{Demand Gen Brief}

Top Ten Demand Generation FAILS (Part 5) This Building has Structural Issues

noreply@blogger.com (Anonymous) — Thu, 30 Jul 2015 13:49:00 +0000

Have you ever been to the top of one of those Television towers or the Stratosphere in Las Vegas? These interesting structural designs seem to have a round building perched atop a very tall and very thin pole. What you can’t see is the very large concrete base buried below the surface, without which the entire structure would topple at the first puff of wind.

The same goes for a “structurally sound” Demand Center – much of the “structure” is invisible, below the surface, and absolutely necessary for proper function.

How sound is your demand center’s foundation? Since it is “invisible” how do you measure and keep track of its structural integrity? Let’s pretend for a moment that we’re engineers trying to determine the integrity of your foundation; how would we go about it?

As with any measurement, there are a few key characteristics we need to investigate. Let’s don our hard hats and dive in.

1. Is the original design sound? Seems like a pretty good question. Does the plan reflect good engineering practices? Does it accommodate the needs of the building’s users with the correct infrastructure (Mechanical, Electrical and Plumbing)? Do the specified structural components meet codes and standards?

These are all great parallels to your Demand Center structure. Is your Demand Center plan sound. (Do you even have a set of “blueprints” for your Demand Center infrastructure?) Does the infrastructure suit the needs of your internal clients in terms of its ability to support all of the various Campaign elements necessary for your marketing programs? Do the individual components, such as email engine, website integration, CRM integration and database meet up to industry best practices?

2. Did the plan accurately consider the building site environment? Were climate, severe weather, seismic and geologic conditions adequately accounted for in the design? How were each of these conditions determined and documented?

To properly design a Demand Center infrastructure, you need to adequately assess your Center’s environment. This requires a thorough Business Process Review (BPR) to determine that actual business requirements you plan to meet. These are your climate histories and soil samples, upon which you can base good infrastructure design. Do you have a set of documented (and agreed upon by the business stakeholders) business processes and associated goals by which your success will be measured?

3. Is the structure built according to plan? You might have designed a great building, but is it actually built according to those plans? Are the building components exactly as specified in the plan or were there substitutions? Are the as-built measurements precisely as specified in the plan?

When assessing Demand Center structures, the answer 99 times out of 100 is a resounding NO. The correct skill sets for specific roles could not be hired and there isn’t time or budget to properly train them. Specific software or plugins to maintain data hygiene are in next year’s budget. Platforms won’t support needed process or functions. Integrations between critical systems can’t happen because of lack of internal skills or budget to hire external vendors. Once very important caveat to note here: if you don’t begin with a detailed Demand Center blueprint, you cannot claim the infrastructure isn’t built according to plan. You’ve heard it a million times, but failing to plan is planning to fail.

4. Have environmental factors changed since the building was built? Has increased local development altered the surrounding micro-climate? Have repeated severe weather events altered soil conditions or associated codes?

Has your operational environment changed since you implemented your Demand Center? Mergers, acquisitions and reorganizations will all have an effect on how you operate. Personnel changes in key positions can affect your operations, changing SLAs or quantity expectations. In general, how has the landscape changed since you originally designed your Demand Center?

5. Have use factors changed since the original design was created? Has increased use of electronic devices changed the average power consumption per occupant? Does the building structure cause problems with the increased use of wireless devices? Has modern interior office design affected occupant density, affecting dynamic and static structural loads?

Interesting how these very same factors can and should be affecting the way your Demand Center operates. Does your Demand Center design accommodate the increased use of wireless devices, both internally and externally? How does this affect your QA processes? Can you adapt to the ever-changing technology landscape to include multi-screen, location-based advertising and the Internet of Everything?

What’s your plan? Do you have a set of blueprints that adequately document this plan in sufficient detail to build it? There is zero chance that your business environment is going to remain static for the next two, three or five years, so you need to prepare to “remodel” in the future. In order to remodel, you need to have an accurately documented plan to form the basis for that remodel. Design. Document. Build. In that order. Failure to follow that simple, prescriptive process leads to Demand Gen FAIL number 5.

Notes:

Your Demand Center infrastructure is like a building, requiring the necessary design diligence and documentation (blueprint) to build, maintain and remodel it in the future.

When troubleshooting, it is impossible to determine where a system is not working properly without a design document against which you can compare the operating process. This wastes valuable time at (almost always) a critical time in the production process.

In next week’s edition, we will look at Demand Generation FAIL number 6: Lumpy Pancake Batter. Because we all love inconsistency (not).

Create Marketing Reports That Will Thrill Your CEO

noreply@blogger.com (Anonymous) — Thu, 20 Nov 2014 18:35:00 +0000

Yes, you read that headline correctly. Thrill your CEO. In order to meet that expectation, you will first have to understand what kinds of things get your C-Suite excited. Those are called executive strategic drivers. Some examples of those drivers are Growth Strategy, Competitive Pressures, Regulatory Changes, Risk Management, Shareholder Value, Profitability and Technological Market Disruptions.

Let’s look at what was not in that list of strategic drivers. Unaided Brand Awareness, Total Impressions, Number of Leads, Funnel Metrics… that tactical list of things you are probably reporting on right now. I am not at all saying your current reports are not important. In fact, they are critical to building and maintaining a revenue pipeline. They just don’t address strategic challenges from an executive perspective. And you can change that!

Putting Some Perspective on Reporting

If we simply change perspective from Demand Gen Success to Organizational Success, it is very straightforward to realign your reporting. We’ve already established that tying your Demand Gen metrics to revenue is critical to determining success. That never goes away. You are in a business and that business has a key objective (if not the key objective) of generating revenue, which provides livelihoods for employees and products and services for customers. Your executives are charged with not only keeping, but building that revenue stream and the profits it generates. Your owners (or shareholders) want to see a positive return on their investment and your company is but one of a myriad of investment options. How does Demand Gen contribute to success from that perspective? Let’s just look at Demand Gen performance from the perspective of three of the executive drivers:

Growth Strategy
Profitability
Risk Management

Growth Strategy

First, let’s look at the strategy options for growth, which fall into three broad categories: organic growth, partnerships and acquisition. Demand Gen falls into the organic growth category, which means growing the organization by driving increased revenue. This is pretty straightforward, as demand gen is the primary driver of revenue growth. We don’t need to spend a lot of time expounding on the advantages of revenue growth, but we’ll come back to this issue.

Your reporting should reflect both retrospective performance and predictive future performance (for internal consumption only, of course). Your executives want to know how well you performed, but also what to expect in the future. The entire purpose of building a demand gen machine (we’ve often called it a “Marketing Factory”) is to drive efficient, predictable and scalable revenue generation. That includes growth. And growth thrills your CEO.

Profitability

Part of the equation for effective demand generation is how efficiently you can do it. Looking at this graph, we want the best possible combination of demand and the cost required to obtain those results, creating an Effective and Efficient demand gen machine.

As the graph indicates, you can spend more to generate more leads, or you can spend less and generate fewer leads, but neither is an ideal state. You are seeking the best combination of generating demand and reducing the cost of acquiring leads, thereby reducing overall customer acquisition costs.

Creating reports that show your trend over time – and the resultant reduction in cost for acquiring more leads for less cost per lead indicates increased profits. Profit thrills your CEO.

Risk Management

Since we’ve pared down our set of executive drivers, let’s now look at the associated risks. At the highest level, your CEO must balance the risks associated with growth: grow too fast and it is difficult to maintain the organizational infrastructure required to manage the additional business. How will manufacturing produce enough product to satisfy demand? How will the additional burden on staff affect customer satisfaction? Can our supply chain keep up with demand? Can we deliver the additional product through our distribution channels?

On the other hand, if growth is too slow the organization may be too big to maintain its margins and keep up with competition. Will we need to downsize the organization to keep costs in line with revenue? How will the market react to slow growth and potential layoffs? What will we need to do to correct the revenue outlook?

From the profitability standpoint, many of these same questions apply, with some additional flavor. Where can we cut costs with the least impact on product quality and delivery? Where can we consolidate functions or increase efficiencies? Where can we benefit from economies of scale?

To manage risk in each of these categories, your CEO really needs to see the roadmap because changing course before something bad happens is always preferable to changing course afterwards. Fortunately, you are on a course to build a predictable and scalable Demand Gen machine that will help your CEO chart the correct course. By providing your executives with a predictable course, you are helping them avoid risks associated with proceeding blindly on a course into the future. Your predictability reduces risk. Reduced risk thrills your CEO.

Change the conversation.

Your reporting needs to combine retrospective performance with a predictable performance forecast. Looking backwards and projecting forward provides your executives with the information needed to make smart course corrections. Your CEO wants to ramp production, supply chain and distribution that same 15% you have predicted an increase in demand. With that understanding, your reporting becomes a critical information source for business decisions with weighty consequences. Reporting with that perspective makes your Demand Gen team an extremely important part of your organizational success. And you CEO will be thrilled!

Notes:

Align your reports with executive strategic drivers.

Don’t just look backwards, look forward.

Be Predictable.

Thank You!

I want to thank the thousands of demand gen professionals who have spent the past 40 weeks on this journey with me. I am often surprised at what Google tells me about the number of readers of this humble blog post. We’ve traveled together down a long road to learn about building, organizing and managing our Demand Gen teams and I hope you’ve learned something that will make you a better marketer.

What’s next?

I’m going to take some time off from posting through the holiday season and the remainder of the year to regroup and refuel. I will be taking the fundamental ideas from this post and organize and compile them into an e-book that I will publish early next year. I hope you will be as excited to read it as I am to publish it. I’ll also be looking for new and exciting topics to cover in next year’s blog posts. In the meantime, I wish you much success and ever-increasing demand!

Deodorant Goes Viral! Test Intelligently.

noreply@blogger.com (Anonymous) — Wed, 12 Nov 2014 13:56:00 +0000

In my last post, we took a look at a framework for optimization that creates results that will inform future programs and tactics. Using Scientific method, we created control and test groups to prove out our hypotheses. We also looked at ways to increase our testing flexibility using test matrices allowing us to test multiple factors simultaneously to get the best combination of variables. Now let’s look at a real-world example that might challenge our assumptions.

Deodorant goes Viral!
Let’s say our good friends at Acme, a Consume Packaged Goods company, is releasing a new mens' deodorant brand. The marketing brain trust has spent plenty of time, resources and money testing and validating the brand positioning and customer value proposition. Acme has settled in on a particular brand voice that is best presented in a humorous light.

Testing on several control groups have settled on a particular series of video clips that have shown the potential to “go viral” and spread the new brand’s message over the Internet for very little money. The demand gen team packages and presents the idea to brand leadership and everyone agrees the videos are engaging and hilarious and will definitely spread like wildfire over the Internet, so the project gets the green light. Time to light ‘em up! The Demand Gen team posts the videos on You Tube and eagerly waits for the results.

Within hours the video does, indeed, go viral as expected. Views are in the millions, and rapidly increasing. Within days the videos are at the very top of the view lists and are making the rounds via Social Media channels. All is good, right?

And now, a word from our sponsor…

Expectations are high, but word from the distribution team is the product is staying on the shelves in droves. Expected backfill orders are non-existent. The videos are obviously a smash hit, spreading the new brand across the Internet at record speed. Why no product sales as a result? Quick, somebody check their Twitter account to see what’s going on!

Houston, we have a problem. While everyone seems to absolutely love the humor in the video, the reaction is not exactly what product planners have in mind.

#worldsdumbestdeodorant

#dumberthandirtdeodorant

#lmaodumbdeodorant

#smellslikestupiddeodorant

#canyousmellthatgoodandbethatstupid

Yes, the videos are hilarious, but nobody wants to be associated with a product whose promotional videos depict its users as complete idiots. And it’s too late for those tens of millions of viewers to “un-see” those videos.

What should Acme have done?

This is a clear example of where spending a little time and money on a limited pilot could have saved a lot of embarrassment later. Executing tests in a controlled environment with limited, but representative audiences can provide insight into those unintended consequences. These pilots should concentrate on understanding not only what will happen, but why it happens.

Change the conversation.

Your pilot should be conducted with the end objective in mind. These pilots are good at bridging assumptions you may have made in causal relationships. In this case, ACME assumed that millions of Internet views would cause millions of product sales. Instead, those views led to brand ridicule and corporate embarrassment.

Pilots can also be used to test specific audience segment reactions against the whole. It is a great way to determine how message/offer variants track in one segment vs. another. Do customized messages really improve responses? Better to pilot and know than spend additional time and money only to find out after the fact you generated no additional lift for your efforts.

Notes:

Pilot before committing to an untested plan.

Pilot with the end objective in mind.

Pilot to correct causal assumptions.

We’re now piloting testing and optimizing every bit of success out of every program we execute. It’s time to tell your C-Suite about the fantastic work you are doing. Unfortunately, Marketing historically has done a less-than-stellar job of reporting on its success. In our next installment, we’re going to begin a series on reporting to overcome that legacy: Create Marketing Reports That Will Thrill Your C-Suite!

Three Ways to Use your Demand Funnel Part 3. Optimize Your Lead Processes.

noreply@blogger.com (Anonymous) — Tue, 04 Nov 2014 16:35:00 +0000

We just explored way to properly use your Demand Funnel to diagnose and fix problems with your Lead processes. Using this diagnose-and-fix methodology, you should be able to get leads moving and plug and any leaks in your process. This should create a positive lead flow with negligible leakage or stuck leads and an “always-on” diagnostic to keep you from developing more problems. So you’re good, right? Not so fast! You now need to use the Demand Funnel infrastructure you’ve created to optimize your process. Here’s how.

Understanding Optimization
Optimizations makes some assumptions, so let’s make sure we have properly aligned on those.

1. Optimization assumes your process works. If your process is broken, optimization will not help. It may make matters worse.

