bulldog solutions putting the customer at the center of...

By Tim Wilson, Director of Business Process Analytics, Bulldog Solutions

Putting the Customer at the Center of Your Lead Scoring

Bulldog Solutions

www.bulldogsolutions.comLLM_LeadScore 01/29/2008© 2008 Bulldog Solutions, Inc.

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Bulldog Solutions Putting the Customer at the Center of Your Lead Scoring

Putting the Customer at the Center of Your Lead Scoring

ContentsThe Lead Marketing Optimization Revolution .............................................................................................2Successful Companies Must Be Customer-Centric ....................................................................................3Taking Your Lead Scoring to the Next Level ...............................................................................................4Start with Where You Are Today ...............................................................................................................5Two Dimensions: Profile Match and Engagement Level ..............................................................................6Scoring Without an Engagement Component ............................................................................................7Incorporating Engagement Level in a Single Lead Score ............................................................................8A More Realistic Look at the Profile Match and Engagement Level Dimensions ...........................................9 Score Accuracy .................................................................................................................................9 Score Weight ....................................................................................................................................9 From Theory to Reality .....................................................................................................................10A Lead Qualification Machine with Multiple Levers ..................................................................................11Engagement Scoring: Where to Start .....................................................................................................12Multidimensional Lead Scoring and Lead Nurturing .................................................................................13A Third Dimension: Position in the Buying Cycle ......................................................................................15Summary .............................................................................................................................................16

The Lead Marketing Optimization Revolution Old school lead-generating efforts often fail because Marketing and Sales initiatives are dependent on each other but disconnected. The image often associated with this relationship is a funnel. At the top of the funnel is Marketing, which finds and lures leads that are then pushed down to the lower portion of the funnel, which is Sales.

This funnel image is fundamentally flawed because it suggests a linear process. Rather, to succeed, the process must be ongoing and circular, like cogs that continue to rotate and engage each other. One cog is Marketing (tactics), and this must be in alignment with a Sales cog (engagement), both of which are driven by a third cog: the continuous process of lead marketing optimization.

Complaints from the Sales department often occur because Marketing prematurely hands over leads to Sales, which creates efficiency problems. First, some of the information that needs to be gathered could have been gathered automatically through a Marketing dialogue. Second, the lack of that information results in lead handoffs that have little or no near-term potential. Over time, these inefficiencies cause Sales representatives to lose trust in the value the Marketing department is providing. In the worst case, it results in the salesperson starting to cold call himself, which makes the level of inefficiency even greater.

This paper outlines a framework you can implement to help bridge that gap and optimize your demand generation: multidimensional lead scoring.

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Successful Companies Must Be Customer-Centric In The Customer Century: Lessons from World-Class Companies in Integrated Marketing and Communications, Anders Grondstedt writes:

Non customer centric thinking organizations are organized to efficiently produce and distribute goods. They relegate customer management and brand building to marketing and communication departments and agencies that sequester themselves in separate offices, isolated both from each other and from the customer, churning out advertising and other communications material to an information overloaded world. They make a virtue of outspending and outshouting the competition. Run more ads. Maximize the numbers of impressions. Get more ‘ink.’ They are frittering away millions of dollars in “marketing.”

Has your organization moved beyond Marketing and Sales silos? Does Sales have a regular voice in your lead-generation planning and lead-scoring processes? Does Marketing support Sales well beyond simply throwing leads at them? If so, then you have cleared a significant hurdle in the optimization of your lead marketing.

Now, is the way you measure the potential of future customers during your lead generation based on what the customer really needs, or is it based on what you think or want him to need? In an exchange on Brian Carroll’s blog, Jeffrey Eisenberg wrote, “I’ve seen lots of marketers sacrifice early- and middle-stage buyers because they had to show an immediate ROI on each campaign they ran. Who is accountable for all the potential business they lose by saying the wrong thing to the right people at the wrong time?”1 This is a different hurdle, and it is the one on which this paper primarily focuses.

