even a specific customer (looking at the SPI for a specific customer is important for your big customers). As revenue is just price x units, the SPI measures the impact of price changes on sales. It is not always positive. Knowing your SPI is a duty of the pricing expert. Knowing the reasons for changes and the trends is critical to taking effective pricing actions.

So what is SePVA or Segmented Price Variance Analysis? It is a chart of revenues per client (or segment or offer or geography – whatever you are analysing, plotted against price. At Ibbaka we also refer to this as a price dispersion. Before you try this, sketch what you think the shape of this line should be. Will it slope down from left to right as your largest customers are getting better prices? Or perhaps the slope goes the other way, as the largest customers get the most value and are willing to pay more. Will the curve be linear, concave or convex? What is the logic behind the curve you expect?

Once you have the data, do some curve fitting and see what kind of curve best fits the data and how much of the variance (or r-squared) the line accounts for. At Ibbaka we generally want r-squared to be greater than 0.7, though in companies with poor pricing discipline it can be much lower.

Of course some accounts will fall above the line, they are relatively overpriced, and others will fall under the line. Some variance is normal, what you are looking for is outliers or even better groups of outliers.

A typical SePVA or Price Dispersion Graph

Are the groups of outliers actually signalling that they belong in different segments?

In some cases, one just gets clusters and there is no meaningful curve that can be fit. In this case, you are almost certainly dealing with customers that belong in different market segments. Sometimes there will be clear clusters, but in other cases the dispersion will look random.

When this happens, you need to explore other dimensions. What else could you use for the X-Axis? Is there some other variable that would snap the data into order, so that you could fit a line, or at least find some meaningful clusters. Some things to look at include:

Usage data. Is there some pattern of use that is correlated with price? If there is, that would be a very good thing as it would suggest a new pricing metric based on use.
Industry data. Are companies in one industry getting a different price than companies in another industry? If so, why? Are there packages that can be designed for each industry?
Geographical data. Are some geographies getting a better price? If so, why? Are there grey markets where people are buying in one market for use in another?

The most interesting thing to do is to map price against value metrics and value models. If you have data on the value drivers that matter to each customer, you can see if the customers cluster around value drivers (Ibbaka has software that helps to do this). If you have been able to develop value models for each customer (an emerging best practice), check and see how value and price are correlated. Wouldn’t it be nice if customers getting the most value are paying the highest price. Of course, you may want to correct for volume when you do this. If company A and Company B are getting a similar unit value, are they also getting a similar unit price?

One can go a step farther and create a SePVA for the SPI (Sales Price Index). Map the SPI for each company on the Y-Axis and try other values on the Y-Axis. Find out which values find order in the data.

The first step in good pricing strategy is to find the order in the data. If there is no order, you will struggle to execute on pricing strategy.

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An Open Competency Model for Pricing Expertise

Steven Forth — Wed, 16 Oct 2019 00:18:26 +0000

In 2018 Ibbaka partnered with TeamFit to research emerging skills in pricing. The growing demand for pricing experts, changes to revenue models (especially the rise of the subscription economy) and the introduction of new technologies (AI and specifically machine learning) was changing the skills needed for pricing expertise and opening new job opportunities and career paths.

We have continued this work, helping our clients build up their own pricing expertise and investing in our own training and development. The trends we identified in 2018 have gathered force and are pushing us to take this work to the next step.

Share your expertise - take this five minute survey

What is the next step?

In February 2020 Ibbaka-TeamFit will publish a competency model for pricing expertise. Specifically, this will be an open competency model, one of four that we will be publishing in February of 2020.

Pricing Expertise
Customer Success
Design Thinking
Adaptation to Climate Change (with the ResilienceByDesign Lab at Royal Roads University)

These models are open in that …

They are made available under a Creative Common license (so you will be able to use and modify it without paying us any money)
They are meant to evolve with use
They are modular and parts of one can be used in another

A pricing competency model needs to be modular and open as the pricing function interacts with many other functions. There are many jobs in which pricing competencies are important. Some examples include

Product and service managers need a good understand of pricing in order to guide development and choose priorities. In many cases they will be expected to set the basic approach to pricing. Few product or service managers have been trained to do this.
Revenue and sales leaders need to understand value and pricing if they are not to be crushed by the negotiation experts in procurement.
Customer success managers and leaders (note that this is one of the competency models we are developing) need to be focused on value to customer and then making sure that there is a return on the customer success investment. This requires pricing competencies.

Part of the power of pricing is that it is where all of the different parts of the business come together. Good pricing is based on the value delivered. Value is relative to the alternatives and is in the eye of the customer. Market segmentation, customer targeting, offer packaging and pricing are all tightly connected which we illustrate in our value graph.

The Ibbaka value graph.

There are many ways to design a competency model, but in most cases the model will usually include Jobs, Roles, Behaviors and/or Tasks. Skills are the atoms of competency models. They are what connects all of the other pieces.

The structure of a competency model

One open question about the Pricing competency model is whether it should include values. The Design Thinking model will, because when we surveyed the design thinking community some 70% of people believed that it should.

Some of the Roles we are considering for the Pricing competency model are as follows:

Pricing leader
Pricing coach
Pricing analyst
Pricing AI analyst
Pricing designer
Pricing sales support
Pricing deal desk

You can let us know what is missing by taking the survey or sending an e-mail to info@ibbaka.com.

The granular level of a competency model is the skills. We put skills into a skill graph that defines the connections that skills have with each other. The four key connections are …

Associated skills: the two skills are generally found together in the sames person - Economic Value Estimation and Value Analysis are associated skills
Complementary skills: the two skills are frequently used together, but often by different people - Price Negotiation and Pricing Data Analysis are frequently used together but there is no reason to expect the same person to have both skills
Parent skill: the high level skill, Pricing is the parent of the Pocket Price Waterfall and Economic Value Estimation
Child skill: the more specific skill that inherits properties from a higher level skill - Price Dispersion is a child skill of Price Segmentation

We will have the first version of this model available in February of next year and will be demonstrating how it can be used to build pricing capabilities at the Spring 2020 Professional Pricing Society conference.

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Service Design and Experience - Thoughts on Majid Iqbal's O-P/E=N Model

Steven Forth — Tue, 08 Oct 2019 12:19:28 +0000

In August, Majid Iqbal visited Vancouver to give a talk at the Value Innovation and Pricing Vancouver Meetup. We invited him up for three reasons.

Services are a growing focus for innovation, understanding their design, how they create value, and how to price them is mission critical for many companies.
Majid’s work makes deep use of patterns and uses them to organize and generate services.
Majid proposes a novel way to integrate value (which he refers to as outcomes) with price and the quality of pricing experience.

These three themes are all critical to our work at Ibbaka.

Majid is the author of the important new book Thinking in Services (BIS 2018). The book sets out a compelling approach to services. It begins with a definition that helps us think more clearly: “Services are performances and affordances producing outcomes that satisfy a set of customer needs.” That services are both affordances (making something available, this is the sense in which Software as a Service is a service) and performances (doing something that provides a desired outcome, like cooking a meal or designing a pricing model) is the key to their nature, and the source of much confusion. How you think about pricing an affordance and a performance is often different, but most services combine the two.

The book goes on to identify the patterns and promises associated with services and provides a 16x frame that can be used to design a service and weave stories through it.

All of this is compelling and worth close study and application, but one of the things that caught our attention is that it proposes a way to factor customer experience into price.

Customer experience is emerging as one of the key drivers of value. Recent research from Watermark Consulting “2019 Customer Experience ROI Study” found that customer experience leaders outperform the market.

This opens the question

How does customer experience impact pricing?

Answering this question is going to be critical to organizations looking to make significant investments in customer experience. Majid Iqbal provides an approach to doing this with his O-P/E=N or OPEN model.

O-P/E=N

Let’s start by seeing how he defines his terms.