2. Optimization should be built in to your Lead Management process. It is not an optional thing you do every once in a while for specific processes or parts of your process. To be really successful, optimization needs to become a part of your Demand Gen culture – something that is an expected part of the way everyone does their jobs.

3. Optimization requires a framework and methodology. You cannot optimize against a moving target.

We have already covered many ways to perfect your process, so we’ll spend little time here addressing that subject. At this point we need to assume your processes are defined and properly implemented.

Building Optimization into your process

If we think of Demand Generation as a series of actions taken to achieve success against a given strategy, we would normally execute these actions with a plan (as opposed to random acts of marketing). Organizations manage those projects in a variety of ways with a variety of tools – most often referred to as project management. The three pillars of project management are: 1) Scope, 2) Resources and 3) Time. To build optimization into your project plan, you are likely affecting all three of those pillars, with scope being the key. Let’s look at a simplified example.

For every Demand Generation project, no matter which tactics or media are used, major project categories remain relatively constant. Starting with the idea that we would like to do X by Y date, you may see a project plan similar to this:

1. Initiation and Planning: What do we want to do? Who is our target audience? What defines success in Demand Funnel terms? How will we measure it?

2. Discovery: What are the requirements, resources and constraints to doing it?

3. Ideation: Based on our discovery, how should we do it?

4. Design: Based on ideation results, what do the deliverables look like?

5. Development: Based on approved design concepts, build the deliverables.

6. Testing: Based on the design requirements, make sure the deliverables meet requirements.

7. Deployment: Execute the delivery of tactics to the target audience.

8. Reporting: How did we do against our plan?

As a Demand Gen professional, you probably recognize project plans that look similar to this. Within each of these major categories will be many sub-categories, each dependent on the scope, time and resource availability. Of course, your organization will have its unique twist to this structure.

What’s missing? Optimization. Where should optimization fit in this plan? Let’s take a look at a revised project plan including optimization.

1. Initiation and Planning: What do we want to do? Who is our target audience? What defines success in Demand Funnel terms? How will we measure it? How will we optimize it?

2. Discovery: What are the requirements, resources and constraints to doing it?

3. Ideation: Based on our discovery, how should we do it? What should be optimized?

4. Design: Based on ideation results, what do the deliverables look like? What components of the deliverables should be optimized and compared to other similar programs.

5. Development: Based on approved design concepts, build the deliverables. Build the optimization components.

6. Testing: Based on the design requirements, make sure the deliverables meet requirements. Make sure the optimization components and tests work per specifications.

7. Deployment: Execute the delivery of tactics to the target audience. Implement the testing components.

8. Optimization: Evaluate test components on the prescribed cycle. Report and record results within the framework. Deploy winning components.

9. Reporting: How did we do against our plan?

Notice we only added one major step to the plan, but optimization has become completely integrated into the planning, design and execution of the overall plan.

Optimization Framework

Optimization on a particular program is great. Great for that particular program. But how do we scale optimization so we can leverage optimization learnings across Demand Gen programs for the entire organization? For that, we need a framework.

A framework is simply a method by which we can organize and execute our testing and optimization such that results can be compared to other, similar tests. Think back to high school science classes where you learned the Scientific Method. Your testing framework should emulate this methodology to maximize your results and create the ability to measure them across multiple programs of similar – and, in some cases, dissimilar – types of programs. To get to an operational framework, let’s start with objectives and work backwards.

Objective: Create 1,000 MQLs in Q1

Let’s break this down. (Although your number is different, this is probably a very common objective for Demand gen teams, so it will be easy to relate.) We have two real options here. The first is to create MQLs from your unknown TAM – those contacts outside your database, but fit your target market. The second is to convert current Inquiries (those contacts already in your database who have previously interacted with your brand) to MQLs. This sounds like the basis for an optimization test, so what would we want to understand from this program test?

1. Total Volume of conversions: did more Inquiries or Unknowns convert?

2. Speed of conversions: Which converted faster – Inquiries or Unknowns?

3. Cost of conversions: Which converted at a lower cost - Inquiries or Unknowns?

As a result of this optimization framework, we would begin to understand how best to apply our marketing resources to the challenge of creating MQLs. However, we need to dig deeper into optimization because we need to understand why these conversions happen. Without that understanding, we could wind up applying the wrong tactics for the wrong reasons. This is where our use of Scientific Method gains us an advantage in optimization.

We start with a hypothesis and devise a method to test that hypothesis against a baseline. Let’s say our proposed program is designed to execute a very typical multi-touch mix of tactics, including an email and a direct mail message. We have looked at the previous arguments and decided to address current Inquiries in our database as our target audience, with the objective of creating our 1,000 MQLs. It have been determined that conversions (via form submit) from this program will generate sufficient scoring points to “auto-MQL” any Contact already in Inquiry status. Let’s also assume our benchmark conversion rate is 5%, so we require a total audience of 20,000 Inquiries for this program. Our optimization objective is to convert at least 6%, beating our benchmark rate by 20%. How, then should we design our optimization tests?

Let’s start with our hypothesis. We believe offer messages work better than product messages because our product is well-known and comparable to other products in the industry. Price drives conversions.

The conversion points for this program are:

Data and list hygiene, along with good emailing practices, are the keys to deliverability. We don’t test for that at a program level, so let’s assume static deliverability for this program.

Open rates are a direct result of the combination of sender and subject lines (for email) or packaging for direct mail. We’re going to test two specific messages:

1. Better Widgets, Better Price

2. 20% off Widgets until Friday.

Once the email or direct mail is opened, we need to get the recipient to read far enough into our message to respond to our call to action (CTA). We’ve already established that our products are well known, so we don’t need a lot of description, other than why the reader should respond now. Here, we are going to test two messages and two CTAs in a multivariate matrix to understand what combination provides the best results. This test covers both the Read and Respond steps in our conversion path.

Message

1. Our great widgets do more for you.

2. Our great widgets are on sale.

CTA

A. Better Widgets, Better Price.

B. 20% Off this week only

The matrix is very simple, covers every possible combination, and looks like this:

1A 2A

1B 2B

Conversion happens once the recipient has responded, and is the final measure of how committed the recipient is to your message and offer. Whether the response is to purchase or to engage more deeply with your brand, this commitment is the critical step. Do not assume that once your recipient has clicked the CTA, he or she will go ahead and execute the conversion. Abandonment here indicates you have not solidified your “closing message.” Let’s try something to test that commitment here – I call it the bonus close.

For three of the four message/offer combinations, a sale price is expected. Only one expects just a “better” price. Let’s align each of the four combinations with a bonus close test.

· 1A expects only a better price. Bonus Offer = 20% off through Friday

· 1B expects 20% off this week only. Bonus Offer = 22% off if you order by Wednesday

· 2A expects an unidentified sale price. Bonus Offer = 20% off through Friday

· 2B expects 20% off this week only. No Bonus Offer = 20% off through Friday

These tests will help us understand the best mix of offers and bonus offers as they meet or exceed expectation when the recipient hits the conversion form.

Change the conversation.

Optimization is a conversation that needs to be a part of every program execution. As you have seen here, it is a lot more than a few random tests thrown into the mix to get a few extra conversions; it is an entirely new way of thinking about what drives those conversions. The conversation should not be if we test, it should be how we test. Smarter tests lead to smarter programs.

Notes:

Test against solid hypotheses to provide scalable optimization.

Optimization is a culture, not an action.

Test every conversion step in your program process.

Are you all in on optimization? I hope you are. One last thing to consider: what if one of your tests goes wildly wrong? (This is not a bad thing – it is why we test!) Is there a way to mitigate risk and not put your Demand Funnel in jeopardy? Excellent question, and we’ll look at ways to do that next week in: Deodorant Goes Viral! Test intelligently.

Three Ways to Use your Demand Funnel Part 2. Get your Leads Moving Again.

noreply@blogger.com (Anonymous) — Tue, 28 Oct 2014 12:21:00 +0000

It is great to have an accurate diagnostic tool that will effectively tell you what is wrong with your Demand Gen programs. However, diagnosis is not very helpful if you do not have a treatment plan to solve the problem. The good news is, no matter the diagnosis, your Demand Gen problem has a cure! Matching the fix to the problem is usually not at all difficult. Let’s look at the proper approach.

Get Started
First, let’s recall the three things you can affect relating to total Demand:

The number of Contacts in each stage (the sum of those representing the entire Funnel).
The conversion rates from stage to stage.
Time in stage, which reveals the Funnel velocity.

Understanding these metrics also provides us with the diagnostics necessary to understand our funnel problems and remedy those problems. We’ll look at three common problems and the remedies you can apply to each. Before we address those remedies, let’s recall a few principles of our demand funnel, so we can properly diagnose the problem and apply the remedy.

The funnel should always be shaped like a funnel. That means early funnel stages should always contain more Contacts then later funnel stages. Although the exact numbers will vary from organization to organization, the general shape should be constant.
Conversion rates should get higher as the Contact gets lower in the Demand Funnel. This should be universally true, since Contacts only progress as they become more and more likely to purchase. It would be highly unusual to find a higher conversion rate for MQLs than SQLs, for example.
Time in stage will vary from organization to organization, with one exception. MQL-to-SAL should never take very long. In general, an MQL sitting in stage awaiting acceptance by Sales should not last more than 7 days. Otherwise the buyer’s interest level could wane and he or she moves on or forgets about the interest. We will look at this in our cases below.

Case 1: Stuck Inquiries

This case often happens when organizations do not have a content strategy. Without that strategy, communication is often also stuck in first gear, with messaging focused on attracting net new contacts into the funnel, rather than converting those already in the funnel. This is remedied with a comprehensive contact strategy that targets specific messaging to Contacts at every stage in the funnel, rather than sending the same message to everyone every time. Conversions from inquiry to MQL are all about offering additional information about reasons to move now.

Case 2: Stuck MQLs

This should be the simplest case to solve. If your organization has proper agreement between Sales and Marketing on the attributes of a “qualified” lead and the SLAs for Sales acceptance, nothing should ever get stuck in MQL state. If MQLs are getting stuck, it is most likely a process issue in which the responsibility for sales acceptance is not properly understood. Training and close management of the process will remedy this situation.

The second possibility is a technical process malfunction. Lead routing (usually performed on the CRM side) may not be actually sending MQLs to the proper queue or individuals. This is usually easy to diagnose by the complaints coming from the Lead recipients who are not getting the expected MQLs in their queues. Fixes usually need to be made in the Lead Assignment rules or MAP-CRM integration.

Case 3: Stuck SQLs

SQLs should never be technically “stuck.” If your product or service requires a long sales cycle, consideration for the length of cycle should already be in place. However, when leads do get stuck, in nearly all cases it can be tracked back to lack of discipline in dispositioning lead or opportunity status (see this {Demand Gen Brief} article: Four Ways You Are Marketing Backwards). Dispositioning leads in SQL stage is critical to the health of your demand funnel.

Change the conversation.

When Sales wants more leads, the conversation almost always ends up addressing adding new leads to the top of the funnel. Rarely does an organization take the time to examine what is going on mid-funnel and address concerns there, even though this will almost always provide a faster, cheaper and higher quality lift in lead flow. Although we’ve addressed some common fixes there, there are always considerations unique to your organization’s process and lead flow. Take the time to examine what is happening mid-funnel before rushing to add more leads to the top, which may only compound your problems.

Notes:

Your Demand Funnel is your chief diagnostic tool for Demand Generation.

Diagnose first, and only then apply the solution to the trouble spot.

Mid-funnel fixes are often faster, cheaper and of higher quality than top-of-funnel.

Now we’ve learned how to use our Demand Funnel as a diagnostic tool and how to apply remedies to the problems we’ve found. These are critical steps to maintaining the health of your Demand Funnel. However, we don’t want to just maintain our Demand Funnel, we want to improve it! Next week we will look at ways to improve our overall Demand Funnel performance in: Three Ways to Use Your Demand Funnel, Part 3. Optimize Your Lead Process!

Three Ways to Use your Demand Funnel, Part 1. It’s an Always-on MRI to diagnose Marketing Effectiveness.

noreply@blogger.com (Anonymous) — Mon, 20 Oct 2014 13:00:00 +0000

Back to a medical analogy, wouldn’t it be great if you had tools like your doctors have? Tools that could magically see inside your Marketing “body” and allow you to instantly diagnose problems. Not enough MQLs? Instant diagnosis. Conversion problems? There’s a cure for that.

The truth is - you do have an “MRI” for your Marketing troubles. It’s called a Demand Funnel. If you are using it properly, you have all the diagnostic tools you need to completely understand what is and what isn’t working properly in your Lead process!

Get Started
Interestingly enough, most organizations have some semblance of a Demand Funnel in place, but many are only used as reporting tools and some are not used at all. Step number one is to understand exactly what your Demand Funnel is telling you. When using an MRI machine as a diagnostic tool, if the doctor has no idea what to look for in the imagery created by the machine, it is useless. Your Demand Funnel works the same way. If you, the Demand Gen expert, don’t know what to look for, it is not effective as a diagnostic tool. Let’s make sure we understand what we’re looking for in your Demand Funnel diagnosis.

Basic Demand Funnel Metrics

In your Demand Funnel, you are measuring the three things you can affect that relate to total Demand:

The number of Contacts in each stage, and the sum of those representing the entire Funnel.
Conversion rates from stage to stage.
Time in stage, which reveals Funnel velocity.

Before we move to diagnostic details, here are a few things to consider. You may not have complete or reliable data past MQL. (For more information, see this {Demand Gen Brief} post.) This is OK, because you can perform a diagnosis on the data you do have. If your MAP is not automated to the point of updating Funnel stages in a timely fashion, you probably need to build (or have built) a program to match your funnel stages, definitions and attributes of Contacts in stage. Otherwise, you will not be working with up-to-date data.