Your prospects are deluged with information. They have virtually infinite sources for researching and identifying solutions. To successfully reach these potential buyers, you need to start by putting your future customers—whether they buy this month, next month or next year—at the beginning of every strategy and tactic that you pursue.

This paper lays out a framework for developing a customer-centric lead-scoring strategy.

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Taking Your Lead Scoring to the Next Level You score your leads and use that score to determine which leads are qualified and which ones are not. But, somehow, your Sales organization still complains that the leads you are giving them are not good leads. This is frustrating, because you did everything right:

• You involved Sales when determining what attributes to base your lead scoring on and how those attributes should be weighted.

• You looked at lead conversion data to determine the attributes of leads that turned into customers.

• You optimized your lead collection processes so that you were only asking leads to provide basic contact information and information that you would use to score them.

Overall, though, the feedback you are getting from Sales is that the leads are better … but still not very good.

The reason for this may very well be because your lead scoring is now geared entirely towards identifying one thing: leads who Sales would most like to talk to.

What is missing here is a critical dimension of your leads: How interested are they in talking to you? Is it possible that Sales now sees that the leads are better because the job title, company size, or whatever you are scoring exactly match the profile of who they want to talk to, but, when they try to contact the leads, very few of them respond?

This article describes how you can evolve from a one-dimensional lead score to a multidimensional lead-scoring system that assesses both the profile of the lead and his engagement—his willingness and interest in interacting with you. In a customer-centric organization, understanding your future customer’s needs, interest and engagement is what lead marketing is all about.

This does not have to be wildly complicated, and this additional dimension can be added without needing to conduct extensive training with your Sales organization—in fact, it can be largely transparent to them.

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Start with Where You Are Today If you are like most companies that have implemented lead scoring, then you are scoring based on a series of attributes. If some of those attributes are behavior-based, you are ahead of the game! But, at the end of the day, your scoring can be represented conceptually as shown in the following figure.

Your lead score is a number, and that number puts the lead somewhere on a spectrum of possible scores: the higher the score, the better the lead. Somewhere on that spectrum is a threshold, and every lead with a score that exceeds that threshold is a qualified lead (or a high lead, an “A” lead, a hot lead, etc.—terminology varies from company to company). To pick nits a little bit, the most descriptive term for these leads is “Marketing Qualified Lead,” or MQL. Even if Sales provided input into the scoring model, these are still leads that are being scored by Marketing processes. The distinction is important because, after a lead has been qualified by Marketing, there are two conversions of that lead before it becomes a true opportunity for Sales:

• Conversion from an MQL to a Sales Accepted Lead (SAL): These are leads that Marketing has qualified and passed to Sales, and on whom Sales is taking action.

• Conversion from an SAL to a Sales Qualified Lead (SQL): These are leads with whom Sales has successfully engaged in a meaningful dialogue; Sales has determined them to be truly qualified leads—there is the potential for revenue.

A conversion rate that Marketing and Sales both focus on is the overall conversion from an MQL to an SQL (or an “opportunity”). It is imperative to realize that there are two components of this conversion: the conversion from MQL to SAL, and the conversion from SAL to SQL:

• The target for the conversion from MQL to SAL should be greater than 90%.2 If it is not, then there is a clear misalignment between Marketing and Sales, because Sales is ignoring the leads that Marketing has qualified. In fact, according to SiriusDecisions, the average MQL to SAL conversion rate for companies is between 53% and 68%, which means that, “before the engine is really getting started, between one-third and one-half of marketing’s output is lost.”3 This paper only indirectly addresses issues with MQL to SAL conversion.

• The conversion you can expect from SAL to SQL will be lower—best-in-class organizations have a rate somewhere around 70%4, but that is a conversion rate you want and need to maximize. A common problem is that a large portion of MQLs never respond to attempts by Sales to contact them. If they do not respond, then they cannot convert to an SQL.5

Adding a second dimension to your lead score is geared towards improving the SAL to SQL conversion by factoring in the likelihood that a lead will actually respond to a call or e-mail from Sales.

