Now let’s picture the documents that tell you only what you need to know. Recipes, for instance. They tell you:  Get these specific things out of the cupboard or fridge … if you don’t have some items, buy them … and this is how much you need … now do these actions in this order. Recipes walk you through only the ... Continue reading entire post on next page ... »]]> Think of the times in life when you are barraged with a tidal wave of information, but all you really want to know is, “what do I really need to know?” That inch-thick stack of mortgage paperwork. Credit card agreements. Mobile phone instruction booklets. Automobile owner manuals. Insurance policies.

Now let’s picture the documents that tell you only what you need to know. Recipes, for instance. They tell you:  Get these specific things out of the cupboard or fridge … if you don’t have some items, buy them … and this is how much you need … now do these actions in this order. Recipes walk you through only the actions needed to get the desired result.

Recipes do not tell us all information there is to know about cooking and baking and the foods we’re making. There is a reason why measurements should be precise when baking. There is a science to proper substitutions. There is a method behind why some foods are ideal paired together and others should never touch each other on the same plate. But a recipe doesn’t get into all that. If you want more information, there are plenty of books and Internet sites where you can learn.

CRM contains an entire library of information about customers and sales. But you don’t need the whole library all the time. Isn’t it counterproductive to walk into a library and face stacks and stacks of books when all you want is a book about how to train a new puppy? No one just wanders the shelves containing millions of pages of information if they’re seeking a specific solution and they need it fast. Instead, there’s a simple search method that gives a few choices, and it gives the brief information needed — in this case, a code of letters and numbers – to quickly and easily find the location of the right book.

Our vision is to do this for CRM. To deliver only the information that sales reps need each day to take action. To deliver only the most relevant information, e.g. the information that leads directly to actions that will produce sales and revenue and keep profitable customers happy.

We believe that less information is often more valuable.

So, how much information — and what kind of information – are your sales reps receiving? How can you make it actionable information, more like a recipe?

Sourcing new outbound leads is a never-ending endeavor for sales and marketing. Prophesies of cold calling being dead have not come true if only for the simple reason that prospecting through all channels must be on the table to fuel the engine of sales growth.

Companies typically procure lead data from four main types of leads:

Compiled lists: The likes ... Continue reading entire post on next page ... »]]>

Sourcing new outbound leads is a never-ending endeavor for sales and marketing. Prophesies of cold calling being dead have not come true if only for the simple reason that prospecting through all channels must be on the table to fuel the engine of sales growth.

Companies typically procure lead data from four main types of leads:

• Internally-generated leads: Referrals, word of mouth, events, etc.
• Intelligence-based leads: Newsfeeds, industry alerts, personnel changes, etc. InsideView is one good example of this, but we believe LinkedIn also fits this mold (the evolution of this is exciting)
• Special or vertical lists: Trade associations, commerce groups, organizations operating with a geographic charter
• Compiled lists: The likes of D&B and InfoGroup, including credit files

But as any sales or marketing manager knows, simply dumping more records on a sales rep is a thing of the past. Lead nurturing and scoring are the norm, wherein prospects are nurtured until they raise their hands as hot leads, and are then forwarded to sales. In addition, predictive modeling that identifies the most likely prospects based on the “ideal customer” profile must be part of the mix.

It’s clear that the prospects at the top of the funnel – the ones you might pay for – are not sales ready. Further criteria and filters must be added which reduce the number of truly viable sales-worthy leads. Let’s take a look at how the leads get whittled down in the pipeline – we call this the “prospect waterfall:”

The net result is, if you are paying for leads and then “throwing away” 55% of the records (typical from our experience), your true list cost goes up by almost 125%. Add the additional processing cost, sales rep fatigue and opportunity costs, and you can see why your prospecting results and ROI are not what you had hoped for!

For best ROI, pay only for what you use.

If your current processes throw away prospect records that you paid for before the sales reps see them, it is time to reassess your lead generation program. Or as one of our clients put it, “stop buying leads until you figure it out.”

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That which is abundant has little value.

More or less, these are the lessons of life.

Sales organizations go through the CRM selection process with great diligence. They spend even more resources redesigning existing processes, integrating the technology and people, training and rolling out the shiny new thing with great fanfare. Making sure every sales person is empowered.