O is Outcomes. Going back to the definition of a service, a key aspect is that services are “producing outcomes that satisfy a set of customer needs.” For this to work as an equation, the outcomes have to be quantifiable. There are many ways to go about doing this. At Ibbaka we often use Tom Nagle’s Economic Value Estimation or EVE. In healthcare, Quality Adjusted Life Years (QALYs) is sometimes used as a quantitative metric. In some cases, one even designs a value metric as part of the pricing work. This metric is then used to communicate value in sales and to measure value delivery by customer success.

P is Price. The trick here is to frame price and outcomes in a way that they can be connected. This is another way of stating Ibbaka’s mantra that value drivers determine value metrics (the Outcomes) and that pricing metrics should track value metrics.

E is Experience. The customer experience puts price in context. See below for more on the implications of dividing Price by Experience. This is the key to Majid Iqbal’s proposal on how to work customer experience into value. Having metrics to track experience is just as important as having metrics to measure outcomes.

N is the Net Value. In the full Thinking in Services model one has to think through both net value for the customer (Nm) and the net value for the service provider (Nv). The net value is the value of the outcomes less the price adjusted for the customer experience.

So what does it mean to divide Price by Experience? Basically, a high quality customer experience, where E > 1, the effective price is lower (you are dividing by a number greater than one). An investment in better customer service is rewarded with more pricing power.

When the vendor provides an inferior customer experience, E < 1. Dividing by a number smaller than one, makes the numerator, the effective price, higher. Another way of thinking about this is that an inferior customer experience decreases pricing power.

The provider needs to decide if investments in customer experience can be recouped through higher prices. The buyer needs to be persuaded that the better customer experience is worth the higher price.

Of course this is not all there is to customer experience. Offering a better customer experience can also reduce costs by eliminating support calls. In subscription business models, good customer experiences have been shown to reduce churn, and, for other services, they drive repeat use. There are a lot of ways that customer experience impacts the business.

The power of the Thinking in Services approach is that it ties together so many aspects of a service and shows how they connect together. This is central to service design. The O-P/E=N equation shown above is an example of this. At Ibbaka we are still working on how to work this approach into our work on market segmentation, customer targeting and pricing design. Having an integrated approach to thinking in services is a great help in this work.

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Why do they sell used books by weight (and what that implies for pricing data)

Steven Forth — Tue, 01 Oct 2019 22:55:40 +0000

One of the oddest pricing metrics I have encountered is in the used book business. People in the used book trade often by books by weight. The going rate in the US today seems to be from 5¢ to 25¢ per pound with the unit of purchase being the pallet (a pallet of books is about 1,300 pounds so it will cost between $65 and $325 per pallet).

Buying books by the pound! I can’t think of anything further from value-based pricing. Why does this make sense?

It is almost like mining. The books bought by the pound are the paydirt: “dirt, rock, or other raw materials which contains (or may contain) profitable quantities of ore or other valuable materials.” To make paydirt valuable, one needs to do a lot of processing and then transport it to market. The same with the books, though in this case the processing is done in the seller’s warehouse where it is more convenient. Buying books by the pound is a way to manage uncertainty about value. It reduces all of the books to their lowest common denominator and uses that as the pricing metric. If uncertainty about value could be reduced, the price would go up.

In fact, that is exactly what happens. Buyers use a variety of techniques to reduce uncertainty. Sometimes they buy a sample. The minimum buy is usually a pallet, but sometimes it is a truck. One then works through the sample, figures out what is in the sample, and determines how much to pay. Of course one has to hope it is really a representative sample.

The other technique is provenance. Where did the books come from? Have they already been picked over and all the best books picked or are they fresh to the market? Are they the discards from a small local library or are they from a private estate (private estates are generally more valuable than other sources, these are the shipments selling at 25¢ or more per pound).

An important thing to remember about the used book trade is that there is a floor price. If you can’t sell the book you can sell it for pulp.

Is there anything like this in software? In fact yes. There is a small but emerging market for undifferentiated data sets. There are some companies that are buying data by volume (megabytes, or even terabytes). The rapid improvements in data mining are making it worth buying undifferentiated data (the paydirt) and processing it into ore (nuggets of insights or even predictions).

Unfortunately, some of this is happening in the grey market or even the black market. Over the past six months, the inevitable offers by questionable development shops have been joined by people offering data of dubious provenance, or even legality. The prices are crazy low, but there must be someone that is buying or there would not be so many sellers.

We are not suggesting you buy any of this data. Don’t. Only buy data if you know it has been legally sourced and you can test the value. But if you are selling data, and many organizations are, you want to avoid selling it by volume. How do you do that?

Don’t sell paydirt, sell ore.

Know your data, and be able to describe its properties to possible buyers. You have to be able to do some data mining yourself so that you are providing the assays to the buyer and not relying on them. Reducing search costs increases value. This is especially true in a world awash in data of all levels of quality and relevance.
Differentiate your data. Anything undifferentiated gets sold at the market price. The market price trends to the variable cost. The variable cost of data approaches zero. Remember that differentiation is always (i) for a specific customer or customer segment and (ii) relative to the next best competitive alternative. A market segment is defined as a set of buyers who get value in the same way.
Add value to the data through rich metadata, at the file level and through embedded metadata. Just what metadata you use to enhance value will depend on your target markets and their use cases.

Related blog post: Do you price inputs or outputs?

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Do you price inputs or outputs?

Steven Forth — Wed, 25 Sep 2019 18:26:40 +0000

The simplest way of thinking about a process is that there are a set of inputs, some form of transformation occurs, and then there are some outputs.

A book combines the inputs of authors, designers, editors, proof readers and type setters (OK, with modern software, designers and typesetters are pretty much the same thing), along with glue, paper, ink and sometimes a bit of string. That is for a physical book of course. An e-book is a string of 1s and 0s that can generate pixels when used with the right software and device. Inputs, outputs, What do you price?

Much of pricing is the result of frozen accidents. Someone set a price one way at some point in the past and no one has ever gotten around to changing it. Books and eBooks are a good example of this. Hardcover books are traditionally priced at 3-to-5 times the manufacturing cost. This gave a reasonable returns to author, publisher, distributor and retailer. (There is even a profit calculator from major book distributor Ingram that helps you do the calculations). The hardback book sets the reference price for the trade paperback and in most cases for the eBook.

Think about that for a moment…

The cost structure of a hardcover book sets the reference price for an eBook with a totally different cost structure. This pricing maintains itself because of the power of framing effects. The hardcover book, which few will buy or read, frames the price of all other versions for historical reasons.

Cost based pricing, as we saw above with books, uses the inputs to set the price. Market based pricing uses the outputs. Value based pricing uses the outcome of using the outputs, usually in some other process.

Value based pricing is a way of linking together processes to reflect the exchange of value across the process.

Are we really talking about a linear process? Not in most cases. We generally need to be thinking of webs rather than linear inputs and outputs, just as ecologists now speak of the food web rather than the food chain, we need to be thinking in terms of value webs rather than value chains. Just as food webs are about the transfer of energy, value webs are concerned with the transfer of value.

Pricing is how each node in the web captures its share of value.

From cadavies in the grade four curriculum

Of course it is not that simple. Let’s look at the most common pricing metric in the SaaS world, number of users. Is this an input or an output. Neither really. It is just a measure of how many individuals can access a service. Is this a measure of value? Not usually. It is removed from the web of processes in which value is created. To understand value one must look at the role a service plays in a series or processes and compare the service you are trying to price with the competitive alternatives (the other paths through the value web that can get you to the same place).

Value-based pricing puts the service in the context of the role it plays on a specific path through the value web and compares it to other paths that lead to the same place. It is a form of value path analysis with a focus on how much value can (and should) be captured along each step of the path.