Reading your Demand Funnel MRI

We just determined the three things you can affect relating to total Demand, so now you need to determine the metrics that tell us how well your Demand Gen team is doing. First is to determine the volume of Contacts in each Funnel stage. While your Demand Funnel will be different, it should look something like this:

Prospect 191,302

Inquiry 22,956

MQL 11,019

SAL 10,138

SQL 2,433

Secondarily, we need to determine the conversion rates from stage to stage and, in turn the composite conversion rate for the entire funnel. Based on this example:

Prospect – Inquiry: 12%

Inquiry – MQL: 48%

MQL – SAL: 92%

SAL – SQL: 24%

Prospect – SQL: 01.27%

Finally, we need two additional data points to determine stage velocity throughout the funnel: stage date (a date/time stamp applied when the Contact reaches any given stage) and time in stage (a calculation based on the stage date for the next stage in the series minus the stage date for the calculated stage). We want to understand this number because total demand is a function of both how many contacts in the funnel convert and how quickly they convert. Think of velocity this way: with the identical conversion rates, if you can cut the time in stage across the entire funnel in half, you can create twice the SQLs at any given point in time. Like conversion rates, time in stage adds up to a composite across the entire funnel. Based on this example:

Prospect 8 days (Inquiry Stage Date 10/18/2014 – Prospect Stage Date 10/10/2014)

Inquiry 18 days (MQL Stage Date 11/05/2014 – Inquiry Stage Date 10/18/2014)

MQL 22 days (SAL Stage Date 11/27/2014 – MQL Stage Date 11/05/2014)

SAL 2 days (SQL Stage Date 11/29/2014 – SAL Stage Date 11/27/2014)

SQL 15 days (Closed Stage Date 12/14/2014 – SQL Stage Date 11/29/2014)

Composite 65 days

Your next step is to begin documenting the Demand Funnel baselines for each of these metrics on a periodic basis. Start documenting on at least a monthly cadence, with the intention to move to a weekly cadence. The objective is to determine if your metrics are moving in the right direction. Your conversion rates need to go up and your time in stage needs to go down. Volume then becomes a calculation based on how many MQLs or SQLs your sales team needs.

Change the conversation.

Your MRI training is now complete. You know how to read it and diagnose your Demand Funnel problems. Conversations that used to revolve around how many contacts need to be added to the top of the funnel can now be fine-tuned to talk about conversion rates and velocity. Remember, the ultimate goal is closed business (Closed/Won Stage) and the conversation needs to be about how to get there as quickly as possible, rather than how many nebulously-defined “leads” can you generate. You have a powerful diagnostic tool. Use it to your advantage!

Notes:

Your Demand Funnel is your chief diagnostic tool for Demand Generation.

Using the tool to determine specific problems will lead to specific, focused solutions.

Remember, the issue is closed business, not the number of undefined “leads” in the funnel...

You will also be able to understand where Contacts are “stuck” in the funnel and apply tactics designed to move them to the next stage. That is where we will pick up next week – using your Demand Funnel diagnostics to determine where to apply specific tactics to solve specific problems in: Three Ways to Use Your Demand Funnel, Part 2. Getting Leads Moving.

Four Ways You Are Marketing Backwards. When was the last time you asked Sales to properly disposition their MQLs?

noreply@blogger.com (Anonymous) — Mon, 13 Oct 2014 14:19:00 +0000

There is another recurring phenomenon I’ve seen in one hundred percent of the Marketing and Sales organizations with whom I have consulted. Literally - every single one of them. This phenomenon has a name and, even though it is not published or circulated in any formal way. But every time I see the phenomenon in an organization, I can invoke this name and marketers everywhere immediately understand it. It is “The Black Hole.”

The Black Hole
Of course, this Black Hole has no cosmic origin, but it does seem to have cosmic relevance – at least in terms of Demand Generation. To understand the significance of The Black Hole, we need to first revisit typical Demand Funnel operation and its implications in Closed-loop Reporting. If we go back to our previous discussion about building a Lead Management process, we’ll recall that there need to be specific stages through which a buyer – or Lead for our purposes – must travel to become a customer. Each of these stages have definitions, actions in stage and triggers to move them either forward to backwards in the process.

In a typical Demand Funnel, there is a specific handoff between Marketing and Sales between the MQL (Marketing Qualified Lead) to SAL (Sales Accepted Lead) stages. At this point, Marketing (typically via the MAP, or Marketing Automation Platform) no longer initiates changes to the Demand Funnel stages. Sales (typically via the CRM, or Customer Relationship Management system) initiates changes to the Demand Funnel as a result of conversations with the prospect. These updates are called dispositions. For example, when a Sales Rep has a conversation with a prospect and discovers specific BANT qualifications have been met, she might need to open an Opportunity and trigger Demand Funnel movement from SAL to SQL. This is a typical type of Demand funnel disposition.

This is also where we discover the Black Hole! Most Demand Gen organizations have little to no insight into what happens to a Lead once it exits the MQL stage and is being dispositioned by Sales. Once these Leads exit Marketing’s jurisdiction, they fall into The Black Hole, never to be seen or heard from again. Why is this a problem? It makes closed-loop reporting impossible, since Marketing has no idea how or when Leads move through the Funnel to finally close – either won, lost or other (usually a class of leads that don’t buy at all – either from you or your competitors). Critical data is lost, and Marketing cannot, with any reliability, attribute revenue to its Marketing activities.

Why Sales should care

We’re going to start this discussion with a key topic we’ve discussed earlier: creating a solid MQL-to-SLA agreement on the definition and SLA. Further discussion on this topic with Sales is impossible without this agreement, so make sure you have it in place. Often, when we get to this question – why should Sales care? – we get a number of responses, such as:

· We consistently close our quota, so why should we have to enter a bunch of stuff that is only relevant to Marketing?

· This stuff is irrelevant to my job and takes too much time I could be using to talk to prospects and sell more.

· I already fill out my weekly prospecting report for my Sales Manager and this is a duplication of effort – I shouldn’t have to do this twice.

These are all powerful arguments, so how does Marketing respond to these objections?

1. First, understand this is a team effort. It is not “us vs. them” and if you treat it that way, it will become that much harder to gain consensus on the right way to disposition Leads so everyone benefits. Approach the subject as a collaborative effort to improve the entire organization’s results.

2. High performers consistently meet and exceed quota, and often are accorded a lot of credibility when it comes to sales process to close business. Let’s face it, what Sales Manager would not want to have everyone emulate their top performers? What’s relevant here is that these dispositions are not only relevant to Marketing, they are highly relevant to Sales! The more the Marketing team can understand about how Leads process through the system, the Marketing will get at identifying and qualifying better prospects to send to the Sales team. Do top performers want to spend less time with poorly matched prospects and more time with those prospects who fit the ideal buyer profile? If we want to stop wasting time, let’s stop wasting it talking to prospects who are unlikely to buy in the first place!

3. Why are Sales managers asking their reps to manually fill out additional reporting when everything they need to know should be dispositioned in the CRM system? If the CRM system is not set up with the correct hierarchies allowing managers full visibility into the activities and results of their teams, the organization has an infrastructure issue that needs to be resolved. Every leading CRM system has a way for managers at any level to see the current state of their entire team’s pipeline in real time or near real time. The rep is correct – she should never have to enter the same information twice.

There is one final argument we often hear, but should be moot if you have begun with that strong MQL-to-SAL agreement. That argument is that Marketing only sends over junk leads. If Sales and Marketing leadership have aligned and agreed on the definition of an MQL, this argument is actually one against Sales leadership, not Marketing. If that agreement is in place, anyone complaining about the quality of Leads should be referred to the Sales leader who agreed to the MQL definition, because that individual determined the attributes of a properly qualified lead

Change the conversation.

There should never be a question about why Sales should disposition Leads in a timely and effective manner. Change the conversation to how Marketing can help Sales accomplish those dispositions so the data acquired can help both teams improve the quality and quantity of MQLs being sent to Sales! That way, everyone wins.

Notes:

Understand Lead disposition is a team effort. Timely and proper disposition of Leads helps everyone succeed.

The information gained through timely and proper disposition helps both Marketing and Sales..

We’ve used the Demand Funnel to show why we need a complete picture of the Lead lifecycle from Marketing to Sales. We’ve convinced Sales it is in their best interest to disposition Leads in a proper and timely manner, so we can rely on our Demand Funnel. Next, let’s dig into some ways we can leverage your Demand Funnel in Three Ways to Use your Demand Funnel to Improve Marketing Effectiveness, Part 1.

Four Ways You Are Marketing Backwards Is everyone on the same page? No? Here’s how to fix it.

noreply@blogger.com (Anonymous) — Mon, 06 Oct 2014 12:03:00 +0000

Imagine attending a the symphony where none of the musicians had the score. The conductor taps his music stand and the musicians nervously look around, not knowing whether they are playing Pachelbel’s “Canon in D” or Tchaikovsky’s “1812 Overture.” Disaster is imminent, correct? Before you react to the unprofessionalism of any orchestra that would be caught in such a ridiculous situation, take a look at your own Marketing Department. Is every member of your “orchestra” playing from the same sheet of music? Let’s look at some common ways this seemingly “amateur” disconnect can happen to anyone and how to fix it.

True Story
In a weekly staff meeting, the CMO took the stage and began by confidently asking the audience if anyone could recite our key value proposition. Nobody (including myself) could. I recited – verbatim – the last generation of value proposition. As a key director in the organization, how could I not know our key value proposition? It had never been communicated outside the creative department – even to leadership within other key components of the Marketing organization! Sad, but true.

Being able to both understand and communicate your organization’s Marketing objectives, strategy and key components, such as value proposition and key differentiators is prerequisite to being able to successfully execute. Let’s look at some common issues – and fixes.

Your strategy is too complex

I see this mistake far too many times. If your demand generation strategy is complex, it very likely means you are not on the right track. While complex plans with numerous dependencies work great in Hollywood action movies, they seldom work out so well in reality. In most cases, those complicated dependencies wind up looking more like roadblocks when it comes to execution.

Can you explain your demand gen strategy in sixty seconds to a complete stranger? If not, it is probably too complex, and likely you can’t explain it well enough to everyone in your organization so they can execute against it. And if they don’t understand it, how will they know whether or not their tactical plans are actually designed to meet strategic goals? Or, worse, whether or not they have met any goals after the fact? Here are some simple tests for over-complex strategies:

1. Would your parents understand your strategy after a five-minute conversation? In General Eisenhower’s order of the day to 2.3 million troops on D-Day, his strategy was simple. “We will accept nothing less than full Victory.” Any questions? If your strategy leaves room for questions, keep working.

2. Does your team understand what to do? Do they understand what their specific tactical tasks are? Which leaders will be delivering specific tactical orders? If communication channels are unclear or your team will be getting (potentially conflicting) orders from different sources, you still have some clarifying work to do.

3. Will your team know when it has accomplished its objective? Are your goals quantifiable in a way that is easy to understand? Do all of your team members know the metrics for which they are responsible? If your measures of success are ambiguous, your team’s performance will also be ambiguous.

You have assumed communication

Communication is only accomplished when the message has been both received and understood. Often, send an email memo or delivering a PowerPoint presentation at a staff meeting assumes communication has happened. These are both forms of monologue and not dialogue. Good communication requires a dialogue. Make sure dialogue happens. Here are some good tests to make sure you have communicated your strategy.

1. Make sure strategy is understood at every level of leadership first. If your managers don’t understand it, you can be guaranteed your front line team won’t understand it either. Meet with managers individually to ensure true dialogue happens.

2. Ask specific questions. Ending a discussion with “Do you have any questions?” does not count. Start with these three questions to get a baseline on whether or not your communication has been both received and understood:

a. In your own words, can you repeat back the strategy/objective?

b. At a high level, what are you going to do to execute against this strategy?

c. How will you know you have accomplished your goals?

d. Can you successfully communicate this strategy to your team?

3. Let you managers communicate to their teams. Be in the room to demonstrate your support, but let the managers actually deliver the message. This lets the team know from whom they should expect to receive further communication about goals, strategy and tactical execution.

Have the difficult conversations up front

If there is going to be any resistance or difficulty, that conversation needs to happen prior to execution. It is much easier to make any necessary considerations for these types of obstacles before diving into execution. Often, line managers or team members have insight into tactical execution issues not visible to leaders and, if these are real obstacles to success, you absolutely need to have these conversations up front! In general, these obstacles only fall into one of two categories:

1. Situations you can control

2. Situations you cannot control.

Of those you cannot control, you can make necessary accommodations in metrics or operational process - if you know about them. Finding out after-the-fact makes for unpleasant results. Of those you can control, doing something about them up front will vastly improve your chances of operational success.

Change the conversation.

The common thread here is having conversations. Lots of conversations. Not memos and not presentations, but conversations. Great communication up front is critical to successful execution by insuring everyone is on the same page. When you tap on your music stand, the entire orchestra will be lined up on the first measure of the “1812 Overture” and your team will make beautiful music!

Notes:

Reduce complexity. The greater the complexity, the greater the chance your team will not properly understand your goals and strategy

Don’t assume you have communicated. Assure your message has been both received and understood by asking four direct questions.

Have the difficult conversations up front.

So, Marketing has a plan and everyone on the team now knows exactly what it is and how to communicate it to others both inside and outside the organization. Your plan’s success is now measured by closed business attributed to Marketing campaigns. However, to measure your success, Sales needs to properly disposition (meaning disposition in a timely fashion) Leads and Opportunities in your CRM system. Chances are good they are not. Why not? Let’s look at some good arguments you can use to get Sales on board in: Four Ways you are Marketing Backwards, Part 4.

Four Ways You Are Marketing Backwards. Do you jump when Sales asks for something?

noreply@blogger.com (Anonymous) — Mon, 29 Sep 2014 12:21:00 +0000

You know the story. It repeats like clockwork every thirteen weeks. It’s the end of the quarter, half or year and Sales needs to close more deals to make “the number.” Consequences are dire, and Sales has let you know that the end of life as we know it depends on your ability to deliver X number of hot new leads within the next 12.5 minutes! It is truly time to panic. Or not.