Yet adoption remains at an abysmal level by measures beyond logins, “clicking on plays” and “call blocks.” Why?

Here are three most cited reasons aggregated from numerous research:

It is not believed to generate ... Continue reading entire post on next page ... »]]>

That which is scarce is precious.

That which is abundant has little value.

More or less, these are the lessons of life.

Sales organizations go through the CRM selection process with great diligence. They spend even more resources redesigning existing processes, integrating the technology and people, training and rolling out the shiny new thing with great fanfare. Making sure every sales person is empowered.

Yet adoption remains at an abysmal level by measures beyond logins, “clicking on plays” and “call blocks.” Why?

Here are three most cited reasons aggregated from numerous research:

1. It is delivered primarily as a technical tool, relegating the human element.
2. It is perceived as management pushing something from above.
3. It is not believed to generate more value: sales, profits, targets.

In other words, it is not adding value to the life of the sales person.

One sales leader I know used to say, “if you don’t know the value of what you’re doing, then stop doing it. You will find out.” Yes, we are asking you to consider the opposite of what every expert says, everything you have heard, and even what we’ve said on these pages – stop doing SFA – if you are not sure of the value being delivered.

But wait, you say! How could we stop using SFA? Well, you start by MAKING IT SCARCE.

If you really believe you are adding value with your SFA, then start by giving it to less people. Select a team, or select reps via a lottery system. If not the entire SFA, then some components which are considered valuable should only go to a select few. Make it a privilege to get these components.

No pushing from the top management tier. If a few sales reps using the system see that their lives are better, they meet goals easier, it is intuitive to use, that data is accurate, analytics is meaningful and timely, and it flows well with their daily activities, then acceptance and adoption of the system will spread throughout the sales force.

Make the SFA about adding value, the people who are using it, and the results being delivered. And forget about adoption rates.

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In a repeat run rate business, customers are buying many categories of products and replenishing supplies and inventory on a weekly basis. With so many transactions from customer orders that reps must contend with, it is easy to forget about the customers who are NOT ordering, who are ordering less or not ordering the core high-value products any more.

While we are a predictive analytics company and have a solution to offer here, we also ... Continue reading entire post on next page ... »]]> In this post we look at solving the critical business problem of managing the customer buying cycle, and how tools — simple to advanced — can help sales people support their customers.

In a repeat run rate business, customers are buying many categories of products and replenishing supplies and inventory on a weekly basis. With so many transactions from customer orders that reps must contend with, it is easy to forget about the customers who are NOT ordering, who are ordering less or not ordering the core high-value products any more.

While we are a predictive analytics company and have a solution to offer here, we also explore with customers and prospects who are starting out this question: What is the right fit for their needs? Here are three options in the order of features, scale and cost, with pros and cons we’ve discussed with them:

SALES PROCESS SOFTWARE

Primarily focuses on mechanically guiding rep actions through a rules engine: “call today … email next week … follow-up in 3 days.” Stand-alone or blends with CRM.

Pros: Most simple/easy to follow, ideal for a small team within a larger sales force.

Cons: Does not consider customer attributes and responses or historical sales data, and is not predictive.

MARKETING AUTOMATION SOFTWARE 

Tracks frequency of contacts for communication, which is another way to stay on top of the buying cycle.

Pros: Maps to a pre-thought-out contact strategy, multi-channel, captures customer preferences and responses, and increasingly sophisticated. Ideal for 50-100 reps.

Cons: No historical sales data used, is not predictive, cannot blend external data, may not incorporate sales rep actions, does not identify cause and effect.

PREDICTIVE ANALYTICS SOFTWARE

This niche fits what we do. It is the most costly of the three because of data consolidation, involving expert statisticians with domain expertise, etc. But this process can scale indefinitely, it is predictive, and it can prove generation of incremental sales.

Pros: Support multiple sales channels, extensive data crunching, most accurate, provides cause/effect drivers. Ideal for 200+ reps, integrates with CRM seamlessly, best ROI.

Cons: Generally more expensive, more time to calibrate and start using, involves more people and technology (need expertise).