The counterargument is that users are the agents that create the value so it makes sense to use the number of agents acting in a system as a proxy for value. Very few services are delivered without people getting involved. Even the most automated service is frequently in aid of some work that is being performed by humans (there are exceptions of course, and the number of exceptions is likely to increase over the next decade, but that is a story for another day). So there are arguments in favour of user based pricing.

User based pricing makes most sense when two criteria are met.

Each user gets their own unique view of the data or makes their own unique view of the service. If sharing accounts and co-mingling data would reduce the value of the service, then user based pricing may make sense. For example, I do not want my health records to be jumbled up with those of others.
The actions of each user create unique value that needs to be traced back to that user. When I write, I often want to be able to author my own documents, and not just dump them into a shared file with no attribution. (Think about the difference in value between a signed work of art and a generic work that could have been made by anyone).

So how do we proceed? One way to think about pricing is to look at how a service functions in a value web. What value does it provide in the web and how does it impact the pooling of profits? (Value webs compete with each other for market share, but they compete within the web for profit share).

Six steps to optimizing the value web while maximizing your profits

Choose the right scale. This is often the most difficult part of any analysis. How granular is the process map? In pricing work, we are most in the places where value is exchanged between two different organizations (ignoring for the moment transfer pricing, which works by different rules). A value web is a map of value exchanges.
Map the value web. Look at the inputs, processes and outputs for each step (node). Ask how value is created. Here is the tricky part, you have to go back far enough to pick up the alternative paths that reach the nodes you are most concerned with (the nodes where you are an input to how another node creates value).
Price your outputs as inputs to the node where you are creating value. The key to value-based pricing is to look at the impact of your prices on the next step in the web. When your output is the input into several different processes you have a strong indication that you are serving more than one market segment.
Consider other paths to the same outcome. Pricing disruption most often happens when there is an alternative path to the same downstream outcome. Zoom out and look at all of the other paths that could lead to downstream outcomes. These are the real threats to your business. On the other hand, when you zoom out and look at the wider value web, you may find new places to insert your own service.
Design your service to maximize the value of downstream outputs. The more value created in the value web the more opportunity you have to capture profit. Price to enhance downstream value of the value webs you participate in (optimize value to the customer or L2V).
Price to capture the largest profit possible. Once you have figured out how to optimize value in the value web, you want to price to capture as much of the profit as possible. Value webs compete with each other for market share but within the web for profit share).

There are different strategies one can apply to value web pricing. Apple is focused on a cost/pricing strategy that maximizes its own profit share, and as a result claims the largest share of profit in the entire mobile ecosystem. Google has taken a very different approach. Its pricing and design strategies (the two go hand in hand) are meant to maximize the value of the total value web, and it is happy to see profit distributed across that web rather than trying to make sure that profit pools at Google. (Of course it can do this because it has massive profits from its core search advertising business).

If a company like Huawei or Samsung try to replicate Google’s strategy with Android they will fail. Their place in that value web is very different from Google’s. Huawei, under pressure from the US government and not currently able to access Google apps, is said to be planning to replicate the Google led value web (see The Economist’s Sept. 20, 2019 article on this). This is the wrong strategy. If they remain locked out of the Google ecosystem, then they are more likely to succeed by building a new ecosystem around 5G where they control how profit pools (indeed, they are moving in this direction in the overall 5G market).

Key lessons

Price your service as an input into the next node in the value web
Have a clear strategy for how to maximize the value created by the value web(s) you participate in
Understand how you will design your service and pricing to make sure as much profit as possible sticks to you

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Majid Iqbal to speak at the Value Innovation and Pricing MeetUp August 22

Steven Forth — Mon, 12 Aug 2019 22:05:00 +0000

Thursday August 22 Majid Iqbal will be visiting Vancouver to speak at the Value Innovation and Pricing Meetup. If you are interested in services design and the emergence of new services led business models this will be a great opportunity to meet with one of the real thought leaders in the field.

Let us know you are coming to the Meetup!

Majid is the author of Thinking in Services: Encoding and Expressing Strategy Through Design. This is not a typical process or “how to” book. It looks deep into the underlying patterns behind all services. It begins by asking the obvious, but hard to answer, question “What is a service?” and goes on to explore the ways in which services can create value. Sixteen different elemental services patterns are identified, and ways in which most services are actually the combination of two patterns are explored. See a list of the 16 patterns below.

The patterns are then organized into a 4 x 4 grid that can be used to tell different stories around the service and to test to make sure that the service is complete. This 16x Frame is a great tool for those engaged in service design. It helps to organize the affordances (what the different parts of the service make possible) and the performance (how the service is delivered) from the perspectives of the Service Provider, the Agents delivering the service, the Service Customer, and the Service User.

The book goes on to look at the different strategies that can be implemented in developing and evolving services. This is very helpful for all those organisations that are looking to move their service offerings to the next level or to respond to new competition. Majid shows the role of net value to the customer and net value to the provider in shaping service design. The question of value is often overlooked in standard service design processes. At Ibbaka, we advocate layering value and price into customer journey maps (one of the standard tools of services design).

Why is this important to Ibbaka and our customers?

Services are playing a larger and larger role in how value is created and delivered
More and more companies are delivering technology innovation through services
Pricing bundled offers that include product, services and data is a core challenge for many of our customers
Services design and delivery require new skills and competencies
There is an emerging model of service led growth that provides an alternative path to that of product led growth

The frameworks and patterns included in Thinking in Services are proving to be very helpful in our work where we uncover value, use this to segment markets and choose targets, and then to design pricing models and processes.

Part of our work at Ibbaka involves discovering and applying design patterns. A current project includes the identification of the different patterns that can be found in value creation and monetization through data. We ask questions about how access, analysis and distribution of data creates value and how that can and should be priced. We are working on a pattern language (see Christopher Alexander) for pricing, beginning with data pricing. We suspect that a pattern language of some form will be critical to the move to Machine to Machine (M2M) pricing that we are expecting over the next decade. Majid’s work is one of the key inputs into our thinking on this.

Majid also has some interesting ideas on the role of customer experience in value and pricing. This is something that is critical to several of our customers and we will share some thoughts on his OPEN pricing model in a future post.

Outcomes - Price/Experience = Net Value

The Sixteen Services Patterns

To whet your interest for the Thursday August 22 session, there are eight services patterns identified in the book.

Pattern 1: Examine - Evaluate

Pattern 2: Maintain - Protect

Pattern 3: Restore - Repair

Pattern 4: Transform - Translate

Pattern 5: Conduct - Connect

Pattern 6: Contain - Hold

Pattern 7: Lease - Rent

Pattern 8: Display - Dispense

A page from the book is shown here.

Remember, most services will combine two of these patterns.

Have an opinion on value and services? Share them in these surveys.

Value Innovation and Pricing Insights for CEOs

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Unbundling value to align packages with customer segments

Steven Forth — Thu, 08 Aug 2019 22:04:06 +0000

In much of our work, we are asked to unbundle an offer so that it can be repackaged as a set of offers that will command a higher price. Even when this is not specifically part of the mandate, it often becomes a precursor to our work on value-based market segmentation and pricing. This opens the question though, ‘Why do offers need to be unbundled?’ and ‘How does one go about unbundling an offer?’

Please take a quick survey on Value Innovation and Pricing Insights

Before digging in, it is worth asking why offers even need to be unbundled.

Often it seems simpler to just bundle what customers are used to buying, and the company knows how to sell and deliver. Unbundling can open a can of worms and lead to uncomfortable questions about what functionality is being used and why. Nevertheless, unbundling and then repackaging can be the key to successful pricing innovation. It is difficult to price before one has done some research into how different parts of an offer contribute to value. Remember, the best pricing model is one in which the value metrics (the unit of consumption by which users get value) are tracked by pricing metrics (the unit of consumption that is priced).