True Story
One year, I was preparing for the annual, week-long company shutdown for the week of Christmas – New Years when, at 3:00 in the afternoon on December 23^rd, I received a frantic email from a Sales Manager in one of our regions. “I need to get an electronic Holiday card out to my team’s prospects right now!” I was not amused, and probably push the boundaries of propriety with my response. It went like this.

So, let me understand this. You’re saying Christmas snuck up on you this year, the sneaky way they move it around every year? And you want to send an electronic holiday card for which you have no campaign brief, no content, no message and the SLA for email sends is seven working days.

Based on these facts, we could deliver your “Holiday” card approximately January 13^th. Your lack of preparation and disregard for the 3 emails we sent you in early November asking for Holiday card requests has left you in a situation where you can either a) look really stupid for sending a Holiday Card two weeks after the Holiday ends, or b) look slightly stupid for not sending one at all.

Which brand of stupid would you like to be?

I never heard back from him. Ever. I might have made him mad. But that ended the conversation immediately, because who wants to escalate their own incompetence, ignorance or lack of situational awareness to their superiors?

Frankly, I do not recommend this level of snarkiness in your internal communications. I had history and had built a great reputation for delivering under tight deadlines and difficult situations, so my professional currency bank was overflowing after a banner year. Had it escalated I would have received an official slap on the wrist and a hundred unofficial “attaboys,” but again, I don’t recommend it.

The Point?

The point is that – despite my extreme level of snark – my response was:

1. Based on facts. Guess what, Christmas and New Year’s Day don’t move. Not noticing that until it’s too late is kinda your own fault.

2. Based on preparation. We had created a process to accommodate these foreseeable requests. Christmas did not sneak up on us.

3. Based on communications. We created an internal, three-touch campaign to communicate this process to the audience who needed to know this information.

You can do this, too. There is no reason for lack of a plan or a process with which to execute it.

Change the conversation.

Back to our original, predictable, thirteen-week cycle of lead acceleration requests. Like Christmas and New Year’s Day, the end of quarter is a fixed date that doesn’t move. It is tied to your organization’s fiscal calendar. If you can predict it, prepare for it! Let’s look at the facts you already know about the end of next quarter.

1. Sales will ask for more Leads.

2. Those “Leads” are really MQLs that need to be qualified, mid-funnel Contacts who have displayed some level of buying behavior. Some portion of that funnel would be ready to buy given the proper incentives. Some of those know those incentives come at the end of the quarter and are just waiting to hear about them.

3. You have the capability to pre-fabricate campaigns designed to deliver that message to that audience.

Why would you wait until Sales asks for this inevitable campaign when you already know it’s coming? Start building today, so you are prepared to execute before Sales even asks. You will begin building up currency in your professional reputation bank for that (also predictable) day you will need to cash it in for some snark!

Notes:

Prepare for the predictable instead of reacting to it.

Build repeatable and scalable processes you can utilize over and over.

Communicate your plan to your constituents.

When communicating you plans, it is critical that a clear and consistent message is always delivered. Does your entire team have good clarity on what you are expected to deliver next quarter? Next year? In next week’s edition of {Demand Gen Brief} we will look at internal communications and how it is critical to your interdepartmental communications in: Four Ways you are Marketing Backwards, Part 3.

Four Ways You Are Marketing Backwards. Has Marketing signed on for a quota? Why not?

noreply@blogger.com (Anonymous) — Mon, 22 Sep 2014 12:28:00 +0000

Quota? For Marketing? What?

Absolutely, and it’s a great idea! Here’s why.

Sales is from Mars, Marketing is from Venus
Most organizations experience this odd tug-of-war between Sales and Marketing, in which both spend more time complaining about the other’s performance than hitting goals. More often than not, I find this misalignment between Sales and Marketing can be attributed to a single factor: lack of shared goals.

Let’s face it, you motivate your team towards the specific performance goals by which your team’s success is judged. Hopefully, those goals are closely tied to overall organizational goals that, since we are generally working in for-profit companies, somehow roll up to revenue and profitability. Even if you are a charitable organization, your goals are probably related to raising funds (revenue) for your chosen charitable purpose. If Marketing’s goals do not tie back to these same revenue-based goals, you immediately are at odds with Sales, whose goals are definitely tied to hitting a revenue number. Let’s look at an example.

Lead vs. Revenue: Vegas Oddsmakers Have Leads at 3 to 1

Let’s say Sales success is tied to a revenue goal for closed business. Marketing success, however, is tied to Leads generated. These seem to be compatible goals. In practice, what happens is Marketing calculates the number of Leads necessary to hit the Sales revenue goals and begins to deploy various campaigns to generate Leads. Sales approaches the end of the quarter and is shy of their quarterly goal (we’ve never heard that before, right?), and asks Marketing to ramp up Lead production. With the lead-time necessary to ramp up new campaigns, Marketing can’t possibly generate the Leads requested in the time requested. Answer? Change the “definition” of a Lead to allow more to pass through to Sales. Problem solved. Marketing has exceeded its quarterly goal for Lead generation but, because the Lead quality dropped, Sales actually misses its quota by more than predicted while doing twice the work to call on low quality “Leads.” (For more on this subject, see Sales Thinks Your Leads Stink.)

The problem is obvious. What’s worse, I have seen this happen in billion-dollar companies more often than any self-respecting Marketer should want to admit. Is it any wonder Sales thinks your leads stink?

Change the conversation.

Fortunately, the solution is as obvious as the problem. Shared goals – based on revenue – will create a Sales-Marketing team working together, rather than competitors working against each other. So why not partner with sales around shared revenue goals? Start the conversation from the Demand Gen side, and see if the dialogue with Sales starts to change from “Your Leads stink” to “how can we work together to uncover the best Leads?”

Notes:

Work with Sales to define shared goals.

Define your goals using the same metric as Sales: closed revenue.

One of the side effects of not having shared goals with Sales is knee-jerk response. In the “real-life” example above, it is entirely predictable that sales will inevitably come to the Demand Gen team at each quarter end, looking for more Leads. What they really need is more closed business. However, Sales has a tendency to scream loudly and when Sales screams, the C-Suite assumes there is something wrong, revenue projections will be missed, the stock will tumble, shareholders will revolt and… well, you know the rest. If you are constantly reacting to Sales, rather than executing against a sound strategy, you need to read next week’s edition of {Demand Gen Brief}: Four Ways you are Marketing Backwards, Part 2.

Head in the Cloud? The one time “MORE” is really not.

noreply@blogger.com (Anonymous) — Mon, 15 Sep 2014 12:33:00 +0000

I think we all like to receive things – especially unexpected things. Like when you receive that unexpected gift from your significant other for no reason at all. Or when you find a twenty-dollar bill in the parking lot a the mall. Or when you get an unexpected raise (even though you probably deserved it). More is better, right?

How about when you discover several free (or really inexpensive) cloud connectors that perform a variety of interesting functions. Everyone needs clean data, so why not really clean it up with several plugins or cloud connectors? Or what about appending data, since you probably need addresses and phone numbers anyway. Free? More is better, right? Well, maybe not in this case. Let’s look at a few reasons why not.

Free is not Free
This is the most obvious (and easiest to understand) reason you may want to investigate a little deeper. Check to make sure the free cloud connector or plugin does not require a paid subscription service to actually use it. It should be fairly simple to determine the process required to obtain value from the connector, so make sure that surprise isn’t an unpleasant one.

The Results are not Useful

Going back to previous {Demand Gen Brief} posts, we saw that first identifying your business problem is the key to understanding how to solve for it. For example, while data appending cloud connectors can be useful, make sure the field values are what you need. For example, if your target audience is regional warehouse managers, data that appends the headquarters address and phone number is not going to be particularly useful. Compound that statement for international organizations, where a HQ address might get you in hot water for emailing to a recipient who actually lives and works in a tightly regulated country.

The Results Conflict with Each Other

This requires a bit more investigation and requires you to fully understand your root business problem. What happens when you extract the phone number from one service and the address from another and the two services use very different methodologies for obtaining (or curating) their data. You may find area codes and zip codes in conflict with one another and your logic programs are unable to determine the real location for that company.

Speed Concerns

As we saw in an earlier post, some cloud connectors and plugins have imitations on processing speeds or volumes. These need to be carefully considered when included in programs like Contact “Washing Machines” that function in-line in your lead management processes. If you have lead delivery SLAs, make sure you are not implementing cloud connector processes that take longer that your SLA allows!

Change the conversation.

When it comes to cloud connectors and plugins, free is not always better. More is not always better. Finding the correct level of processing is always the best solution. Only address real problems with solutions that directly solve them. Partial solutions or mismatched combinations of solutions may well leave you in a worse condition than where you started.

Notes:

You need to first understand your business problems.

Fully understand what each cloud connector or plugin actually does.

Make sure any cloud connector actually solved your business problem.

At the end of the day, you need to understand how your Demand Gen efforts are contributing to the bottom line. We will begin a four-part series to understand what you should be working towards, some serious question you should be asking and a common problem to avoid in: Four Ways you are Marketing Backwards.

Head in the Cloud? Three ways to evaluate cloud connectors.

noreply@blogger.com (Anonymous) — Mon, 08 Sep 2014 13:01:00 +0000

There seems to be a plugin or a cloud connector to do just about anything. Match data, clean data, import data, export data, add data to the data you already have, brew an espresso… OK, maybe not brew an espresso, but most certainly everything else.

In fact, they all sound so great and they cost so little, why not just get them all? As we just read, getting them all could definitely create some conflicts in your database and, while each serve a particular purpose, their purposes might not match your purposes! So, how do you go about selecting the plugins and cloud connectors best suited to your purposes? Let’s look at three ways you can evaluate the best approach to implementing one or more that will solve – not exacerbate – your problems.

Mind the Gap
Your selection of plugins or cloud connectors should be initiated by functional gaps in your lead management process. If you don’t know of any functional gaps, you have either a) the world’s one and only perfect lead management process or, b) not performed a lead management (or lead lifecycle) analysis. There are a few questions you need to answer when mapping your lead management process, and these will guide you to understanding the gaps (usually informational gaps) in your process.

· Do I completely understand my Total Addressable Market (TAM)?

· Do I understand all the buyer types and their individual buyers’ journeys?

· Do I have all the information I need to properly segment my audience?

· Do I have all the information I need to mechanically score my contacts?

· Do I have all the information I need to properly route leads where they need to go?

If you don’t’ have complete answers and the data to support those answers, you have discovered your gaps.

Identify your options

If you have an information gap in your lead management process, chances are good others have similar challenges. Where challenges exist, bright people have often identified solutions to those challenges and create cool solutions. Many of these solutions are in the form of cloud connectors and plugins you can easily install in your MAP or CRM platform.

Do some research and identify a list of solutions and the companies who created them. Then use social media to perform some initial discovery about how well your peers have fared using them. Go beyond feature/function comparison to see how well the overall solution performs in real world application. Check for the company’s responsiveness in dealing with installation and service calls. Make sure the solution can meet your speed requirements, especially if you have lead timing SLAs with your Telequal or Sales teams (cloud connectors can be slow). Make a list of requirements and make sure the solution can meet those – or surpass them!

Pilot your solution

Many of your potential solutions will offer some kind of free trial or evaluation period. If not, ask the sales rep to allow for one. Within a thirty-day test period, you will have identified whether or not the proposed solution is a solution or just another headache. Create a small test group of contacts in your MAP representative of the information gaps you commonly experience.

A good way to do that is to take a cut of your data with a fairly random factor, such as one thousand contacts with first names beginning with the latter “J.” Create copies of these contacts, substituting test email addresses and names, such as First1, Last1 and test1@ACMEtestcontacts.com. If you can store these in a Contact Group or similar method of isolation, it makes it easy to delete these contacts after your pilot.

Change the conversation.

This methodology works for virtually all plugin and cloud connector solutions you may want to deploy. By aligning the solutions to the problems, vetting vendors and piloting your solutions, you will get where you need to go without creating additional problems along the way.

Notes:

You need to first understand your process gaps.

Systematically vet potential solution providers.

Pilot your solutions.

Next, we want to understand one of the specific issues you need to avoid. Many plugins and cloud connectors have to balance the need to create solutions with broad appeal to offset the inexpensive cost of cloud-based solutions. This can often translate into a bit of a one-size-fits-all structure that creates unnecessary system overhead: Head in the Cloud? The one time “MORE” is really not.

Head in the Cloud? Why more plugins and cloud connectors may be making your problem even worse!

noreply@blogger.com (Anonymous) — Tue, 02 Sep 2014 13:03:00 +0000

Think of the last visit to your doctor. Did you drag your tired, nauseous self into the exam room, plop down on that table with the funny roll of paper and have your doctor immediately proclaim, “I think you’ll need major surgery” before even examining you? Would you maybe ask her to use that stethoscope and those little tongue depressor thingies to perform some basic diagnostics first? Maybe an X-ray or CT scan might be in order before calling in the scalpels? How about a second opinion, doc?

Or how about your car? When you wheel in for your 25,000-mile service, what would you think of your mechanic who says, “Whew! That car’s maroon – it’s going to need a new engine. And new wiper blades.” Would you just keep right on driving until you found a mechanic with the proper diagnostic equipment to evaluate what – if anything – needs adjustment? Of course you would!

While we would never subject our bodies or our vehicles to such ridiculous treatment, it seems we are happy to turn over our Marketing databases and MAP platforms to exactly this kind of treatment! Cloud connectors and plugins seem like such great solutions to problems, they are just irresistible. They are, for the most part, inexpensive, easy to install and run without any human intervention required. What’s not to like about them? Here are a few things to think about.

They mask the real problem
Like taking ibuprofen to reduce a fever when the real problem is an infection that needs treatment before your immune system can no longer battle on its own. If left untreated, the infection can kill you while the ibuprofen artificially reduces the fever your body was using to fight the infection. Likewise, cloud connectors can treat problems to an extent.