So there you have it. While we sell the hammers, aka predictive analytics software, we don’t see every problem as a nail that needs to be pounded. These tools all have a place in the sales arsenal, so take the time to determine what’s right for your organization.

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The central theme as we see it (of course being a SaaS company ourselves) is 1) the deployment of SFA on SaaS ... Continue reading entire post on next page ... »]]> It’s no secret that sales force automation (SFA) was dreaded not too long back, but has now become an indispensable friend to the sales person. There are many who may still be leery of it, but that number is certainly dwindling. Lauren Carlson’s blog at Software Advice reflects on this sales force automation evolution over the past 15 years, and identifies four factors that explain the change. While we agree with those, here’s our take on where this is headed.

The central theme as we see it (of course being a SaaS company ourselves) is 1) the deployment of SFA on SaaS platforms and 2) SFA is more inter-operable in a sales environment. And that is a great fit to how the best sales people think and act:  sales is seen in the larger context of client and business needs. So while software engineering has taken great leaps forward with usability, content and inter-operability, it has made it easier rather than harder for sales reps to use these tools. 

Let us now envision what the future holds in terms of increasing adoption and further making SFA an indispensable tool for the reps of today and tomorrow.

SIMPLIFY, SIMPLIFY, SIMPLIFY:

Thanks to Amazon, Google, Apple and iPhones, and other innovators, we now live in a world where our tools and devices instantly empower us with just a touch of a finger. There is no need to over-engineer features and functionality. So we will see SFA applications mimic more closely the way sales reps live and work, intuitively pulling things together for the right communication with customers that build credibility and trust.

BETTER INTEGRATION OF ANALYTICS AND DECISION SUPPORT:

Either through native interface, APIs or other methods, information will become more context-sensitive. In other words not “all the data all the time” – that’s like using a cannon to kill a mosquito! Predictive analytics is not used just to determine which customers to contact and what to sell etc., it will also determine when a particular insight or data point is valuable and present it to the sales rep at the right time. The integration of up-to-date sales intelligence tools is further validation of this trend.

GREATER RELIANCE ON SALES PROCESSES THAT PRODUCE RESULTS:

A proven process is a collection of technology, domain knowledge and best practices that are known to produce a better result. There is enough body of knowledge to show what practices work where and why. Sales organizations are already building on this. In addition, the availability of domain expertise and the relative ease of technology integration further drive the dependence on an established process. No SFA = no process.

With the advent of smart phones, tablets and social media we are now at a tipping point with respect to the next evolution of SFAs. It’s no longer a question of should sales team use sales force automation. Companies and sales organizations that do not embrace it and follow a solid process are at a disadvantage. That only portends more exciting times ahead for those that do.

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FUSION OF SFA WITH EMA = TRUE CRM:

With continuing innovation, sales force automation systems (SFA) have been transformed into a sales rep’s best friend, as discussed in an insightful blog post at Software Advice:  easier implementation, data accessibility and now the benefits of analytics and marketing automation are aiding the success of sales teams using these systems.

The success of CRM and Marketing Automation is no secret. More B2B organizations will take advantage of this profitable alliance ... Continue reading entire post on next page ... »]]> Our CRM trends to watch in 2011 were among the most-read words here, all year. Now let’s look forward to what’s in store for sales and marketing data in 2012 …

FUSION OF SFA WITH EMA = TRUE CRM:

With continuing innovation, sales force automation systems (SFA) have been transformed into a sales rep’s best friend, as discussed in an insightful blog post at Software Advice:  easier implementation, data accessibility and now the benefits of analytics and marketing automation are aiding the success of sales teams using these systems.

The success of CRM and Marketing Automation is no secret. More B2B organizations will take advantage of this profitable alliance to create a true lead generation life cycle platform, so that the handoffs throughout the prospect -> lead -> nurture -> sale pipeline will become more seamless and accountable. To accomplish this, data, analytics and best practices will play an integral part in relevant communication.

(Also see our slide presentation, “What CRM was supposed to be.”)

MORE PRODUCTIVE CUSTOMER RELATIONSHIPS:  

The customer value equation will go further so companies and sales teams can generate more revenue and profit from existing customers. This means examining every aspect of customer value, determining where it will come from and coaching/training to empower sales teams with the appropriate tools to realize such value.