The first reason unbundling can be necessary lies in product history. Most successful products began as a simple idea that filled a clear need. “How do I know the skills of the people in my company?” “How can I track prospects through a pipeline and generate reports?” “How can I distribute load between multiple servers?’ The idea starts simple. As it goes to market, the provider comes to realize that other things are needed in order to have a ‘whole product solution.’ This term, popularized by Geoffrey Moore in his classic book Crossing the Chasm, refers to all of the different functions, integrations and services needed to get value from a product. The agile idea of a ‘minimal viable product’ derives from this and is the minimum offer that can create value.

Over time, the whole product expands. New features are added. New services are wrapped around the offer. When a product is successful, and even creates a new category, a whole ecosystem evolves around it. In many cases, features and services are simply layered on top of the original idea. Sometimes they are layered on so thickly that the original vision gets lost. In other cases, the evolution of the ecosystem creates new niches and opportunities that are not well articulated at first. A patchwork of features and services sprout up to try to fill each of these niches. Unbundling is a way to see how all of the different parts fit together and how different combinations are creating value.

There are many ways to unbundle a solution.

One approach is to unbundle on a feature by feature basis. The software engineers and user experience (UX) team generally have a pretty clear idea of what features the offer has.

Another way to unbundle is to separate out features, data and services. Data, in particular, is playing a bigger and bigger role in creating value, and there is generally more than one type of valuable data locked in any application. When an application has grown into an ecosystem, the number of different types of data can be quite staggering, far longer than the list of features.

One of the key questions in unbundling is deciding how granular one should get. If the analysis is too coarse, ways in which value is being created can be missed. An example is talking about the ‘value of the data’ without being explicit about which data and how it is used. One can go too far the other way as well. Staying with data as an example; in most cases, one does not normally need to drill down to each metadata field (metadata is data that is used to describe other data).

At Ibbaka, we use a value lens to guide our approach to unbundling. Basically, before we try to unbundle an application, service or solution, we work to understand value from the buyer and user perspective. We use our standard taxonomy of economic and emotional value drivers to do this. In some cases, we expand this to include social or community value drivers.

The value drivers then becomes the filter we use to unbundle. We are trying to find the different collections of functionality and data that enable each of the value drivers. One way to do this is to build a benefit ladder, but then extend it beyond the benefit to value. See a simple example below.

Benefit ladders are a commonly used marketing tool that helps us think our way from features up through functions to benefits and on to value. Below is a frequently cited example of the Starbucks benefit ladder developed by BCG.

The important thing to note here is that there are many paths up the benefit ladder. The same feature and attribute can support several different functions. The raw GPS data has multiple uses. The same functions can have many different benefits. One way to use benefit ladders is to see if there are features that do not support functions or functions that do not link to benefits.

Take these ladders and layer on top the economic and emotional value drivers. It is the value drivers, and the paths back down from benefit to function to feature that you are trying to get to when unbundling an offer for pricing purposes.

This does not mean that each of these value clusters should be its own offer. That generally leads to too many offers and market (and pricing) confusion.

The other part of this work is to match the offers to the value-based customer segments. For Ibbaka, a good segment is one that gets value in the same way and that buys in the same way. Once one has a value-based clustering of features and functions, and a value based clustering of potential customers (the market segmentation), it is usually pretty clear how to combine them into offers. Because this has all been done on the basis of value (emotional and economic) it is easier to discover the value drivers that will inform pricing.

All of this is easier said than done. A mature application can include thousands of features wrapped in services powered by data. Data analytics often needs to be used to find the clusters of feature-function-benefit-value. The same is true for the market segments. At Ibbaka, we are pioneering techniques from social network analysis to find the meaningful and actionable clusters in data. We started off doing this for market segmentation, and we are now extending it to the unbundling part of our work.

Reach out to us if you would like to explore how your applications and services can be unbundled then put back together in ways that create compelling value for specific market segments.

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Welcoming Alexis, Brent and Jessie to a larger Ibbaka

Steven Forth — Thu, 25 Jul 2019 15:00:00 +0000

People Insights + Market Insights delivers Profitable Innovation

(In the spirit of collaboration, this is cross posted to the TeamFit blog.)

Later this year we plan to combine the people insights platform developed at TeamFit with the market insights work being done at Ibbaka to create a new business (subject to shareholder approval). The two companies have already worked together on a number of projects. In 2018 we collaborated on research into the changing skills used for pricing, and we are now taking that to the next step, building a competency model for pricing excellence. In 2019, we have shared projects on competency models for innovation and customer experience and are doing joint R&D on applications of clustering models and other applications of AI.

The collaboration is already paying dividends, generating new business and ways of solving problems. Our larger vision is to use insights into innovation and market opportunities (driven by Ibbaka's market research and pricing business) to help our customers know where to create and capture value, and then support execution through insights into the skills and teams needed to deliver (we do this using TeamFit's skill and competency platform and its application of AI to identify future skills).

To support this growth, three new people have joined us recently: Alexis Katigbak, Brent Ross and Jessie Tai.

As a student, Alexis led the University of British Columbia (UBC) team that built the prototype for what is now the TeamFit People Insights platform. She will be leading our work in data integration (our platforms are data hungry) and partnering with other companies working towards the same goals of more effective innovation and resilient and adaptable workforces and careers.

“We can influence the future of work for organizations that want to be intentional in how they approach their markets and how their people grow.”

— Alexis Katigbak

Join us in welcoming these three very capable to the team. We are looking forward to seeing how they will change us.

Brent Ross brings us deep experience in culture and change management. He is responsible for customer success and for building a library of open source competency models that will create value for our customers and community.

“I love helping teams navigate complexity and find connections between seemingly disparate things. Core skills that contribute to this ability are systems thinking, asking really good questions, empathy, communication, and strategic thinking.”

— Brent Ross

Jessie Tai was our star intern while at UBC and now that she has graduated she is joining the team. Jessie combines a great analytical mind with discipline and focus (she is also a top level Ultimate frisbee athlete) and is working on many of our projects, connecting the different strands.

“By spearheading and developing best practices in pricing, I believe our impact will continue to strengthen and grow.”

— Jessie Tai

We asked them a series of questions to help us think through how to make them successful.

What impact do you want to have on the company and its community (which includes users, customers, stakeholders, thought leaders, community and the communities we operate in)?

Brent: I think my highest aspiration is to accelerate innovation in part by helping people get more connected to purpose. Not the kind you read in a mission or vision statement, but the sort of purpose you experience more deeply on a day to day basis. When pricing and marketing strategies are well-designed, they connect organizations and their people more directly to the unique value of the business and their impact. Ibbaka also fosters greater self-awareness around individual skills and aspirations through TeamFit Profiles, which in turn can lead to a greater sense of one's own uniqueness and ability to have an impact. Collaboration is essential to this end, and so I also hope to help our customers and partners connect in meaningful and impactful ways with each other.

Alexis: I want to help build products that enable our customers and users drive value in their businesses - whether that's developing the awareness and capabilities of the people that enable this, or uncovering the insights needed to reach their target markets and business goals.

Jessie: I hope we can inspire other start-ups to strive to be the best at what they are doing and believe in their abilities. Ibbaka should have the impact on customers that we are the true leaders in the pricing industry and can take on any challenge. I hope our work can open the eyes of the SaaS and IoT community in regards to pricing. By spearheading and developing best practices in pricing, I believe our impact will continue to strengthen and grow.

What experiences are you bringing to Ibbaka that will shape how you approach your work?

Jessie: My history in competitive team sports has created many transferable skills when it comes to my work with Ibbaka. Skills such as teamwork and communication has always been a strong suit of mine and proven effective in the sport and work environment. Another aspect of competitive sports is the importance of individual training. This calls for a focus on personal goals and performance while testing one's own endurance and intensity. This individual experience translates well to my personal drive in work and mental focus during projects.

Alexis:Vision Critical served organizations that wanted to truly understand their customers and Lululemon had a very highly engaged loyal community. These experiences shaped my product philosophy to one of co-creation and continuously delivering value to customers, users and their communities.