Bad data? Get a cloud connector to clean it up. Can’t segment? Get another cloud connector to standardize your data. Need physical addresses? Get yet another cloud connector to pull in addresses based on the browser’s IP address.

Sounds like a great solution to – what was the problem again? Oh, yeah, bad data. And by “bad” I mean incomplete, non-standardized or incorrect data.

They can limit your options

Because they are inexpensive (or sometimes free), cloud connectors and plugins can have standards to which you will have to comply. For example, if you segment geographically by Congressional Districts instead of Area Code, or have a unique target audience that doesn’t use the “standard” organization levels of Manager, Director, VP (etc.), you may be out of luck. The more sophisticated your segmentation, the less likely cloud connectors will completely address your root problem.

They process at different speeds

You may find you have to make accommodations for the speed and/or volume of cloud connector processing. Many have limitations on the number of Contacts processed per unit time, require longer processing cycles than you might expect, or both. Understanding what kind of throughput you require is critical when determining whether or not cloud connector or plugins are a viable solution for you.

What should you consider?

First, you need identify the problem from a business perspective. These are Demand Generation and Lead Lifecycle problems, not technical problems. These problems follow a formula, and are easily identified:

A to B by when

For example:

I need to promote our new widget to every medical practice with more than 30 employees in the state of Florida before April 30^th.

Now that you have identified the business problem, you to perform some diagnostics to determine the reasons why you can’t promote your widget to your target audience. The root cause (diagnosis) will help determine how you will solve that problem (treatment). Let’s look at some potential examples of root problems.

1. You don’t’ have any medical practices in your database. Those cloud connectors may polish up the data in your MAP only to find out that you have nicely standardized and appended a database not in your target market. Your still have not solved your business problem.

2. You don’t have geographic information on your contacts. Many organizations try to append this data via cloud connectors or plugins that extract address information from either company names or IP addresses. These can produce spotty results if the company headquarters is in another state or in another country. Fi you are marketing to a medical practice in Pensacola, but the headquarters is in Poughkeepsie, your automated programs may inadvertently skip right over that prime prospect!

3. Your title segmentation is incomplete and inconsistent. That cloud connector or plugin is looking for some title to rationalize to “Director” or “VP” and Dr. Sarah Jones – the actual director of your target medical practice – has a title of “Physician.” Your database now thinks nobody is in charge of your prime target medical practice.

Change the conversation.

Don’t misunderstand, I believe cloud connectors and plugins are a good thing. They have good application when applied to the right problem. They are, however, not a magic bullet for every business problem and, in fact, can actually make your root problem worse!

Notes:

You need to first understand your business problem.

You need a proper diagnosis to determine the solution.

Not every problem can be solved with a standard solutions, cloud-based or otherwise.

Next week, we will continue the discussion about cloud connectors and plugins. Now that we know we need to really understand our business problem before prescribing a technical solution, we will investigate how to determine if a cloud connector is a viable solution in next week’s edition: Head in the Clouds? Three ways to evaluate cloud connectors.

Three Ways A-B Testing Will Improve Your Marketing. (Part 3) Into the Vortex.

noreply@blogger.com (Anonymous) — Mon, 25 Aug 2014 14:05:00 +0000

Automating your Demand Generation functions is often referred to as a journey. However, your journey need not be aimless and without a destination. In fact, if you don’t have a destination in mind, your journey will take much longer then necessary and, in fact, may never end. As the saying goes, “If you don’t know where you’re going, how will you know when you get there?”

While your ultimate destination may be something like “a world-class Demand Center,” you will need to establish some milestones along the way to measure your progress. Testing will help you to establish your progress toward (and beyond) those milestones. When it relates specifically to A-B testing, there are some great milestones against which you should always be measuring your progress! Those milestones may be found in your Demand Waterfall (or Demand Funnel).

Principle #1: Programs should be measured against movement
Marketers often fall into the trap of trying to generate activity. Activity is fine, but if that activity does not result in movement, it has both cost you money and gained you nothing. Let me explain.

Let’s say you create an outbound marketing program, sending 50,000 emails to your target audience. You have written incredibly compelling content with a CTA pointing to a wildly popular whitepaper. Your Subject Line drew a 50% open rate and your content prompted 50% of the opens to download your fabulous whitepaper, resulting in 12,500 downloads at a 25% conversion rate. My guess is you’d be jumping up and down at your success after posting these metrics. Not so fast! You’ve generated lots of activity, but have you generated any movement?

Unless you got paid for all of those whitepaper downloads, you’ve actually spent time and money to send out a free piece of information to your prospects, customer and, likely, your competitors. Here’s the real question: what did the recipients do as a result of reading the whitepaper? What was the goal of your program? Was it awareness, engagement or conversion? Did the readers react according to your goals?

Principle #2: Movement should be measured in terms of Waterfall Stages

You have a Demand Waterfall for a reason, which is to determine your prospects’ stage in their buyers’ journeys. Assuming your Waterfall accurately reflects that buyer’s journey, each and every program you deploy should have the specific purpose of moving the prospect from one stage to the next in the funnel.

In our previous example, let’s assume our whitepaper program was an engagement program, with the purpose of moving Inquiries to AQL (Automation Qualified Lead) stage. Based on this goal, we now have a movement objective against which we can measure the success of our program. We can determine the success or failure of the program in terms of how many Inquiries convert to AQLs as a results of the program.

Principle #3: Movement should indicate a significant interaction with your brand

Is downloading the whitepaper enough to indicate a significant interaction? Just because a reader downloaded it does not guarantee he or she even read it. How many downloads do you have just sitting on your hard drive waiting to be read at some future date? We can differentiate between insignificant and significant by creating a definition for those actions.

An insignificant interaction is a download with no continuation of the interaction. Sometimes I download something simply because I want the information and somebody has offered it for free. I have absolutely no intention of purchasing anything, but the information seems interesting or useful.

A significant interaction is a download with a continuing action. For example, a well-designed program might have a secondary CTA within the downloaded asset, prompting readers to engage more deeply with your brand. As an example, after reading mare about a specific A-B Testing solution, another CTA could prompt the reader to try a free testing tool or interact with a free testing framework generator. This continuation action would indicate the reader’s real interest in your solutions.

How do we measure movement?

Waterfall movement is a matter of understanding changes to a Contact record in your MAP. This change has a number of components you need to understand in the context of many other potential changes simultaneously affecting that same Contact record. So how do you isolate the movement you need to measure? The first priority is to make sure you are capturing the required data behind the metrics you want to measure!

1. You should systematically link your Waterfall program to your response measurement. There are a variety of ways to do this; the goal is to attribute Waterfall movement to a specific response – almost always the most recent significant interaction. This is different from Campaign attribution, in which most organizations want to attribute closed revenue across all campaigns that touched the Contact during the Lead lifecycle.

2. You need to record your program responses so they are actionable by your Waterfall program. This means you will not only need to understand which program, but when the Contact responded.

3. In most cases, you will also need to record how the Contact arrived at the program CTA in order to convert. This is a great basis for testing which routes to the CTA are most effective.

Change the conversation.

Optimization should be conducted with the program movement goal in mind. If we go back to our original whitepaper marketing program, we would likely make significant changes to the way we determine success if our goal is Inquiry-to-AQL conversion. IN that case, 12,500 whitepaper downloads that don’t result in AQL conversion might look like a tactical success, but is actually a strategic failure. How would we change the conversation?

First, we would change our target audience to include only Contacts in the Inquiry stage. If the goal is to convert Inquiries to AQLs, what is the purpose of sending to any other than Inquiries? Second, we would insure our infrastructure was pre-built to capture the data points necessary to measure Inquiry-to-AQL conversion. There is no sense setting a goal we cannot measure. Thirdly, we set up our A-B testing points to measure the things we can both control and change, such as traffic sources. Did outbound emails work better than banner ads, or did paid SEM work better than purchased media?

Notes:

Testing must be performed with an overall objective in mind.

You should be testing movement, not activity.

Your infrastructure must be pre-built to capture the data necessary to your metrics.

Next week, we will take a look at how your MAP platform might be doing a whole lot of processing that accomplishes nothing. With SaaS and cloud-based solutions come a plethora of cloud-based add-ons. They do all sorts of nifty stuff, but do you really need or want them? Maybe, but there is a right and wrong way to look at cloud connectors and plug-ins. We will look at them in next week’s edition: Head in the Clouds? Why Less may be More.

Three Ways A-B Testing Will Improve Your Marketing. (Part 2) Avoid Misdirected Testing.

noreply@blogger.com (Anonymous) — Mon, 18 Aug 2014 12:51:00 +0000

Last week we decided that any testing framework needed to have a specific destination in mind – your objective. While it is reasonably straightforward to match your testing framework to your overall Marketing objectives, it is easy to get misdirected and lose track of your destination.

If your car has a GPS navigation system and if you’re anything like me (I always have a better route), you have heard that voice in the GPS say, “Turn around at the nearest U-turn!” Repeatedly. Mindlessly. Until you just turn it off. (Or, in my case, the GPS finally gives up, decides I’m right, and recalibrates the new course.) You’re A-B testing framework should be like that voice in the GPS, incessantly reminding you that you have left the prescribed course. How? Here are some guidelines to help you understand when your testing is off-course.

Guideline #1: A-B test results are not extensible and repeatable
Subject Line testing often falls into this category. If your testing is not extensible and repeatable, the test is only applicable to that particular email. To repeat a lesson we learned in {Demand Gen Brief} last week, categories of tests, rather than specific tests should be used like this:

We would apply scientific method to create a series of hypotheses to test these assumptions to ultimately create a rule by which all future subject lines are created, such as:

1. Subject lines should be less than 35 characters.

2. Subject Lines should include our company name.

3. Subject Lines should contain the recipient’s first name.

Guideline #2: A-B tests are not actionable

What’s the point of performing a test if you can’t action the results? An example of such a test would be to perform an A-B test on CTA button colors only to find that purple wins by a landslide. Problem? Purple is your main competitor’s color and your brand standards prohibit its use in any way. There are, however, some very interesting takes on this guideline. For example, “best practices” are to not use some key words in your subject line, because they can trigger email client SPAM filters. Or not. What if 50% of your emails got sent to SPAM filters because you used the word free in the subject line, but the remaining 50% showed a 1200% open rate increase over the next best subject line? Would you break “best practices” and go with free? Of course you would, unless…

Guideline #3: A-B tests are specific to only one part of the equation

Remember, each test in your framework is designed to test a specific metric, and each metric measures only a part of the journey from Prospect to Closed/Won. In the previous example, using the word free in the subject line increased your open rates by 1200%. Great, but what happened next? Did those opens turn into clicks? Did those clicks turn into MQLs, SQLs and, ultimately closed business? Your testing framework should be looking at the entire lead lifecycle to determine how each action contributes to the progress of the entire demand funnel. Let’s look at another example.

Open Clicks Convert to MQL Convert to SQL Closed/Won

1200x.5=600 .01x600=6 .50x6=3 .5x3=1.5 .5x1.5=.075

100 100x.25=25 .50x25=12.5 .5x12.5=6.25 6.25x.5=3.125

In the end, that great open rate using the word free only resulted in opens, not clicks. Using the exact same conversion rates from MQL through close, we find a 400% improvement in closed business not using the word free in the subject line.

Change the conversation.

Again, A-B testing must be performed within a holistic framework that considers the entire demand funnel and what each tested step contributes to the whole. Unless you get paid for people opening your emails, the 1200% increase in open rates does not serve your organization’s overall objectives.

Notes:

Testing must be performed within an overall framework with a specific objective in mind.

Testing must consider both the specific action being tested and its overall contribution towards the overall objective.

Again, “best practices” for company A are not necessarily best practices for company B.

Next week, we’ll look at how to tie your testing framework to demand funnel progression, and why it is critical to build your framework that way: Three Ways A-B Testing Will Improve Your Marketing. (Part 2) Into the Vortex.

Three Ways A-B Testing Will Improve Your Marketing. (Part 1)

noreply@blogger.com (Anonymous) — Mon, 11 Aug 2014 12:58:00 +0000

The old Chinese proverb says. “A trip of a thousand miles begins with a single step.” While I’m still not sure how the ancient Chinese knew anything about English units of measure, the saying does imply something very important: a destination. A trip of a thousand miles invariably leads somewhere. And that somewhere is likely missing from you’re a-B testing.

If your testing framework is only that, a testing framework, you are missing out on one of the key benefits of testing. You should be testing with a destination in mind: optimization. Your goal is to both optimize current campaign performance and do it in such a way you can apply that optimization to future campaigns. Let’s look at an example of the types of A-B testing I’ve seen.

Test #1: A-B email Subject Line testing
You may have performed this type of testing, so you know how it goes. This is an open rate test, and is critical, since nobody can respond to your CTA if they don’t open the email first. You take otherwise identical emails and test one subject line against the other, such as:

ACME sells really keen widgets
ACME widgets solve all the world’s problems

You split off 10% of your campaign segment and send Subject Line 1 to half that audience and Subject Line 2 to the other half. Whichever Subject Line wins the test gets applied to the other 90% of the segment, assuming the open rates will follow the same pattern as the test.

Test #2: Email CTA link testing

Once the recipient opens your email, the next critical step is to obtain a response to your CTA. A number of tests have been employed here, such as:

Change the color of the link button – red vs. blue
Move the button to different spots on the page – right column vs. inline
Use different graphic elements as a button – arrow vs. rectangle

The test is run in exactly the same manner as the Subject Line test, with the winner of the pilot group getting sent to the remainder of the segment.

So, what’s wrong with these tests?

Nothing is wrong with the tests themselves. What’s wrong is they are not performed within a framework aimed at solving the real problem. Let’s start by asking this question: How much does your organization get paid when someone opens an email? How about when they click through from an email? (Unless you are a PPC organization those business model is built on creating click-throughs.) For the vast majority of B2B organizations, the answer is $0. We get paid when someone engages with our sales team and ultimately buys our products or services. So what should our optimization framework ultimately measure?