CUSTOMER OWNERSHIP:

With relationships becoming increasingly more mobile and social (and perhaps personal too), there will be contention on who actually owns the customer:  is it the rep, the company or the data/app provider? We’ve already seen lawsuits on such components like blog subscriber lists, Facebook and Twitter connections etc. This is going to become more blurred with the continued growth of social media. One way companies can keep the upper hand is to establish a fair and transparent process.

EXTERNAL INTEGRATION OF CUSTOMER DATA:

Companies have been bringing data together for many years internally, but they only know about what customers do with them. Now via external providers like Facebook or aggregators, there is going to be great interest in knowing about a customer holistically, not just the two-way relationship that companies already know. Privacy considerations included, these will start becoming available on the market.

BIG DATA:

Data trends we discussed last year continue to play out, but one megawave arching over all is Big Data. At the moment, this trend feels more like a solution looking for a problem at the company level. Although age-old techniques like statistical sampling are more cost-efficient, with the need to analyze data across, within, and outside companies and the larger market, more valuable applications will come to market and help realize the benefit of a Big Data strategy.

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Airplane auto-pilots can handle many tasks for the pilot. They can:

But amazing as auto-pilots are, aviators are aware that the auto-pilot does not fly the plane for you. You are still always responsible for ... Continue reading entire post on next page ... »]]> For any airplane pilot, the auto-pilot is a valuable companion. It can automate routine tasks such as maintaining altitude and direction so you are free to focus on the next tasks needed to reach your goal destination.

Airplane auto-pilots can handle many tasks for the pilot. They can:

• Follow programmed climb and descent rates to pre-set altitudes
• Turn the plane to a specific direction
• Line up for landing on the runway
• Execute missed runway approach procedures, like climb away from the ground if the runway approach lights are not visible

But amazing as auto-pilots are, aviators are aware that the auto-pilot does not fly the plane for you. You are still always responsible for reaching the goal destination.

Business analytic tools – particularly those with predictive methods – can function a lot like an auto-pilot. They reduce workload, prioritize tasks and standardize best practices so you can focus on things the auto-pilot doesn’t do:  continuously improving human performance, anticipating hazards far in advance, and staying ahead of the navigation tasks.

Like auto-pilots, how can analytics contribute to sales enablement and productivity?

REDUCE WORKLOAD:

Pilots joke that flying is a long span of boredom followed by moments of panic. Perhaps like all the sales activity during the final days of the quarter? In flying, reducing mundane workload is a top concern and this makes a big difference in the most crucial aspects of flight such as preparing for landing. Sales teams could offload mundane workload to auto-pilots as well.

Here are some ways analytics can reduce workload so you can perform where it counts:

• Less time searching. Time spent searching is hard to document, but costly nonetheless. Smart Selling Tools suggests that only 218 days a year are “selling days” – that’s slightly more than six calendar months.
• Align customer-brand preference. Manufacturers and brands run promotions based on their needs – clearing inventory, launching new products or gaining competitive share. These initiatives are often brought to the attention of sales reps in an ad-hoc informal way. But by using analytics to identify customer brand and product preference, price sensitivity and other customer attributes, reps can take advantage of promotions opportunities and contact targeted customers who are most likely to respond.

PRIORITIZE TASKS:

We all prioritize tasks, either by design or default. In the high-stakes world of aviation, prioritization brings a whole new level of professionalism, airmanship and eventually, delivery of consistently successful outcomes. Because successful outcomes must be achieved. Doesn’t that sound like a sales wish list?

Here’s how prioritization via predictive analytics can help your sales teams:

• Prioritize based on predicted value. Sales reps must allocate time to customer conversation, learning, research and administrative work. Beyond applying good time management techniques, advanced analytics can further boost sales productivity. For example, there is significant value to developing a predicted value measure of customer interaction.
  • For example, predicted value could be the sum total of expected new orders, new product categories, and average order size of repeat orders. Based on this, the frequency and type of contact with the customer, level of effort/time, and type of offers could be varied to realize the value. Without this approach, sales reps are likely to focus on the trailing twelve month revenue which is a lagging rather than a leading indicator.
• Suggest a “best course” workflow. It is not realistic to expect reps to know preferences across all customers and circumstances.  But there are metrics that create a chain of sales activity – like a decision tree – that if optimally followed will result in a significantly higher customer value. How can reps achieve this?
  • Determining ideal “horizontal contact strategy” – in marketing parlance – is perfectly suited for predictive analytics. Rather than stop at one or two actions, this allows reps to see the relationship as a nurturing continuum. This workflow can then integrate with campaign management approaches so reps get additional support from marketing.