Brent: Throughout my career, I've made a point of working across multiple functions and industries with the goal of bridging disciplines, as well as consistently improving my ability to make connections in the bigger picture. I only recently learned that I fit the profile for what the Center for Creative Leadership calls an 'agile learner', which as it turns out, is often the opposite of becoming highly specialized in a single role or function. I also grew up living in a total of five countries including Canada and moved nine times between the ages of two and sixteen. Moving around helped me cultivate deep empathy and curiosity. The combination of these traits is is at the center of how I approach my work with customers, colleagues, and partners.

What are your core skills today? What are your target skills?

Brent: I love helping teams navigate complexity and find connections between seemingly disparate things. Core skills that contribute to this ability are systems thinking, asking really good questions, empathy, communication, and strategic thinking. In my current role, I'm actively working on building my skills in customer success, strategic partnerships, business development, product marketing, and competency modeling.

Jessie: Core: organization, problem solving, empathy. Target: project management, design thinking.

Alexis: Core skills are active listening, agile delivery, customer discovery, product strategy and being organized to a fault. Target skills are ongoing growth in areas such as market dynamics, financial modeling, go to market and team development.

What are your passions, beyond work?

Jessie: I have a passion for sports. I’ve been very fortunate to be involved in countless sports since a young age. Some of my favourites include swimming, basketball, volleyball, baseball, track, javelin, discus, and my current favourite, ultimate frisbee. Fun fact, I play on the top Vancouver women’s ultimate team and we will be competing in Canadian and US nationals.

Brent: I'm a portrait photographer, and I love the process of connecting with people to frame and capture their uniqueness. But like anyone who picks up a camera, I also love to capture the emotion I spot in moments of the day-to-day. I have a background as a musician and singer, and I'm a fan of the ballet. The most inspiring work I've ever seen was a ballet titled, 'Within the Golden Hour' by Christopher Wheeldon. If you get a chance to see it, go!

Alexis: Endless curiosity around food, books and yoga. It is through these activities that I am able to connect to other people, cultures and worlds (fictitious or not)!

Over the next five years, what can we do to make the world a better place?

Brent: Let's face it - humanity needs to seriously up our awareness of how we are connected to the world around us and to be consistently innovating from that place. Our offerings support the kind of accelerated learning needed to help make this happen. The more we can do to help individuals and companies realize their full potential, the better.

Alexis: We can influence the future of work for organizations that want to be intentional in how they approach their markets and how their people grow.

Jessie: We should continue to expand our team of intelligent and passionate individuals. Alongside this, we can continue to foster a unique environment where the team can grow and work together. This will lead to the natural collaboration of ideas and an organic formation of relationships. Expansion and the continued focus on a healthy work environment will lead to creation, problem solving and development that will make the world a better place.

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Pricing across maturity models

Steven Forth — Tue, 09 Jul 2019 21:15:43 +0000

Maturity models are enjoying their moment in the sun. Over the past thirty years, they have developed from a nerdy preoccupation of process and policy geeks (I used to be one of those but claim to be recovering), to a key organizational development tool, to an important marketing framework. Over the past few years, they have increasingly been used to shape pricing strategy.

Please take our survey Value, Innovation and Pricing Insights from CEOs

We mentioned this in our recent post Pricing your solution portfolio: Part 3 - Looking for Interactions and even referenced the Job Architecture Maturity Model in our post on Why your job architecture needs a competency model on our People Insights blog.

This provoked some questions from our readers on just how to use a maturity model to inform your pricing strategy, and we try to answer these here.

Let’s start by asking what a maturity model is and how they have become so important. The current incarnation got its start back in the mid-1980s when it was realized that software development was expensive, complicated and that not all organizations do it well. This resulted in the Capability Maturity Model (or CMM) developed mostly by the Software Engineering Institute at Carnegie Mellon University. The initial work was mostly funded by the US defense sector, which realized how much it was coming to depend on software for all aspects of operations. The CMM is now the CMMI (Capability Maturity Model Integration) and has its own organization, the CMMI Institute. Those interested in maturity models can find a wealth of information there.

The original CMM was focused on process. Over the years this has shifted in many cases to a concern with outcomes, but let’s look at the initial idea. The archetypal maturity model moves across five stages from 1, no process, to 5 where processes are constantly being optimized. (This image comes from Sally Godfrey who is one of the world’s leading experts on maturity models.)

From their initial applications in software, engineering maturity models have branched out into all sorts of surprising areas. Here are some examples.

The research and advisory group Brandon Hall uses maturity models extensively. Here are two examples, a Learning Technology Maturity Model and a Team Performance Maturity Model.

OpenView Venture Partners and the Technology Services Industry Association (TSIA), both organizations that we work closely with, have each published maturity models for customer success. Understanding the business impact of customer success and how to monetize it is an important question for many organizations these days.

There are of course ‘pricing maturity models’, this one from the European Pricing Platform.

Paul Hunt and Jim Saunders have even written a pricing book organized around pricing maturity. See World Class Pricing: The Journey.

A close reading of maturity models (and there are hundreds of these available) suggests that they have been evolving from a focus on process to a greater concern with the outcomes each phase is meant to deliver to the organization. This maps quite well to emotional value drivers. At Ibbaka, we use Maslow’s hierarchy of human needs to organize emotional value drivers and understand their impact on pricing. Generally speaking, the higher the emotional value driver on Maslow’s hierarchy, the greater the pricing power.

So how can a maturity model help you with your pricing strategy? It all comes back to value. Let’s assume there is a maturity model available for your solution. If there is not, then you should consider developing one. The value drivers at each level of the maturity model are going to be different, and this is true for both emotional and economic value drivers.

For emotional value drivers, the higher levels of the maturity model map quite well to the higher levels of Maslow’s hierarchy of human needs, and in our work we have found that there is more pricing power at the higher levels of maturity models.

With economic value drivers, the situation is a bit more complex. Here one has to go deep into how you are creating value for your customers and what new value is added at each stage of maturity. Keeping with the classic, process-oriented approach to maturity models, here is one possible mapping. Note that the value comes from moving from one level of the maturity model to the next.

Level 1 to Level 2: From random to managed.

Emotional Value Drivers cluster on basic functionality.

Economic Value Drivers are often weak at this point and focus on error or risk reduction. This transformation is necessary to set the stage for future value. If this is all your solution does, you are likely to struggle to claim a decent price.

Level 2 to Level 3: Moving from managed to defined.

Emotional Value Drivers cluster on security.

Economic Value Drivers are often based on efficiency. Improved efficiency can have many positive economic outcomes and it is worth working through all the different ways this can impact the customer business model. Improved efficiency is not limited to operating expense reduction. A more efficient pipeline can lead to higher revenues. Efficiency can also make current capital investments more productive, thereby delaying the need for further capital investments. Many innovations have their first impact at this transition.

Level 3 to Level 4: From defined to controlled.

Emotional Value Drivers cluster on security and self-esteem. Note that ‘community’ was skipped over. Process-oriented maturity models generally do not lead to community. This is not true with other types of maturity models. Maturity models built around the type of outcome often include emotional value drivers based on community.

Economic Value Drivers. Once a process in controlled it becomes predictable. This can be an economic value driver in its own right. Predictability does many things for a business. It makes resource allocation more efficient and helps rationalize investment. At present, most successful business solutions are focused on one form of control or another. This should not be the end-point. If you stop here, some smart competitor will find a way to take your customers from controlled to optimized.

Level 4 to Level 5: From controlled to optimized.

Emotional Value Drivers. We are finally getting to self-esteem and self-realization (at least for process nerds). It is unfortunate that so few business solutions (at least those realized in software) are actually able to do optimization. Optimization generally entails exploring complex design spaces and avoiding local optima, those traps that prevent us from getting from an acceptable solution to a better solution. This is still a hard problem for computers, even with AI, and most transitions from Level 4 to Level 5 require some level of professional services.