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Two Dimensions: Profile Match and Engagement Level Two dimensions of the lead score are as follows:

• Profile Match: The company’s (Sales’s) interest in talking to the lead based on who they are

• Engagement Level: The lead’s interest in talking to your company about their needs.

These dimensions are measuring two fundamentally different attributes of the lead. (There is a third dimension—the lead’s position in the buying cycle—that is discussed at the end of this paper.)

When you score along both dimensions, your leads can be represented in a scatter plot as shown in Figure 1 below:

If your leads are truly this scattered—this chart is simply a random distribution—then there are opportunities for you to improve your audience acquisition so that more leads fall in the upper-right part of this diagram. This is an entirely different issue from multidimensional lead scoring, though, so, for the purpose of clearly illustrating the points in this paper, I am using an entirely random distribution.

The red circle above encompasses leads who are in what we call The Buying Zone. These are the leads who have a good balance between exhibiting the profile match of your target customers—the right industry, the right company size, the right job title, etc.—and an engagement level where they’re likely to answer a personal phone call or e-mail from Sales.

Figure 1: Scatter Plot: Random Distribution

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Scoring Without an Engagement ComponentIf you do not score based on engagement level, then the leads that get qualified are instead the following:

Without taking engagement into account, you are qualifying leads that simply are not Sales-ready. On one hand, Sales will likely not be able to get in touch with them, and they may be turned off by getting a Sales touch prematurely. On the other hand, you are not qualifying leads who likely will respond to Sales, in spite of the fact that the leads exhibit a pretty good profile.

DataGraphs_2DLeadScoring.xls

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Bulldog Solutions, Inc. CONFIDENTIAL Page 1 of 1

Lead Score Range

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Figure �: Lead Score Without Engagement Level

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Incorporating Engagement Level in a Single Lead ScoreOne way to incorporate engagement into your lead-qualification process is to include engagement factors in one overall score. Using the scenario described above, and then adding the engagement level score and the profile match score, we see now that the green leads in the following figure are the qualified leads (the red circle is The Buying Zone described earlier).

There is a very heavy overlap between the Buying Zone leads (those in the red circle) and those leads that a single score would identify as qualified (the green dots). At a conceptual level, this begs the question, “Aren’t we complicating things here a bit without getting dramatically different results?” The answer is “No” for two reasons:

• The diagram to this point is overly simplistic; if you added the engagement score to the profile score to get a single number (that could then place the lead on a one-dimensional lead spectrum as shown in the two-arrowed figure at the beginning of this paper), you would have a much more dramatic negative impact with regards to which leads become Marketing Qualified Leads.

• For the leads that are not MQLs, your lead nurturing will be much more effective at converting those non-MQLs to MQLs by using multiple dimensions in your scoring.

The first point is addressed in the following section. The second point, which is equally important, is discussed later under Multidimensional Lead Scoring and Lead Nurturing.



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A More Realistic Look at the Profile Match and Engagement Level DimensionsTo this point, we have treated the profile match score and engagement level score as being equal in two ways:

• Equally accurate with regards to assessing their respective dimensions

• Equally weighted when it comes to identifying MQLs

In reality, they are not equal on either count.

Score AccuracyYou can collect two types of data on your leads:

• Explicit data: Information that the lead has provided to you directly (e.g., by filling out a Web form) or that you have obtained from a third-party source such as D&B, Hoover’s, Experian, or some other service

• Implicit data: Information that you have gleaned based on what the lead has done and when (sometimes referred to as “behavioral data” or “activity data”)

Do not equate explicit data to the profile match score and implicit data to the engagement level score. For instance:

• An explicit request to be contacted by a Sales representative from the company is an indication of engagement level, as the request could be made by someone that is not at all a potential customer.