STANDARDIZE BEST PRACTICES:

No pilot will fly without a checklist. A checklist is neatly categorized with specific, sequential tasks to be done in a short amount of time, or a related set of maneuvers to do. For example, checklists include tasks for pre-flight, taxi, take-off, climbing and landing. The task instructions for each section are also specific to each type of aircraft, and they include manufacturer recommendations, learnings from experienced pilots, and recommendations from NTSB investigations – in other words, time-tested best practices.

Do checklists have a place in sales? Yes. You can use them to:

• Test and Learn. Like marketing will test customer contact points — such as catalog page layouts and e-commerce offers – establish sales rep dimensions to test.  These can be customer portfolio mix, product penetration, growth and customer loyalty. Test various combinations for sets of reps and determine the most profitable combination for customer, product and sales rep. These combinations become a checklist to follow.
• Build analytics that recognize rep attributes. Some reps get growth from a small set of customers, others do well in certain product categories, others do well with a certain size book of business. Through predictive analytics, you can avoid painting reps with a single broad brush that may be counterproductive, and instead craft individual performance levels that are driven by how similar reps have performed historically.

To be effective, sales teams can benefit from centralized formation, the ability to derive insights, and the fortitude to simplify actions. This provides a sense of urgency that can best be leveraged through both predictive analytics, and the integration of these solutions into the daily stream of the rep’s work.

Just as safety is paramount in aviation in all aspects of flight, efficiency is critical to sales. Analytics can deliver that efficiency as a true companion in all aspects of selling.

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What I liked about the story was just like predictive analytics, all the statistics focused on solving one problem, and that is getting the best trade-off against a precise outcome. In this case, get the most wins with the least money — aka, Return on Investment. It was the book I would give to our sales managers saying “Like sports? Like making money? Here’s ... Continue reading entire post on next page ... »]]> The movie Moneyball opens today to some great reviews such as this one at Sports Illustrated. I read the book by Michael Lewis soon after it was released and as a quant I found the story fascinating. What a great pair Billy Beane and Paul DePodesta were that came together at the right time!

What I liked about the story was just like predictive analytics, all the statistics focused on solving one problem, and that is getting the best trade-off against a precise outcome. In this case, get the most wins with the least money — aka, Return on Investment. It was the book I would give to our sales managers saying “Like sports? Like making money? Here’s a book for you!”

Here we’ll not review the book, the movie or Brad Pitt’s performance. Instead I’d like to share what we can learn about building a great sales team using analytics:

DEFINE THE RIGHT METRICS

It took a series of calculated steps to determine that wins were driven not by batting average but on-base and slugging percentage. How did they discover that? Set the outcome first and then run “simulations” of various predictors until one comes the closest. For sales managers, if exceeding quota is the desired outcome, then run several individual and combination factors of sales rep behavior until you find one that is the closest predictor.

DETERMINE THE RIGHT OUTCOME TO INFLUENCE

A baseball team can have many goals: attendance records, fan satisfaction, making the playoffs or winning the World Series. The Oakland A’s wanted to win the most games in regular season. Once this was fixed, then everything they did focused on achieving this outcome. In sales, it’s the equivalent of ALL reps making ALL their customers buy. Break such a massive goal down into smaller components, and focus on how to get the highest percentage of customers to buy/be active for each rep.

SET A PER-UNIT BASELINE

The Oakland A’s asked, “what’s the marginal payroll dollars to spend for each marginal victory?” Between 2000 and 2002, they paid $500,000 per win, compared to rich franchises like the Texas Rangers that paid $3,000,000 per win. Imagine that, what would such a differential do for your per-rep sales?  It can be achieved by a combination of rep, the customers they call on and the products they sell. In order to achieve similar success, the reps need to be aligned with customers who can relate to them, and be comfortable with selling the products each customer wants.