Economic Value Drivers. Optimization has greater potential for economic impact than the other stages combined. It generally takes a lot of work to quantify optimization value drivers, and many conversations with customers. But if you have helped a company move from one stage of a maturity model to another you will have built up the trust needed to have these conversations. This is where the greatest value is created, and it should be the destination that your customer success organization is designed to deliver.

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Pricing your solution portfolio: Part 3 - Looking for Interactions

Steven Forth — Thu, 04 Jul 2019 23:50:04 +0000

This is Part 3 of a series of four posts on pricing a solution portfolio.

Part 1 - How Pricing Changes Over Time

Part 2 - Setting Goals

Part 3 - Looking for Interactions (This Post)

Part 4 - An Integrative Solution

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This series is focussed on the challenges of pricing a portfolio of offers. In the first two posts, we looked at how pricing changes over time and how to set goals for a portfolio of offers. Now, we move on to the most difficult part of pricing a solution portfolio. Working out how to make the interactions between different offers work in your favour. We also look at some of the pitfalls.

There are three key things to consider in building a portfolio: framing, paths, combinations (packaging and bundling). Using these together is the key to successful portfolio pricing.

Framing the portfolio

Behavioural economics and prospect theory have taught us the importance of framing perception and decision making. Each offer in your portfolio frames the others and one has to plan how potential buyers will compare offers to each other. The sequence by which this comparison is made will also shape willingness to pay (WTP).

Which part of your portfolio provides an anchor, relative to which other offers are compared? This is one of the critical decisions to make. If you leave this to chance, you will lose control over how your pricing is perceived. There are several strategies possible here. Take the example of two restaurant chains. One is positioned as a family restaurant offering great value for price. The menu is designed to call people’s attention to the top right offer, which is designed to have a low price point but to lead the customer to add-ons needed to fill out the meal. The customer enters the buying process with the framing that ‘this restaurant offers great value.’ Another restaurant, right across the street, is positioned more up market. It wants to attract people who are giving themselves a bit of a treat, perhaps celebrating a life event. Its menu has a very different design. There is no low priced special. There are specials, but they are priced higher than the daily fare and positioned as being something special or in season. The goal is to frame a high price so that the rest of the menu seems reasonably priced. When we analysed spending for each business the average was about the same, but for the family restaurant the median was lower than the mean (the distribution had a negative skew) and for the destination restaurant there was a positive skew. Speaking with the owners (who asked not to be identified) it was clear that this was a strategy and that each was aware of what the other was doing.

Never make a pricing decision based on averages without checking the skew of the distribution.

A full understanding of framing and its effect on decision making requires a good understanding of behavioural economics, something we will dig into in future posts.

Paths through the portfolio

In most cases, there will be a defined set of paths that you want customers to take through your portfolio. Designing these paths and the pricing that supports them is a key part of portfolio pricing design. These paths are also known, in sales, as upsell and cross sell. Ideally, upsell occurs as a customer becomes more and more able to take advantage of advanced functions to get more value. Cross sell is most successful when the combination of two or more offers, each of which provide value independent of the other, provide even more value when used together.

One way to think through paths through a portfolio is using the concept of a maturity model. These models are popular in many contexts and smart companies are developing maturity models that guide upsell. The basic idea is to have an offer for each stage of the maturity model and a well supported path to get from one phase to the next. Below is an example of a Customer Communication Maturity Model from GMC software. This makes the upsell paths clear. The pricing challenge is to capture more revenue as one moves up the maturity model while not putting in any barriers that discourage customers from using your solutions to get to higher and higher levels of maturity.

There are other ways to think about paths, especially in the context of the technology adoption lifecycle. (see Pricing strategy changes across the technology lifecycle). Paths are especially important when the market is transitioning from one phase of the lifecycle to another, but not all parts of the market are changing at the same time. For example, at the end of life one will want to have well defined paths that lead customers to the next generation of your solution.

Combining parts of the portfolio

The other consideration in portfolio pricing is understanding how different offers will be bundled to appeal to different parts of the market. To do this well you need to have a well thought out value-based market segmentation (see Why good pricing strategy starts with market segmentation). Bundles should be designed for each target segment. Take a holistic approach to bundling. In today’s world, a bundle usually includes products (often priced using subscriptions), professional services and access to data. Your pricing model has to be able to integrate each part of your offer in a way that helps to communicate value and that will make sense to your customer.

Here are five questions that can help you find the interactions between different parts of your portfolio and design an effective portfolio pricing strategy.

What is your value-based market segmentation and what segments are you trying to target?
Are the segments independent or do they interact with each other? (One segment may act as a reference for another, or there could be great markets.)
How do offers frame other offers, within a segment and across segments? (Framing needs to be designed to align with your strategy and positioning, think of the two restaurants described above, who used very different farming strategies.)
What paths do you expect customers to follow through your portfolio as you cross sell and upsell?
How will you combine offers (including professional services and data) to provide exceptional differentiated value for your customers? (Differentiated value is the value that you provide that it is very hard to get from a competitive alternative. It is the source of your pricing power.)

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Buying behavior and AI are transforming pricing - an interview with Craig Zawada of PROS

Steven Forth — Thu, 27 Jun 2019 15:00:00 +0000

Craig Zawada has been shaping our thinking about pricing since 2004, when the first edition of The Price Advantage was published. This book, co-authored with his McKinsey colleagues Michael Marn and Walter Baker and published in a Second Edition in 2010, introduced many of us to critical pricing concepts like the Pocket Price Waterfall and Value Maps. Then, in late 2010, he surprised many of us when he moved to the leading revenue management software company PROS as Chief Visionary Officer. We caught up with Craig recently after he gave a compelling keynote talk at the Spring Professional Pricing Society conference in Atlanta.

Ibbaka: What drew you into pricing? What experiences from outside of pricing do you bring to your work?

Craig: I didn’t plan to get into pricing or become a consultant. My original goal was to run an outfitting company and spend my time outdoors. But I did go and do an MBA, at York University’s Schulich School of Business in Toronto, and I interned at Ernst & Young. One of my projects was to design new pricing for a door skin manufacturer in Quebec. The project was very successful and when I followed up with them months later they were delighted with the measurable impact of the work. We know that does not always happen in consulting. I realized that pricing was a place where I could both have an impact and make a contribution to the basic ideas. Pricing brings together strategy, analytics, people and business impact.

Ibbaka: Moving from McKinsey to PROS was a big change. What changes when you move from consulting to leading a technology platform?

Craig: I worked at McKinsey for 13 years and was a partner co-leading the pricing practice. It was at McKinsey that we got the experience and developed the ideas in The Price Advantage book. When I had the opportunity to learn more about PROS, I was impressed and intrigued by the possibilities of applying technology to pricing. The early companies in pricing software had been focused on estimating price elasticity and using this to try to set prices. It didn’t really work. PROS came in with a different approach.

Their background was in pricing science. Rather than applying theory they were building up their models through experiment and observation. They were able to connect pricing science to revenue management to solve some important pricing problems – and it was working extremely well.

Many McKinsey clients needed this as part of the solution. We often built tools for clients, but these were generally fancy spreadsheets that were hard to deploy and manage. Pricing discipline needs to get built into the technology and this requires a software platform. Moving to PROS let me help shape a technology platform that can be used to drive pricing strategy. I have never looked back. My guess on where the market for pricing expertise was going proved to be correct.

Strategy consultants tend to take a deductive approach to pricing strategy. They spend a lot of time gathering data, figuring out what it means and then making recommendations.

With a technology platform one can take an inductive approach. One generates hypotheses and can then use the software platform to test the hypotheses. With a software platform one goes through a process of modeling, testing then evolving. One can do this much faster and in a more sustainable way than a team of consultants alone are able to do. There is a significant opportunity for the strategic pricing consulting firms to work with technology like PROS to deliver value to their clients.