• A sustained visit to an area of your Web site that has technical specifications about a particular product is implicit data that tells you the lead is likely a technical buyer or end-user, which is information about his profile match (the visit also tells you something about his engagement level).

The reality is that much of your profile match scoring will be based on explicit data, while much of your engagement level score will be based on implicit data. Explicit data tends to be more accurate than implicit data, although neither type of data is ever completely accurate.

Therefore, as a rule, expect your profile score to be more accurate.

Score WeightNot only is the engagement level score less accurate, but, from a Sales perspective, it is less important. How many of your sales representatives would agree not to call a CxO who entered your system as a lead…just because that lead did not seem particularly engaged with the company?

So, theory and reality come into conflict. The best strategy here is to initially give the engagement level score less weight than the profile match score. The key word here is “initially,” which we will touch on later. This is easily accomplished using thresholds as described in the next section.

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From Theory to RealityTo illustrate the challenges that score accuracy and weight present, the figure below shows a two-dimensional grid with thresholds shown for each dimension.

The Buying Zone is the top right quadrant: leads whose scores identify them as having a good profile match and being highly engaged.

The problem with this figure is that the thresholds indicate a hard cutoff. How comfortable would you be with not giving Sales a shot at the leads circled in the following figure?



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Figure �: Lead Scores with Median Thresholds

Figure �: Lead Scores with Median Thresholds (Lost Leads)

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To set thresholds that will improve your qualification process, without drastically altering the volume of leads being passed to Sales as MQLs, lower the engagement score threshold while raising the profile score threshold, as illustrated below (the green leads are the leads that would have been qualified by simply adding the two scores together).

This approach eliminates leads who simply have not exhibited enough interest in the company (yet) to consider them Sales-ready. And, it inherently puts less weight on the engagement score.

A Lead Qualification Machine with Multiple LeversDo not expect (or try) to train Sales to understand and interpret two lead scores. If Sales currently looks at and interprets lead scores, then show them the profile match score only. Even better, though, is to start to shift to a simpler hand-off process by identifying leads as either Marketing Qualified Leads…or not. By making this shift, you will be in a position to have a lead qualification machine that gives you multiple levers to pull:

• Adjusting the engagement score threshold

• Adjusting the profile score threshold

• Adjusting the criteria used to develop the engagement score

• Adjusting the criteria used to develop the profile score

Each of these levers can be pulled independently. And, the impact of pulling each lever can be analyzed before taking action and/or experimented with through testing.



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Figure �: Lead Scores with Adjusted Thresholds

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Engagement Scoring: Where to StartWhen developing an engagement score, it is surprisingly simple to come up with a formula that is wildly complex. The best bet is to start simple and then gradually increase the complexity so that you can test whether each incremental increase in complexity provides sufficient value to make it worthwhile to retain.

You may already collect some level of engagement data:

• A “please contact me” form on your Web site: This attribute should typically max out the engagement score, as it is more of a trigger than a scoring component; but, to keep the process simple, incorporating it in the lead score often makes sense.

• Visits to your Web site: If you have a tool in place that can identify which of your leads visit your Web site and when, then you have a powerful indicator of lead engagement.

• Attendance at an event (online or offline) that you host: Attendance is a much stronger measure of engagement than simply registering for an event (although registration is an indication of engagement as well).

• Opens/clickthroughs on e-mails you send: Generally, this is noisy data and, even if it was not, it is not a particularly strong indication of engagement.

One relatively straightforward way to incorporate engagement is to look at the recency and frequency of inbound activity from the lead—visits to your Web site, registrations for white papers or online events, and so on. What data you have available in this area may vary, but there are numerous marketing automation, CRM and Web analytics tools on the market that provide this sort of data at the individual lead level.