Tactically, we should think of open rate optimization in terms of “best principles” (there’s that term again) we can apply against all of our tactics to improve our funnel conversion rates and velocity. In our Subject Line test, will we actually use that identical Subject Line in another program to the same segment next month? I hope not. Therefore, we need to think of our optimization framework as a series of repeatable principles that we can employ in all subject lines. We would apply scientific method to create a series of hypotheses to test these assumptions to ultimately create a rule by which all future subject lines are created, such as:

Subject lines should be less than 35 characters.
Subject Lines should include our company name.
Subject Lines should contain the recipient’s first name.

Important Note: these are examples of best principles and should not be applied uniformly to your emails as a “best practice.” Again, best practice for Company A could be worst practice for Company B!

Change the conversation.

To successfully optimize, your testing should not stop when the tactical campaign is over. Your testing should follow all the way through the demand funnel to Closed/Won (or lost, but we’ll assume the best here). As we’ve mentioned in previous editions of {Demand Gen Brief}, all of your programs should be specifically designed to create forward funnel movement, and should be built around a specific process. Optimizing only a part of the process will not provide the end-to-end improvement you want.

Notes:

Testing must be performed with an overall objective in mind.

Tactical testing is not generally applicable over all of your campaign tactics.

Build your optimization framework around principles that can be applied to multiple tactics.

Next week, we’ll look at misdirected testing and how you can avoid falling into that trap: Three Ways A-B Testing Will Improve Your Marketing. (Part 2) How to Avoid Misdirected Testing.

Sales Thinks Your Leads Stink. And yes, you can fix that! This is how. (Part 3)

noreply@blogger.com (Anonymous) — Mon, 04 Aug 2014 12:43:00 +0000

You know the smell. It’s late and you’re driving on a deserted highway out in the country. The smell hits you like a ton of pungent, acrid bricks. Dead skunk. Your only thought is how to not get any of that on you as you carefully navigate the darkness seeking to avoid the putrid remains.

Now picture this. Sales thinks your “marketing qualified” (imaging the sales leader making sarcastic air quotes as she complains to you) stink like a dead skunk. That smell you try desperately to avoid on the road in the dark of night. Then the unthinkable: after describing the nauseatingly disgusting state of your (air quotes) leads, she asks for more. Who intentionally runs over that dead skunk? Is your Sales department stupid? Nope. Just uneducated. And it’s your job to educate them!

Remember the Brass Tacks questions?
Last week, we ran the math. (If you missed last week’s blog, click here. You’ll want to know the math behind the brass tacks!) Math is indisputable, but it doesn’t answer the question of “how?” This left us with three Brass Tacks questions:

1. How many Contacts do we need at top of funnel to meet the required number of MQLs?

2. What can we do to affect out conversion rates at each stage?

3. What can we do to affect the time-in-stage to increase velocity?

We actually need to ask question 1 twice, once before we begin our exercise (to establish a benchmark) and again after we finish (to establish our improvement). In last week’s example, we needed 10,000 Contacts at the top of our funnel to reach the target number of Marketing Qualified Leads (MQLs). This established our benchmark segment size. (Again, click here to review how to calculate your waterfall.)

The answer to brass tacks question 2 is a lot more flexible, and requires your unique marketing skill set to execute. However, there are some guiding “Best Principles” that will help you get there quickly, regardless of your market or product.

Principle #1: Execute every program with a specific funnel objective in mind.

This is different from a shotgun approach that targets everyone at every stage in the buying process. Unless you are selling commodities and your only market advantage is price, it is unlikely your B2B buyer is going to find you out of nowhere and send in a million-dollar order based on a single online interaction with your company. Nobody seems to disagree with this fact, but I find it amazing how many people execute marketing programs in this manner.

Principle #2: Even if you’re right, you’re not right.

This means you need to test everything, even if it seems to be working. Improving conversion rates is a matter of playing a continuous game of “King of the Hill.” Your current champion is only the benchmark by which you will compare the next challenger. And as soon as a challenger dethrones the current champion, the game begins anew.

Principle #3: There’s not one answer for everything.

What works for one market or vertical may not work for another, so don’t assume someone else’s “best practice” will automatically work for you. For example, at a time when “best practice” was to send all emails as HTML, I tested this practice. It turned out not to be “best” at all for my application. In fact, text-only emails outperformed their HTML counterparts (as measured by click-throughs) by over 35%. Again, test everything, including “best practices.”

Affecting velocity (brass tacks question 3) is a matter of reducing time in stage for those stages up to a conversion stage, such as MQL. Similar to question 2, there are principles, rather than practices you should follow to decrease your time in stage. Remembering that we need to be executing every program with specific stage movement in mind, we can add two more principles to the mix:

Principle # 4: Know your buyer.

In order to accelerate your funnel, you must completely understand your buyer: who, what, when, how and why she buys. If you have not profiled your buyer, you have no hope of accelerating your funnel because you have no idea which parameters to change and, likely have no data to support those changes. As an example, if your product or service is highly reliant upon FY-driven buying cycles, does your MAP database contain FY start month? If not, how are you going to know when to begin delivering marketing messaging? Does your buyer rely heavily on input from a technical user to make purchasing decisions? Have you created the right content to help that buyer with the technical conversation, and is that communication a part of your funnel acceleration strategy?

Principle #5: Make sure you’re measuring the right thing.

Your MAP will require customization to automate and measure time in stage for your specific demand waterfall because your stage promotion and demotion rules are unique to your organization. Having a correctly defined waterfall program is the first step in measuring progression. Once built, you need to measure your demand waterfall on a regular cadence – at least monthly, perhaps even weekly. The two key metrics you need to capture are:

1. Total number of Contacts in each stage. From this metric, you will be able to calculate your stage conversion rates and cumulative conversion rates.

2. Average time in stage for each stage.

You will want to keep a running log of these measurements to spot trends and measure improvement over time. In general, you want your funnel to move from looking like this:

Change the conversation.

Once you have a complete view of your demand waterfall and understand the factors that affect conversion rates and velocity, you can change the conversation. Following theses principles, you will know beforehand the who, what, when, how and why of your buyer’s journey and know what it will take to reach a specific goal. And you’ll have both the math and the data to back up your argument.

Notes:

You must agree with sales on the definition of a “sales-ready” lead.

There are only three components of Lead volume Marketing can control.

Learn to calculate each of these components and let the math do your talking for you.

This week we talked a lot about testing. Test your conversion rates. Play King of the Hill. Even test “best practices.” That’s a lot of testing. So how should you go about testing? Next week, we’ll begin a new series named Three ways A-B testing will improve your Marketing results.

Sales Thinks Your Leads Stink (Part 2): We need MORE LEADS. And yes, you can fix that!

noreply@blogger.com (Anonymous) — Mon, 28 Jul 2014 13:20:00 +0000

Have you ever heard the phrase; “You made your own bed, now you have to lie in it?” This is the perfect example. As Marketing seeks to become smarter and evaluate leads quantitatively, the initial impact to the lead pipeline is going to be a sudden drop in volume. This will happen virtually every time. And the inevitable reaction from sales is a predictable as the sunrise: “We need more leads!” Let’s examine why giving in to this lie is a terrible idea.

Remember how we got here?
Let’s first recount how we got here. We came to an agreement between Marketing and Sales on what constituted a “sales-ready lead.” Those attributes were quantitative and measurable. Marketing created a Lead scoring system to evaluate every contact on the basis of those agreed-upon criteria. What is being passed to Sales fits those criteria. They have a name and are no longer generic Leads but MQLs or AQLs. Remember?

This is where the rubber meets the road, and demonstrates the importance of previous steps of gaining Sales agreement on the criteria for determining the meaning of “sales-ready.” This is also where Sales either becomes Marketing’s greatest ally or greatest enemy. And it’s your choice. But, before we get to your decision, let’s look at the math. Yes, math.

Look at the math. Because math is indisputable.
Let’s start with the demand before you, “We need more Leads.” And, for the sake of clarity, let’s call them by their proper name, Marketing Qualified Leads, or MQLs. The total number of MQLs is a function of two factors:

1. Number of Contacts in your Marketing database.

2. Conversion rates between funnel stages.

3. Velocity of those Contacts from Prospect (or your top-of-funnel designation) to MQL.

How many Contacts do you need?

The number of Contacts affects your MQL output as a simple multiplier. For example, if your ratio of MQL to Prospect is 0.1 (10%), then you simply determine the number of MQLs you require by dividing that number by your ratio. In this case, if you need 1,000 MQLs, your simple ration equation is 1,000/0.1=10,000 Contacts in your database

Calculate your Conversion Rates.

Conversion rates are much more complicated to change, but should always be top-of-mind for Demand Center managers. Small changes to conversion rates have a big impact on your ratios and, by extension the required size of your Marketing database. The 10% MQL-to-Prospect ratio above is likely a combination of conversion rates between multiple steps, something like Prospect à Inquiry à MQL. If Prospect à Inquiry conversion rate is 50% and Inquiry à MQL conversion rate is 20%, you net out at an overall conversion rate of 0.5 * .0.2 = 0.1, or 10%. By improving the conversion rate between Prospect à Inquiry by 20%, we move that ratio to 0.6 or 60%. And, let’s say we move the Inquiry à MQL rate by 25%, we move that ratio to .25 or 25%. Now let’s look at the math: 0.6 * 0.25 = .15, or 15%. We actually moved the total ratio by 50%! Our calculation now looks like this: 1,000/0.15=6,667 Contacts in your database.

Velocity has impact.

Finally, the velocity calculation can increase your throughput to MQL. However, this calculation is difficult to measure and has the least impact on your ratios. Regardless, you should know it and be able to calculate it for your MAP platform. Velocity is simply time in stage. Velocity impact is time-in-stage*volume-in-stage. By reducing time-in-stage, we successfully improve our pass-though volume by the same percentage. For example, if your average time-in-stage for Inquiry is 20 days, this means you have Inquiries stacking up behind a 20-day “dam.” This analogy is a great way to visualize the velocity effect. If you can lower the time-in-stage by 25% to 15 days, you are allowing more volume through your dam by lowering its threshold. Imagine lowering a dam on a diver from 20 feet to 25 feet – what would happen? Initially, a flood of backed-up Leads would flow through. Remember, you will need to maintain the volume of incoming Lead flow to maintain this volume, once the threshold is lowered!

Brass tacks.

We now know what needs to change. The “brass tacks” question is how do we effect those changes. We need to ask these three questions:

1. How many Contacts do we need at top of funnel to meet the required number of MQLs?

2. What can we do to affect out conversion rates at each stage?

3. What can we do to affect the time-in-stage to increase velocity?

The WRONG Response!

In many cases, the immediate response is to take the easy road to answer question 2. The easy road is to artificially lower the dam by reducing or eliminating the agreed-upon criteria for a “sales ready” Lead. (Bypassing Lead Scoring.) This leads directly to Cause A, and negates one of the key benefits of a Marketing Automation platform. It is quick, easy and completely wrong.

Change the conversation.

Let’s go back to the original demand, “We need more leads.” The conversation usually goes something like this:

Sales: What happened to all our Leads? We’re dying over here.

Marketing: Lead Scoring has reduced the quantity, but improved the quality of the MQLs.

Sales: What? I don’t care. I need more leads NOW!

Marketing: But we agreed on the criteria for MQLs, and we are sending exactly what you require.

Sales: I don’t care! I have 200 reps sitting around not making phone calls because the pipeline is dry! Do what you have to do to get me more leads today!

Marketing: That’s not so easy, since we set up the system to do what you requested.

Sales: I’m calling the SVP. This is BS. We need people to call. The Sky is falling and the world is coming to an end by noon.

Marketing: Ok, OK, I’ll turn off Lead Scoring!

And, you just wasted hundreds of thousands of dollars on Marketing Automation.

Instead, let’s have this conversation. We’ve established and agreed upon the definition of a “sales ready” Lead. We now have the calculations to demonstrate exactly what we need to generate the required number of MQLs. Based on this equation we can know ahead of time what it’s going to take to generate the required number of MQLs. Here are the two options:

1. Marketing is provided the necessary funding to perform the necessary actions to meet the required number of MQLs, or;

2. Sales can reduce its staff of sales reps to meet the number of MQLs that will flow through the system at current capacity.

How many times is option number two even contemplated? Is that just because Sales screams louder? Data will answer the screaming and help prevent Marketing from falling for the “We need more leads” trick at the expense of maintaining the quality of those leads.

Notes:

You must agree with sales on the definition of a “sales-ready” lead.

There are only three components of Lead volume Marketing can control.

Learn to calculate each of these components and let the math do your talking for you.

We looked at three “brass tacks” questions earlier, and you probably thought to yourself, “Great, but how?” And that’s an excellent question. Next week, we’ll dig into the “how” for both increasing conversion rates and stage velocity. When the boss asks you how to fix it, you need to be ready with the answers!

Sales Thinks Your Leads Stink (Part 1) Because they Really do? And yes, you can fix that!

noreply@blogger.com (Anonymous) — Mon, 21 Jul 2014 12:51:00 +0000

In the ongoing battle between Sales and Marketing, Leads are often the major casualties. Marketing claims Sales doesn’t follow up on its Leads and Sales claims Marketing only sends over garbage not worth any follow up.

Who’s right?

Over the next few weeks, we’re going to dig into some statistics provided by Sirius Decisions and ask the simple question, “Why?” Here is the data:

20% of Leads are followed up by Sales

80% of Leads are never followed up by Sales

Conversely,

20% of those same Leads never purchase anything

80% of those same leads buy within 24 months (usually from somebody else) – if they are nurtured.

That’s a big IF!
The finger pointing begins and our ongoing battle rages. Is Sales correct? Let’s look at the possibility Sales is correct, and assume for a moment our “leads” are really not sales-ready. Identifying the problem is the first step to fixing it. There’s a straightforward fix, and you can implement it in your Demand Center in a matter of weeks.