PROS is a great company to do this as we have a long-term view of the market and we put our customers first. We reinvest close to 30% of our revenues into research and development, which is much higher than most software companies. We do this to continue to lead innovation.

Ibbaka: You have spoken about the ways in which the buying process is changing and how that will lead to changes in how prices are set, managed and communicated. Can you share your latest ideas on this?

Craig: We commissioned independent research into this over the past year. Based on this research we are seeing a number of trends which have major implications for pricing.

First, is that the sales experience is driving revenue growth. Look at this data from CEB. Sales experience accounts for 53% of the buyer’s decision. This overwhelms all other aspects. B2B buyers increasingly expect the sales experience to be fast, frictionless and relevant. How value and price are communicated is a key part of this. Which brings me to the next major change.

PROS is on the cutting edge of delivering on this “inductive approach”. PROS customers express delight in the innovation roadmap saying that they expect PROS solutions to deliver on their pricing needs for the long-term. PROS delivers on the requirements of some of the most sophisticated pricing organization and leverages that innovation to help organizations just getting started in their price transformation journey. Our experience across hundreds of implementations allows us to guide businesses to fast and meaningful ROI through price improvement.

The second thing is that speed is the new currency. Here is the slide I used for my PPS (Professional Pricing Society) keynote.

This was a critical insight for one of our major customers. This company sells through channel partners and they were finding that win rates went down 40% if the response took more than 24 hours for a quote. Further analysis showed that determining price on a deal accounted for 67% of the time required to make a quote. Most pricing groups are not tracking the length of time it takes to generate a quote, but this is emerging as a critical metric for pricing performance.

Now that pricing is part of customer experience, we need to think about our pricing teams differently.

Just putting list prices on the website is not enough to accomplish this. There are a lot of challenges in doing this today as one is either going to set a high price and have to negotiate, which slows things down, or one does not frame things properly and leaves money on the table. Buyers want to get transactable prices online. This is one way that the B2C experience is impacting B2B. Buyers are increasingly not going to put up with a lack of transparency or a slow buying experience.

In some cases, buyers are willing to pay a price premium for fairness, transparency and speed.

Another important change in buyer behaviour is that people are trusting algorithms to set prices more than they trust people. When you get caught up in a price negotiation with two people there is always a concern that the other side has out negotiated you. Not many people enjoy buying a car from a car salesman. A well-designed pricing algorithm gives a sense of authority and independence from human bias. We had a sense that this was the case, but we were surprised when our independent research found that about 2/3 of B2B buyers preferred algorithms to determine pricing rather than negotiating price with a seller.

Traditionally pricing guidance has been framed in terms of ‘floor,’ ‘target,’ and ‘expert’ prices. This begs the question of what do you do when you can only present one price? Pricing software algorithms use data to answer this question.

Most enterprise pricing has been 80% high touch and 20% “no touch”. We expect this to switch to 20% high touch and 80% algorithmic, “no touch” pricing.

Ibbaka: How will it change the role of pricing software and other applications?

Craig: In a fundamental way. Pricing professionals will think differently about how to drive business with pricing. In the near future it will be the technology that enables and drives strategy. Pricing power will come from how businesses create impact, and this means getting comfortable with letting the technology drive pricing decisions.

This includes aligning with your customer’s need for speed. ‘Time to price’ will become a critical metric. To achieve this, pricing will need to work with smaller, agile teams and avoid getting bogged down in deal desks.

Pricing technology will enable strategy by making possible hypothesis testing, the rapid exploration of different pricing models and much better portfolio management.

Ibbaka: Who is good at this today?

Craig: The airlines have been doing this for over thirty years. These ideas are now relevant to B2B. Examples are dynamic pricing, unbundling and a focus on customer experience. Airlines have to operate with big fluctuations in demand.

When the Toronto Raptors made it to the NBA Finals, their fans wanted to be there and demand for flights to San Francisco ticked up quickly. For the sophisticated airlines that leverage AI-powered Revenue Management technology like PROS, the system sees the surge in demand and quickly adjusts their ticket offerings to optimize the balance between their inventory and demand.

Ibbaka: You and PROS have a great deal of expertise in AI and machine learning. How will AI change pricing and related areas over the coming decade?

Craig: The impact will be substantial. The first thing that needs to happen is that people be able to evaluate claims about AI. Many claims are being made and there is a lot of noise in the market. People need to understand the basics of AI and be smart at evaluating what is most relevant for their business.

Artificial Intelligence applies well to pricing since there are quantifiable and measurable ways in which the algorithm can continue to learn from new results. However, it is necessary that the system be purpose built for pricing in order to deliver on the unique requirements for price segmentation design, price testing, scenario modeling, and price rationality. Accuracy and precision in the price outputs are vital as you can do great damage by presenting the wrong price to a customer.

Effective application of AI depends on meaningful data and those built for pricing are able to integrate transactional data with marketing data, CRM data, and external signals. The algorithms improve and deliver more precise, relevant recommendations/decisions as they incorporate different types of data. They get smarter over time, so the earlier you start the more opportunity your AI has to gain capability.

AIs are already giving better pricing advice than ‘pure judgment’ and they are only going to get smarter.

Ibbaka: You have chosen an extraordinarily beautiful place to live. Can you share some of the best things about it?

Craig: Yes, I moved to Kimberley, British Columbia in 2009. My family and I wanted to be closer to the outdoors. The area is great for hunting, fishing, hiking, skiing, just about anything outdoors. It is easy to get to Calgary and from there I can get anywhere I need to go.

We live off grid using a micro-hydro electric power system. There are a lot of possibilities here.

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Things are changing in technology services - an interview with Laura Fay of TSIA

Steven Forth — Wed, 12 Jun 2019 23:54:45 +0000

Things are changing in the technology industry. What was once a world of technology asset sales with attached support and implementation contracts, delivered by customer support and professional services whose concern was with post sale break/fix support, installation, configuration and support of systems, has become something fundamentally different.

This was clear at last month’s (May 2019) Technology and Services World event in San Diego. The main themes of the event were customer success (over on the People Insights side of our business we are developing a competency model for customer success) and the need for companies to find ways to sustain scalable and profitable growth with a healthy recurring revenue business model. One prescription given was to do this by augmenting subscription offers with the complementary services that would assure customer success.

Customer success delivers real value in the form of adoption services. Monetizing that value is what should be priced. This got our attention as value-based pricing nerds. We reached out to Laura Fay, VP Research & Advisory, XaaS Product Management, at the Technology Services Industry Association (TSIA) to get her insights into the changing nature of technology and services offerings and how this will impact pricing. We first met Laura in Chicago at the Product Development and Management Association (PDMA) back in November 2018.

Ibbaka: What do you bring from your past experiences into your current role at the TSIA?

Laura: I bring three decades of technology, products and services experience to TSIA. I started by career in engineering. I got my first degree in computer science and worked in big tech at the beginning of my career. From there I went on to product management positions and then to general management. I have worked on everything from a raw startup with two people and an idea to very large companies like IBM. I’ve experienced the cycle of starting a company, growing it, going through an acquisition, and then starting again. It is useful to see the full range of challenges over companies at different stages of growth and scale.

I lived the transition from perpetual technology license deployed on-premise to SaaS (Software as a Service) twice. It can be a tough transition for product people. Shifting to a service mindset and accelerated release cadences is a big culture change. Sales, finance and all the other functions have to change as well. Overall this experience opened my eyes to how challenging that can be for companies and their customers.

Just prior to joining TSIA I made a pivot to focus on value realization by starting and scaling a customer success function. The world begins to look quite different when you focus on customer value realization as opposed to the Product Management world of value creation.This is especially important with subscription models. Companies will only be successful if the subscriber experiences value you’ve created and renews the relationship. There are huge implications for the business.