GET BETTER OVER TIME

While the Oakland A’s were already one of the most efficient franchises in cost-per-win at the early stages, they continued to get better each year.

INITIATE SOME EVOLUTIONARY REVOLUTION

Huh? Challenge status quo, but don’t go all out on a limb. By bringing science to a 150-year practice honed by the scouts, Billy Beane challenged them and eventually produced a game changer. In statistical parlance, “test and control” is the process by which a small sample is isolated to perform a test, and then compared to the ones where no change occurred. If sample results exceeded status quo, that was evidence that the test could be rolled out successfully. Build a culture of test and learn in your sales organization.

FOCUS ON JOINT TEAM OUTCOME

A baseball team needs to be consistent in all areas and address critical gaps. What a gripping episode when the A’s, desperately wanting to replace Giambi, get into a bidding war for Hatteberg so they play him in first base, just for his on-base performance! Can conventional thinking yield this decision? While caliber of an individual player is important, it should always be looked at in the context of what they would do in the presence of other factors, and how their contribution would boost the team performance.

A customer-facing team consists of inside reps, field sales, specialists, customer service agents and operational personnel. A good service rep cannot by themselves undo poor touch points delivered by other members of the team. Even among the sales reps, consider the strengths of each rep and deploy them where the team needs improvement or a certain performance needs to be met. For example, if a certain sales rep has strong knowledge and success in a particular product category, deploy that rep with a customer base where you need to achieve critical success in this category.

ANALYTICS CAN GIVE YOU AN UNFAIR ADVANTAGE

While all the traditional indicators are valuable and have a role in running your team, the lesson from Moneyball is that we must look beyond the obvious, to dig deeper into what most people can’t see. This requires specialized skills, tools and competencies, and it’s in your best interest to seek and find them. Also think how you can be most cost-effective in procuring these resources towards the desired effect. Do not hesitate to ask around and for example pick a sales manager who is most comfortable and interested in analytics as a leader to test various opportunities.

Believe that you can win over larger competitors with deep pockets by deploying a thoughtful and cohesive analytic approach. In the end, in Moneyball it mattered less how much money the Oakland A’s spent than how well they spent it. Similarly, it’s about the quality of one-on-one sales conversations, not the quantity of sales calls. 

Who would have thought analytics can be mainstream entertainment? I am going to the premier this evening – please try to catch the movie soon. I hope for the sake of our own Chicago Cubs, that Randy Bush is watching Moneyball at a theater near him.

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Retain focus on business objectives

The excitement of implementing a tool that solves basic operational problems is understandable. The front-end responsibility of reliability, inter-operability and security is clearly with IT. These challenges are significant.

But it is important to go beyond the technology’s bells and whistles. By establishing a vision for analytics – metrics, measurement methods, forward-looking indicators and performance management – and incorporating these in the design, the rationale for the CRM system and its ROI can be validated. Through predictive analytics, business processes can be mapped and modeled, and ... Continue reading entire post on next page ... »]]> Yesterday we posted the first tip of how to use predictive analytics to make your CRM system even more valuable. Today we share several more tips …

Retain focus on business objectives

The excitement of implementing a tool that solves basic operational problems is understandable. The front-end responsibility of reliability, inter-operability and security is clearly with IT. These challenges are significant.

But it is important to go beyond the technology’s bells and whistles. By establishing a vision for analytics – metrics, measurement methods, forward-looking indicators and performance management – and incorporating these in the design, the rationale for the CRM system and its ROI can be validated. Through predictive analytics, business processes can be mapped and modeled, and benchmarks created for delivering quantifiable goals to the enterprise via the CRM system.

For example, is the primary objective of your CRM to support lead generation, product penetration or customer retention?  Based on your needs, predictive analytics can help develop appropriate forward-looking indicators, expected results and diagnostics of the results at all levels of activity – customer, sales people, products and operational areas. This will allow ongoing correction and calibration of your activity within the CRM system that maintains the focus on the business outcomes, not just at preset review times or at the end of the year.