Step 1: Get on the same page
You absolutely must work with Sales to determine what will be considered a sales-ready Lead. You cannot do this on your own because, in order for this process to work, Sales must agree on the definition. Marketing cannot define it for Sales, so collaboration is essential. However, that agreement must be stated in objective, quantifiable terms, not just the subjective “sniff test” (which actually doesn’t stand up to its own sniff test). What should those objective characteristics look like, given your sales organization is unique?

These objective characteristics should be broken into two categories: Profile and Behavior. For B2B marketers, Profile is the combination of demographic and firmagraphic characteristics of the ideal prospect, such as company size, title and department. For B2C, Profile will consist entirely of the demographics of the individual. Behavior is the digital body language expressed in online buying behavior. Has the prospect visited certain web pages, downloaded something or engaged in click-to-chat?

Once Sales and Marketing have agreed to the Profile and Behaviors that comprise an ideal Lead, you can move on to Step 2.

Step 2: Put a ruler on your Lead

Simply stated, how will you measure your objective criteria? Again, Sirius Decisions has created a model you can easily adapt to your criteria. Its co-dynamic model assigns values to both Profile and Behavior characteristics to create a score you can use to evaluate the sales readiness of a Lead.

I also recommend adopting the Sirius Decisions Waterfall terminology for describing “Leads.” If everything is a Lead, then nothing is a Lead. By specifically describing a sales-ready Lead by a different name that every other “Lead,” you provide clarity in your communications to the Sales team. Once you’ve defined your measurement system and labeled your sales-ready Leads accordingly, you can move to Step 3.

Step 3: Act on this information

Some data points are actionable and others are not. For example, there isn’t a lot you can do to get your prospect promoted from Manager to Vice President. However, you can create content designed specifically for your Manager to pass on to his superiors, thereby creating the potential for additional Contacts entering your system. This is called an Audience Acquisition Nurture. There’s that word: Nurture! Well-designed Nurture programs have very specific goals, and the tactics and content should be designed to meet those goals.

Nurtures are NOT about sending repetitive sales-oriented content out to large, untargeted groups of prospects. That strategy does not work, and I have a very specific name for them: opt-out campaigns. Because that’s what they do, get more people to unsubscribe from your communications than respond to them.

These three steps will effectively eliminate the “Your Lead Stink!” argument from Sales. How can Salespeople complain about Leads sent to them exactly as they requested? This is where the objective criteria and measurement comes into play. If they ask for VP and above in IT who have downloaded trial software, and that’s what you send them, the question then becomes why did Sales agree to that definition of “sales-ready?”

Notes:

You must identify the problem before you can fix it.

You must agree with sales on the definition of a “sales-ready” lead.

Your definition must be in quantifiable, objective terms.

You need to act on the information you have.

So, let’s say your Marketing team has agreed to a sales-ready definition, and there is still a problem with passing Leads to Sales that they still don’t believe are good enough. You have fallen victim to Cause A, the Sales argument that they are not receiving enough Lead volume. Like any other problem, Cause A can be fixed. Next week, I’ll tell you how.

Top Ten Demand Generation FAILS (Part 10) The Missing Link!

noreply@blogger.com (Anonymous) — Mon, 14 Jul 2014 12:43:00 +0000

Last week we looked into the secrets to reporting, and we’ve got it properly lined up before we launch our campaign. We’re going to report on MQLs generated by territory for our new Wombat preventer SaaS software. We’ll need to consider both outbound sources and inbound sources from media, such as Wombat Weekly and The Wombat Report. Just one problem: we don’t have Australian contacts in our database, not to mention critical opt-in data. And the only market for Wombat Preventers in is Australia.

Incomplete and incorrect data account for many, if not most, of the problems marketers have automating campaigns. We’ve mentioned before that data is one of the critical interdependencies required in the demand gen process. Data is the fuel that helps us make critical decisions. Bad data equals bad decisions.

Over the years, I’ve seen a lot of databases and, as you can guess, in 100% of the cases they contained significant levels of incomplete and incorrect data. The best I’ve ever seen contained 45% incorrect or incomplete records. You don’t want to hear the worst. Having said that, also in 100% of the cases, we were able to identify the problems and make significant improvements to the data. How? Let’s look at some things you can do to improve your data quality starting today.

Identify your requirements.
Where have we heard that before? Right, everywhere! Without an objective, there isn’t any way to know whether or not your data is right, wrong, or incomplete. How do you intend to use your marketing data? Make a list in the form of questions you need to pose to your database, and include all the decisions you will need to make. This list will include questions like:

What is the Contact’s vertical market?

Where is the Contact located?

Is the Contact a current customer?

How many employees in the Contact’s company?

These segmentation questions help you form the basis to understand what information needs to be accurately recorded in a Contact’s record in order to extract these answers.

What decision will I make based on this information?
This is a great way to determine how you need to record field-level information, often referred to as field standardization. There is no universal answer to this question, because every organization uses unique rules in their business. You will need to determine this in relation to every question posed in the requirements section above. Let’s look at a pretty universal requirement, “Where is the Contact located?”

This is almost always (if not, you need to consider why not) composed of several fields used in conjunction with each other, such as Address, City, State and Zip. Some businesses also use telephone area code to determine physical location. Your database may use different field names, but they are going to be similar. What decision will you make based on this information?

Are you determining sales territories for lead routing? Do you execute location-based marketing programs? Do you sell different products or services in different geographies? Are you a global marketing organization and need to consider email compliance in various countries? Does your marketing message need to be localized to consider different cultural implications?

The answers to these questions can range from very simple to extremely complex, depending on how the decisions intersect. In many cases, you will be making multiple decisions based on location and, if so, do these decisions have conflicting data requirements? For instance, are your sales territories (lead routing) divided by area codes while your market localization is divided by metropolitan area?

Where are the holes?

Now that we know what decisions we need to make based on our data, we can begin to identify the holes. Those holes always manifest in on of two ways: incorrect data or incomplete data. In our example above, we need to understand major metropolitan areas so we can create location-based marketing messages. Perhaps we have affiliate marketing programs with the local sports teams. If so, how does our system know that St. Charles is a suburb of St. Louis? Do we need a zip code lookup table, or do we need a field with a specific MMA value to determine our target market? In this case, we need to add a missing data element to make up for the incomplete data preventing us from making a decision.

Our use case also requires us to route leads by area code, because that’s the way our sales territories are divided. Since we know from previous {Demand Gen Brief} posts our data degrades at about 25% per year, our phone numbers can go bad at the same rate. People move, change jobs and retire all the time, so we need to keep our data fresh, so your sales reps don’t follow up on a hot lead only to find out John doesn’t work in that department any more. (Cue the snotty email from your sales rep.)

Data governance and regular hygiene are the answer here. Whether it is in the form of data plugins that constantly update your database, or in the form of quarterly refresh imports, your data needs a regular cleansing so it doesn’t start smelling like last week’s garbage.

To take this particular use case a step further, how will you act on the area code data? Does your MAP platform have the ability to use part of a field to perform programmatic decision steps? Can it use CONTAINS or STARTS WITH as operators in decision blocks? If not, you may need to consider how to extract area code into a separate field that is actionable in your system!

Data is the missing link most often overlooked when building a demand gen strategy. Don’t make the mistake of not designing your database to very specifically answer the critical questions you outlined above. If not, you may be relegated to considering specious Bigfoot sightings to find your Demand Gen missing link!

Notes:

You can’t properly design and build your database without clear requirements.

Be specific when asking yourself, “What decisions will I make based on this data?”

Find the two holes in your data: incomplete and incorrect data.

Don’t let this happen to you! We’ve now reviewed the Top Ten Demand Generation FAILS, and I hope I’ve presented actionable solutions to those fails. Next week, we’re going to switch gears and look at why Sales thinks your “qualified Leads” stink. Do they? Really?

Top Ten Demand Generation FAILS (Part 9) Ex Post Facto Reporting!

noreply@blogger.com (Anonymous) — Mon, 07 Jul 2014 13:05:00 +0000

Here’s the situation. Your Demand Gen team has been asked to create an email campaign for a new product announcement, Product X. This campaign includes several emails, product data sheets and a complete microsite with multiple links to assets. Being the great demand gen professional you are, you provide a checklist of metrics for reporting and ask your product manager stakeholder if these campaign reports are required and if any other reports might be needed.

Clicks from emails to microsite? Check.

Clicks from microsite to form? Check.

Form completion and abandonment? Check.

Campaign-generated MQLs? Check.

Anything else? No, that will do it.

Geography, named account clicks, other segmentation reports? No, what you said is perfect.

So you create, receive approval, launch and complete your campaign exactly as requested. Two months after the campaign concludes, the very same product manger fires off an excited email proclaiming the VP of Sales needs a report on the number of Product X named account respondents from Vermont for a meeting in 30 minutes. After wasting 10 minutes digging the document out of the archives, you send back the written campaign brief indicating the report requirements, which specifically excluded both geography and named accounts.

But the VP of SALES needs it NOW!

I don’t’ care if the Masters of the Universe and Elvis Presley want it, the data doesn’t exist and that report can’t be generated.

Well, you already know the rest of the story. The product manager fires off angry emails to the VP of Sales, CC-ing the VP of Marketing, the COO and Oprah, for good measure, indicating what a buffoon you are and how you could not produce a “simple” report. This is a classic example of Demand Gen Fail number 9: The Ex Post Facto Report (reporting retroactively).

You will be vindicated in the end, but damage has been done and a massive amount of your valuable time has been wasted defending your perfectly executed campaign. How can you prevent these situations? Three steps will dramatically help.

Review the written process
In a previous edition of {Demand Gen Brief}, Top Ten Demand Generation FAILS (Part 4) Where is the Menu?, we talked about formal process. IN that edition, our “menu” was the analog to the various parts of our process, including the order in which those tasks should be completed. Reporting is a key consideration for every campaign, and the metrics of success must be captured if success is to be measured. As a part of the campaign brief (or whatever you call the campaign design document), the elements of campaign success should be clearly outlined. Having the key stakeholder answer these three questions can capture those:

1. What will determine the success or failure of this campaign? This should be an open-ended question. The stakeholder needs to document, in his or her own words, what those elements are. It should be in the form of X units of Y by when.

2. What are the subdivisions of those success metrics? These categories will be the ways you can subdivide the whole of Y in the success equation. For example, if Y is expressed as MQLs, are those MQLs of a specific size, location, vertical or product line? How many ways does this need to be sliced and diced so that all stakeholders are represented?

3. Are these report formats sufficient? This is a yes or no question. You should present examples of the reports representing the success metrics, and make sure the stakeholder understands what reports will look like. Never ask an open-ended question around report format, because you won’t be able to produce the magic dashboard that transforms mashups into clickable charts that perform “deep dives” into the thought patterns motivating buyers in Croatia, sorted by three levels of stakeholders breakfast cereal preference. This yes or no also allows you to respond to such requests before the fact (pre factum), eliminating surprises.

Get a signature
Sounds simple, doesn’t it? You have reached an agreement to deliver a specific product at a specific time, just like any other contract. So, get a signature, indicating agreement between the two parties – in this case, the Demand Center and the requesting stakeholder – defining the terms of the agreement. Reporting is one of those terms. No, signature? No campaign. If this were a contract to sell your house, would you proceed without the buyer’s signature? A signature indicates a commitment to the terms of the campaign. Ambiguity hurts both parties, so eliminate it as much as possible.

Broadcast your methodology

Let everyone know how your Demand Center operates. You act as an internal agency, so run your operations in the same way. In the example above, the VP of Sales would have known that there was a previous commitment to deliver specific reporting, so the questions would have been directed at the Product Manager instead of you. (VP to Product Manger, “You asked for reporting by geography and named accounts, right?”) It becomes very clear very quickly where the broken link was.

Don’t let your lack of project management certification of experience inhibit you from instituting basic project management in your demand center organization. Even basic management will reduce inconsistency, improve timeliness and reduce errors. Any of these improvements will likely reduce the #1 complaint!

Notes:

The right time to determine necessary campaign reporting before the campaign is designed.

Review the process with requesting stakeholders every time. It will get shorter and easier as stakeholders get familiar with the process, but the review is necessary to proper understanding.

Treat the process like an external agreement – complete with all the details necessary to understand that a campaign – including reporting - has been completed according to the agreed-upon specifications.

We now understand what reports are going to be required before we’ve designed the campaign. Fantastic! We’re going to report on MQLs generated by territory for our new Wombat preventer SaaS software. We’ll need to consider both outbound sources and inbound sources from media, such as Wombat Weekly and The Wombat Report. Just one problem: We don’t have Australian contacts in our database, not to mention critical opt-in data. And there’s no market for Wombat preventers in North America. Missing data? This leads to Demand Gen FAIL number 10: The Missing Link!

The Number One Complaint! Top Ten Demand Generation FAILS (Part 8)

noreply@blogger.com (Anonymous) — Mon, 30 Jun 2014 13:15:00 +0000

Our modern word project derives from the Latin projectum which means “to throw something forward.” Sometimes that gets actualized as “throwing something over the fence.” Which does not really hold to the original meaning of the word.

More often than not, when projects do not get completed on time, on budget and of the expected quality, we can trace the root cause back to a deliverable that got thrown over the fence, usually too little, too late. Copy was a week late. Copy was a week late and full of errors and had to be re-written. Creative left out a critical CTA. Somebody forgot to run the finished document past legal. You probably have your own “favorite.”