The opportunity to join TSIA’s research & advisory team came along at the right time. I wanted to take all of the knowledge and experience I have gained over the past years in the technology industry and apply them to a wider range of companies. TSIA let’s me do this.

Ibbaka: What is your current role and what impact would you like to have?

Laura: TSIA’s mission is to increase revenue and profit performance of technology companies. We engage in primary research across the industry and uncover patterns of success - that is, proven practices that correlate with positive business results. We then help our members to understand and apply these proven pacesetter practices. We help our members move from identifying business challenges to the people, process and technology capabilities they need to succeed. We do this through data, frameworks and actionable guidance that lead to improved performance. Further TSIA’s trusted community of business leaders 600+ memberships from 35 countries and including 80% of theFortune 100 Tech firms is an unparalleled resource for our members.

My role is VP Research and Advisory for XaaS Product Management. This research practice focuses on aligning and optimizing practices in product management to accelerate scale of the XaaS business resulting from success of the XaaS offers in market. I help companies understand where the opportunities are in XaaS (you could call this ‘anything as a service’) and product management’s role at the epicenter of impact in the as-a-service revolution.

Product organizations are often horizontally oriented and focussed on building features and functions of benefit to the widest possible range of customers. Their businesses are often selling technology to an IT buyer. In most of these cases, the purchase comes out of the customer’s CapEx (capital expenditures, that get amortized over time). The customer support function is an afterthought to cover for gaps in QA and design. Basically, once the sale is done the job is done.

XaaS models are completely different. Services have to be repeatable. The focus is on the value proposition to a new, and often additional, business buyer. The buyer comes from the line of business and is buying out of OpEx (operating expenses). Real value has to be delivered for services to be consumed on an ongoing basis. In services, you have a lot more skin in the game. With XaaS, the sale is the beginning and not the end. Success depends on getting adoption, supporting engagement and then making sure that value is actually being realized by the users of the service.

In XaaS, the vendor has to be proactive and shape the customer experience. The metrics that matter are ARR (Annual Recurring Revenue), retention and churn (how much recurring revenue is retained or lost in any period), adoption and engagement, and above all, customer outcomes. Customer success is about delivering customer outcomes.

The most successful services business’s business are vertical not horizontal. Success depends on a deep understanding of the customer.

Ibbaka: What are the key trends you are seeing in XaaS? (We can supplement this with links to your publicly available research).

Laura: The first thing people need to accept is that SaaS companies have struggled to get operating scale into their models. It has taken Salesforce more than 18 years to deliver operating profits. Most of the best known SaaS companies are not profitable on a GAAP basis.

TSIA’s Cloud40 Index identifies the performance attributes of companies with a XaaS business models. It is a representative sample of 40 companies including PaaS, IaaS, SaaS categories. I reviewed the XaaS performance model recently at Technology & Services World Conference and recently wrote about the critically important role that Product Management plays in shaping and accelerating XaaS success.

The Cloud 40 index tells an interesting story. When the vast majority of revenue is derived from the technology subscription, we’ve seen that it’s very hard to make money with that model. Why?” Embedded., non monetized support costs in addition to hosting costs are eating away at gross margin and revenue growth is propped up by high sales and marketing spend. We can see this when we look at XaaS Business Model Performance Review.

The answer may be in providing a ‘Complete Offers,’ one that combines the technology with data, analytics and services. A historic equivalent was referred to as ‘Whole Product”.

Ibbaka: How does this relate to ‘product led growth’?

Laura: I see product led growth as very complementary to complete offers. The offers must be complete and they have to deliver value. Product led growth can be a powerful go-to market strategy to complement the complete offers that cost effectively and predictably drives sales, customer adoption, expansion and long term growth. The technology solution must continually unlock value for the customer.

Ibbaka: How are these trends impacting pricing?

Laura: Value and outcome based pricing depend on having a Complete Offer. As mentioned earlier, Complete Offers are offers that include the necessary technology, services, data and analytics to ensure the customer realizes value and achieves the desired business outcome.

Market based pricing remains the most popular pricing model today, reflective of ‘me-too’ offers highlighting feature function priced by user by volume. Born in the cloud companies tend to talk about value but use market based pricing. There is a disconnect here. These companies have to make the move to value based pricing.

Companies are establishing their pricing model close to product launch time rather than coincident with the offer and product design, potentially missing the opportunity for pricing to have a strategic impact on design to drive the desired customer behavior.

Customers have demonstrated willingness to pay for the value delivered in the ‘complete’ offers. When they exist, see less price erosion from discounting.

When transitioning to XaaS, companies need to completely rethink the price-value package. Too often they just take the old license and divide by five. When you factor in the ongoing support and the other costs that are part of the model this leads to pricing that will not deliver sustainable profits.

And just offering the same technology as a perpetual license to offering it in subscription license form does ignores the ongoing commoditization trend of many technologies.

Effective XaaS pricing must be built on the value proposition.

The offer has to deliver the promised outcomes.

In XaaS a vertical go-to-market strategy takes on increased importance to the profitability picture. In this context, verticalization and segment specific pricing becomes core.

To do this, you have to deeply understand your customer’s business. It’s delivery domain specific value that drives a willingness to pay.

TSIA can help with data, best practices, outcomes and community of peers as companies walk along this path.

As mentioned earlier, many born in the cloud companies tend to talk about value and outcomes but really are providing access to technology offered with market based pricing. There is a disconnect here. These companies have to make the move to value based pricing built on thier complete offers.

Giving away too much for too little undermines business viability, which is what we are seeing in a lot of first generation cloud companies. The only way to avoid this is to put pricing at the beginning of innovation. Doing this will change the solution. We are starting to see this change. People are starting to think about pricing earlier in the value creation phase of their product lifecycle.

Ibbaka: What new skills will be needed to respond to these trends?

Laura: Based on our research, there are new skills needed around offer management and pricing design management. (Ibbaka’s People Insights business is also working on a competency model for pricing design).

Success requires having a dedicated pricing function with deep skills. Pricing skills support many parts of the organization. They inform offer design, but they also contribute to value-based communications in marketing and sales. When value is effectively communicated to the buyer we see less price erosion from discounting.

Some of the skills needed for pricing are financial modeling, which is more than just spreadsheet manipulation, understanding the psychology of pricing and willingness to pay, market segmentation, solution imagining and design, customer knowledge and of course marketing, sales and product management basics.

Ibbaka: How will these changes lead to better business practices?

Laura: As they say, what gets measured gets managed. So we need to start measuring the value being delivered. This means we have to model the ROI (Return on Investment) for the customer.

Too many companies think that scale and profit will just come with top line growth, but the experience of the first generation of SaaS companies shows that this is not necessarily so. (Tom Nagle, author of The Strategy and Tactics of Pricing, made a similar point in our interview with him “Value-Based Pricing’s Senior Statesman Tom Nagle on the Skills Needed for Pricing Expertise”).

Managing profitability requires good pricing strategy and execution. Companies need to pay close attention to their revenue mix and proactively determine the real profit contribution of each component. This is turn depends on their customer mix, which will reflect their market segmentation.

Pricing has to be an ongoing effort. It is not something that is set once and then done. Market understanding, the product design, the complete offer (technology, services, data and analytics), and pricing need to evolve together.

Ibbaka: And what do you do when you are not leading the transformation in XaaS?

Laura: I love to cycle and hike. Recently I completed the Portuguese Camino route. It was a 227 kilometer (140 mile) ride from Porto, Portugal to Santiago de Compostella, Spain.

It was really great. I met people from all over the world and experienced great food and wine along the way.

Closer to home, I like to hike particularly alpine hiking. I have recently completed 60 of 167 miles of the Tahoe Rim Trail. I am doing that in a series of long day hikes.

Being outdoors for extended periods gives me time to relax and refuel.

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