Implement analytics-based decision processes

Because initial concerns of getting the CRM system up and running usually consumes all priorities, many organizations do not plan enough for life after implementation. There are three specific areas where predictive analytics can help drive ongoing adoption and  value of the investment.  Design these components at implementation:

• Data integration:  To produce valuable predictive analytics, a significant volume of data regardless of source must be brought together, cleansed and summarized.  Design the system to provide succinct information at the rep’s fingertips, so they get big-picture visibility about customer trends.         
• Action recommendations:  Translate insights into specific steps within a decisioning process. This should start with the sales rep at the center, looking at the customer portfolio holistically. Set an amount of time to spend on each customer based on expected return for each customer interaction. These actions should be part of a deliberate, systematic, established process flow that sales and business leaders know will be acceptable to the users.
• Performance feedback:  Integral to the decisioning process is showing sales reps (the users) the results and consequences of their actions. No sales person likes leaving money on the table, we think. Feedback should show relative performance of the reps against a control group (also called “business as usual”), peer group and team. These results should be delivered timely – latent enough to be meaningful and short enough to correct developing trends. 

Predictive analytics can add significant value when you are considering, selecting and deploying CRM systems. Including your analytic needs up-front rather than as an afterthought can ensure that the CRM system supports your business objectives and outcomes. While the importance of technical requirements are the backbone of a great implementation, making business analytics a close partner can pay rich dividends.

When presenting our solutions to address issues like new customer growth or optimizing relationships, clients often ask, “but isn’t that what our CRM is supposed to do?” Yes, it can, but the intelligence to empower the CRM system can be driven by predictive analytics.

More about predictive analytics and CRM:

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A CRM system can be a boon to sales people. CRM helps overcome the technology hurdle of accessing information over disparate systems. CRM systems help improve collaboration within, above and across the entire organization, allowing the company to speak with one voice. And from a governance perspective, these systems help elevate the customer relationship from individual dependencies to an enterprise-wide strategic asset.

When you add the potency of predictive analytics, a CRM system can be even more valuable. Leaders in analytics, sales operations and technology can fulfill their obligation towards sales empowerment ... Continue reading entire post on next page ... »]]> Customer Relationship Management (CRM) systems are the currency of customer-sales interactions. Effective, simple CRM software helps sales reps to focus on content of conversations rather than the mechanics of conversations, resulting in sales empowerment and productivity gains.

A CRM system can be a boon to sales people. CRM helps overcome the technology hurdle of accessing information over disparate systems. CRM systems help improve collaboration within, above and across the entire organization, allowing the company to speak with one voice. And from a governance perspective, these systems help elevate the customer relationship from individual dependencies to an enterprise-wide strategic asset.

When you add the potency of predictive analytics, a CRM system can be even more valuable. Leaders in analytics, sales operations and technology can fulfill their obligation towards sales empowerment by creating a cohesive approach that brings these disciplines together.

How well we achieve this determines if a CRM system just gains basic acceptance, or whether it is fully adopted and even embraced by sales people who realize its benefits for themselves as well as for their customers.

Here are guidelines to help make that happen:

Consider a multi-stage deployment

In the first stage of CRM implementation, deliver base functionality to the users so that their immediate, tactical pain points are addressed. This often involves getting the system up and running and available without interruption – the kind of stuff that builds rapport with the sales team. It can include consolidating contact hierarchy and transaction history, integrating with hardware (i.e., computer, phones) and software (procurement, shipping), and even interacting with social media.

In subsequent deployment stages, add features – often not present in out-of-the-box CRM systems – that build credibility with sales, extend the functionality and improve the outcomes of customer interaction. This is where predictive analytics can lead the charge. In order to identify hidden opportunities and capitalize on customer interactions, predictive analytics requires three components:

• Synthesizing extensive amounts of data, including cleansing and reduction base on insights
• Applying data mining and robust statistical methods
• Integrating relevant and distilled intelligence back into CRM

These stages need not run in sequence. You can the basic team in place while initiating the gathering of data relevant for analytics. Then insights gained from analytics can help you prioritize implementation decisions.

Tomorrow, more guidelines to help you get the most out of your CRM system with predictive analytics …

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