While the components are all different, the root cause is consistent: failure to deliver components on time and to specifications. As a demand gen practitioner, you are at the end of the line, counting on campaign components delivered on time and to specifications. Your job requires the assembly of these “finished” parts into the executable campaign, ready for public consumption. In {Demand Gen Brief} we have often referred to demand gen as a “marketing factory” and this makes a great analogy. If you were the automobile final assembly plant, putting together all of the pieces built elsewhere and delivered to your plant, you would have a 100% expectation that these delivered parts would be built to spec, and be there when you needed them. Imagine how well your assembly line would execute if the engine delivery showed up a week late, or if the seats arrived without upholstery. Would you be expected to just “bolt it all together” and ship it out? I can only wish that were a rhetorical question.

We understand the problem (only too well, I suspect). Fortunately, the solution is really pretty straightforward: formal project management. And by “project management” I mean a systematic method for managing projects, not yet another software tool you need to buy and learn. The complexity of your project management (PM) system should reflect the complexity of your campaign execution process. The more resources, disciplines and project components required to build the campaign assets, the more complex your project management needs to be. There are definitely a few essentials any formal PM system needs to be successful.

Timeline
Everyone involved in the project needs to understand the timeline. In virtually every case, the major timeline needs to be broken down into component timelines. Start with campaign deployment date and work backwards. To understand the individual task timelines, start asking questions to the responsible stakeholders. These questions apply to every component task, and will help you determine how to stack up your tasks into a complete timeline.

1. How long does the task take to complete?

2. What has to be completed before you can start this task (dependency)?

3. What external resources do you need to accomplish this task?

4. Where does your finished task product go when you are complete?

5. How will you transmit the completed work product?

A few tips you will want to apply here: start building your timelines in number of days, not pinned to calendar dates. You will want those tasks in both number of days (which reflects backlog) and number of hours (which represents the actual work effort required). These will come in handy in the future when you want to see how long it took to actually complete each task compared to the estimated time. Understanding these will help you better estimate in the future, and may help prioritize those backlogs!

Responsibilities
Everyone assumes they know who is responsible for what, but on those occasions where there is ambiguity around task responsibility, it is a recipe for disaster. Put a name or department name on every single task on your timeline. Make sure the responsible party or department head is aware of that responsibility. In addition, responsible parties need to understand any downstream dependencies, so the effects of on-time delivery are completely understood. The time to discuss responsibility is prior to beginning the project, not when tasks are due.

Specifications and Standards

This is another area where assumptions can quickly run a project off the rails. Make sure every responsible party understands what his or her deliverable is. In most cases, there should be standards or specifications for the deliverable. Those standards can be very simple, such as:

Email copy will be delivered in a Word document of no more than 200 words in length. All copy will be free of errors, grammatically correct and all external references must be validated. A double line feed will indicate paragraph breaks. Any links from within the copy will be highlighted by blue text and underlined. All link URLs must be fully qualified. All copy must be approved by legal prior to submission. Include the words “FINAL COPY” in the header of the document in 24 pt. RED font.

This single paragraph leaves little to the imagination about what final, submitted copy needs to look like.

Kickoff Meeting
While nobody wants to attend yet another meeting, project kickoff meetings will prove to be one of the most valuable meetings you will have on your calendar. As you have more of these, they will become very efficient and stakeholders will come more and more prepared to answer your questions and establish timelines. To make these meetings effective, you need to properly prepare, which will include some level of project breakdown. Otherwise, you won’t know which stakeholders to invite, and nothing stalls a kickoff meeting like, “Where’s Sally? She has to provide the copy for the Purple Chrome Widgets emails.” You should also include your project sponsor at this meeting. If a critical obstacle is encountered in this meeting, the sponsor needs to be aware and, if possible, provide direction on potential solutions. Your kickoff meeting agenda will vary, but here’s a good start.

1. Project definition, stated objectives and success metrics

2. Committed deadlines (this project deploys when?)

3. Defined component parts (12 email nurture program with program logic)

4. Stakeholder weigh-in on the five timeline questions.

5. Timeline conflict resolution

6. Commitments from stakeholders (everyone leaves committed to the timeline)

While this blog is not intended to be a comprehensive thesis on project management, or how to implement project management in your demand center organization, I hope it give you a good start in that direction. There are a number of great PM resources available online, such as:

www.projectmanagement.com

www.pmi.org

www.projectsatwork.com

Notes:

Consistently ask the five timeline questions when building a project plan.

Make sure everyone understands who is responsible for what.

Specifications and standards reduce errors and improve timely delivery.

Project kickoff meetings will save you time and headache!

Now that you’ve got your project management ducks in a row, and are executing those campaigns efficiently and effectively, you know the next question is coming. How did my campaign do? Do at what? Opens? Clicks? Dancing the jig? The time to understand reporting and metrics requirements is before the Campaign is designed. Not after the data is collected and is missing the three critical metrics you needed to measure. This leads to Demand Gen FAIL number 8: Ex Post Facto Reporting!

Top Ten Demand Generation FAILS (Part 7) Testing One, Two, Three!

noreply@blogger.com (Anonymous) — Mon, 23 Jun 2014 11:53:00 +0000

We like to associate the term “rocket scientist” with really smart people who accomplish amazing things. But without well-executed QA, even rocket scientists can make really dumb mistakes. Like with the Mars Climate Orbiter in 1998.

Due to a miscalculation in payload distribution and a mismatched measurement system between different engineering groups, the thrusters produced more than 4x the necessary thrust. This resulted in a $320MM trash heap orbiting Mars (or so we think – nobody really know). My point? If NASA rocket scientists need active Quality Assurance, so does your Demand Center.

First, let’s define Quality Assurance (QA). Without a clear definition, we will all have a slightly different view of the subject. According to the American Society for Quality (ASQ), Quality Assurance is defined as: The planned and systematic activities implemented in a quality system so that quality requirements for a product or service will be fulfilled. Now that we understand the definition, let’s look at some hallmarks of good QA in a Demand Center organization.

Hallmark #1: Culture of Quality
Is quality appreciated and held in high regard throughout your organization? If so, many of the hallmarks below will seem second nature. A culture of quality tends to permeate all departments within an organization, and affects the output of everything produced. “Good enough” is replaced by “Does it meet [insert your company name here] standards.” Do you immediately, and without question, re-work or reject anything that does not meet up to these standards? If so, you have a culture of quality. If you respect time or price over quality, you likely do not have a culture of quality.

Hallmark #2: Quality is visible everywhere all the time
Examples of quality work are on display. Awards are on display. Your co-workers talk about quality and it is the first question asked when a new idea is discussed. If your new ideas are initially met with “how fast” or “how cheaply” can the new idea be produced, you likely do not have a culture of quality. (Note: Even in a culture of quality, speed and price are important subjects, but they tend to NOT be the highest priority and are not the first question asked.)

Hallmark #3: There are defined standards and processes for quality
Notice this did not say “defined standards and processes for quality assurance.” If we go back to our definition above, quality assurance is not just a department or a check tacked on to the end of a project. That is a quality control step. Quality assurance is baked into the entire process, making sure that quality is produced and maintained in the entire production process. Whether it is a Rolls Royce engine or a six-touch nurture campaign, quality needs to be baked into the entire process to ensure that the quality control step is merely an affirmation of the quality already built into the end product. If you don’t have defined processes and standards or QA is a step in the process, you likely do not have a culture of quality.

Hallmark #4: Senior management is actively involved in quality
Quality is not so much dictated as it is lived. If senior management gives lip service to quality in town hall meetings and weekly newsletters, but every question concerning development or manufacturing concerns time or money, you definitely do not have a culture of quality.

Let’s view this from the perspective of a well-known, high-quality brand, like Rolls Royce. Imagine the meeting where engineers have an idea for a new, fuel-efficient engine. Does the meeting start with “How cheaply can we build it?” Or does it begin with, “Will this engine live up to the standards of a Rolls Royce?”

Key to delivering consistently high-quality programs, content and delivery mechanisms is creating a culture and process that promotes quality. This may force pushing back on internal clients when they fail to meet deadlines – one of the most difficult process failures to navigate. But failure to build quality into every step of your production process leads to Demand Gen FAIL number 7: Testing, One, Two, Three.

Notes:

Quality Assurance is not a department or the final step in your delivery process.

Hallmark #1 of a high quality Demand Center is a pervasive culture of quality.

Speaking of client failure to deliver project components on time, in next week’s edition of {Demand Gen Brief} we will dig into that issue. It is by far the most common complaint I hear from demand centers concerning production timelines, and we’ll look into ways to avoid that situation in Demand Gen FAIL number 8: The Number One Complaint!

Is innovation killing innovation?

noreply@blogger.com (Anonymous) — Wed, 18 Jun 2014 20:53:00 +0000

There are a million blogs, posts and comments about innovation nowadays. In fact, it seems innovation has become an end in itself - innovation for the sake of innovation. But is that a good thing, or is "innovation" actually killing innovation?

In the quest to find the next disruptive game changer, are we innovating things that require no innovation? Like a talking refrigerator? My refrigerator already has an LED display panel that tells me when to change, and even when to order, a new filter. I can only imagine a pleasant dinner with my wife being interrupted by Siri demanding that I change the filter in my refrigerator. Not the kind of "innovation" I want.

Granted, there are some real innovators like Steve Jobs and Elon Musk who are really looking beyond the horizon at products nobody knows about today, but everyone will want tomorrow. There is a real and valid place for innovation, but if everything is "innovative" then nothing is really innovative.

In a bigger sense, are we chasing innovation at the expense of building well what we already build? Are we gambling the incremental changes that make our products and services a little better every day for the potential game-changer that will "revolutionize" the industry? How much revolutionizing do we actually need, versus evolution that build on already-solid foundations?

Don't get me wrong, I am 100% behind true innovation. I just hate to see artificial innovation replace solid, incremental gains that turn good products and services into great ones.

Top Ten Demand Generation FAILS (Part 6) Lumpy Pancake Batter

noreply@blogger.com (Anonymous) — Mon, 16 Jun 2014 12:15:00 +0000

As you anxiously take the first bite of your stack of hot buttermilk pancakes, dripping with maple syrup, you notice that dusty, dry sensation. The light, fluffy texture is interrupted by a giant glob of unmixed, uncooked flour, salt and baking powder. Lumpy pancake batter has ruined your breakfast.

What caused the lumps in the batter? Inconsistency. The inconsistency was caused by shortcutting the mixing process. Your grandma probably insisted you mix your batter 200 strokes. You probably use an electric mixer. But whether you are building your biceps with a wooden spoon or decorating your backsplash with an electric mixer, shortcut those 200 strokes and you get lumpy batter. And how many lumps does it take to put a ding in your otherwise glorious breakfast? That’s right, just one.

Let’s see how your Demand Center might suffer from lumpy batter. Even if you have properly assessed and documented your process and tailored an infrastructure and organization to work optimally in that process, shortcuts lead to lumps. We’ve all seen them and we’ve all experienced the outcome, either massive operational headaches or deployment mistakes. It’s a simple result of the Compound Delay Effect.

Under normal operations, a campaign deployment process looks something like this:

When early-stage tasks get delayed, the effect is compounded into later stages. Not only is there a delay in beginning the task itself, there are additional delays caused by re-scheduling. The task itself becomes larger because of the start/stop activities added to the mix. And resources are often shuffled to accommodate, meaning originally scheduled resources might not be available and other – and perhaps less ideal – resources are substituted. The compound result becomes distorted and looks more like this:

As any Project Manager will tell you, there are only two ways to combat this Compound Delay Effect: move the timeline or add more resources. Sometimes there are no additional resources and sometimes there is a dependency that prevents the useful addition of resources, even if they were available. Other times, the timeline is rigid and tied to an external event that cannot be moved (like a national trade show). Therein lies the great temptation to shortcut the process, leading to lumpy batter.

Nobody wants to shortcut the process. It is sometimes inevitable. When it becomes the norm, you have a real operational problem. Let’s look at a few outcomes, underlying causes and potential solutions.

1. We’re not quite sure whether or not the project is on schedule, but we think so.

Projects are consistently delivered behind schedule and every deadline is a mad rush to the finish, resembling a college “all-nighter” prior to a big test.

Build project management into your process. Yesterday. If you have in-house PM expertise, figure out how to utilize it. If you need to hire project managers, do it. They will help you build realistic project plans that include all the dependencies, hand-offs and all those tasks you never thought to include in a project plan.

2. QA is constantly seen as a “roadblock” to completion.

More than likely, QA is not the roadblock but, as the final step in the process, is receiving its assets too late to practically make deadlines.

QA should be considered an integral step in every process. As with any project plan, sufficient time and resources should be assigned. This plan should include time for the normal-case scenario, not the best-case, which is most often the plan. This means plan for mistakes and re-work. Because you know that is going to happen. If your assets were delivered mistake-free every time, you wouldn’t need QA at all.

3. Tasks keep falling through the cracks.

You consistently think you are nearing completion, only to find out some details (or critical component) has not been completed. After much shouting and finger-pointing, somebody bribes some resources with beer and pizza to work after-hours to cobble together something you can pass off as a deliverable.

This is not an operational plan. Assuming you started with a project plan listing all of the tasks and associated deliverables, somebody still needs to be paying attention. Project Managers are responsible for making sure tasks are completed on time and in the proper sequence, handoffs are made and deliverables are delivered.

According to dictionary.com, the primary definition of inconsistent is “Lacking in harmony between the different parts or elements; self-contradictory.” Like lumpy pancake batter. Or Demand Center processes that don’t always follow process.

Assuming these solutions sound preferable to the alternative, inconsistent chaos, we should begin to see a pattern in the solutions. Project management helps achieve the discipline necessary to keep our execution consistent with our defined process. Failure to consistently manage our projects leads to Demand Gen FAIL number 6: Lumpy Pancake Batter.

Notes:

Your defined Demand Center processes must be consistently followed in the execution of each and every Campaign. Even small variances can lead to poor execution and a negative user experience.

Formal Project Management will help you stay on course and consistently execute according to plan. Implement some form of project management into your system.

In next week’s edition, we will look at Demand Generation FAIL number 7: Testing, 1,2 3! How to make sure Quality Assurance is actually assuring quality.