Using recency and frequency in the scoring is really taking a page out of RFM (recency, frequency and monetary value) techniques for database segmentation. In this case, though, you are looking at recency and frequency of activity, rather than of purchases. Depending on your situation and what data you are using, you will need to do some experimentation to figure out exactly how to assign the recency and frequency values so that neither factor can, on its own, push a lead over the engagement score threshold.6

Do not get hung up on getting the scoring perfect. Once you have something in place, you can add sophistication (factors for which content was visited on the site, how many pages were viewed per visit, etc.) and test the results.

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Multidimensional Lead Scoring and Lead NurturingEarlier, I mentioned that the benefit to introducing multiple dimensions in your lead score is not just for identifying the right leads as being MQLs at a point in time. There is an equally significant benefit when it comes to how you nurture the leads that are not qualified.

Consider a scenario in which the profile match score and the engagement level score are simply added together to create a one-dimensional lead score. Returning to our two-dimensional diagram, the following figure illustrates a problem with that approach that we have not yet touched on.

The two circled leads would have an almost identical lead score, although they are clearly very different. Lead A is your dream profile, but there is little evidence that he even knows your company exists. Reaching out to him from Sales may actually turn him off. Lead B is wildly engaged with your company, but could not be a worse fit for you when it comes to being someone with whom Sales would want to engage.



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Figure �: One-Dimensional Lead Score

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Obviously, these are two extremes. But, neither lead should be abandoned. Both leads may lead to MQLs at some point in the future, so hopefully, you will nurture both of them. How you nurture them, though, should be very different, as shown in the following figure.

In the case of Lead A, the nurture program is trying to drive increased engagement. For these leads, you may want to make more enticing offers to get them to engage—offers that may be too expensive to offer to your entire database, but that you can afford to make to leads who have the right profile. The goal here is not to artificially get them to appear to be engaged. Rather, the goal is to provide a sufficiently enticing “hook” to grab Lead A’s attention enough that you can provide her with information that she finds valuable and that begins to position you as a trusted resource for information.

Not all of your Lead As will bite. That is a good thing. You want to find those that do and then, as they continue to engage with you through your Marketing channels, identify when they are sufficiently engaged to be passed to Sales. The benefit to Sales is not only that the lead will return their calls, but the lead will already be informed as to what the company has to offer, and Sales will quickly get to a much more targeted conversation.

Figure �: Nurturing Strategies

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In the case of Lead B, it is not possible to simply move the lead straight up into The Buying Zone. The profile is who the person is, and that is not something that you can dramatically influence. Rather, your nurturing of Lead B should be geared towards getting introduced to a lead who does have a more desirable profile—Lead C in the figure above (who may or may not already exist in your database). Lead B may be able to help you not only identify Lead C, but also to get Lead C engaged. These highly engaged/low- profile leads can be very valuable—they can be your entry into a company. Offers to them may be targeted passalong campaigns or access to information that can be used for selling your offer internally. These leads can also be used simply to gain intelligence about the company from an insider--whether they are already using your competitors’ products, whether your offering is a good fit for the company, and so on.

Leads who fall in the bottom left area of your scoring grid have the longest path to travel to get to The Buying Zone. Typically, you need to move them horizontally—get them more engaged—and then leverage your relationship with them to gain access to someone with a more ideal profile, who then needs to be engaged. These leads should be nurtured in some fashion, but it is the last group for whom to set up a nurturing campaign.

A Third Dimension: Position in the Buying Cycle There is a third dimension along which you can and should be assessing your leads: their position in the buying cycle. This is a critical dimension when it comes to being truly customer-centric. Even if you are not able to directly incorporate it in your lead-scoring process7, it can and should be incorporated into your lead marketing.

Companies are increasingly recognizing the need to shift from focusing on the sales cycle, which is centered around the company and its needs, to focusing on the buying cycle, which is centered around the customer’s needs. In both cases, the eventual customer moves through a process from complete unawareness of the company to placing an order. The key distinction, though, is that the buying cycle is how the customer moves through that process from her perspective. In your customer’s world, there are many variables that you simply cannot influence: what problem she actually needs to solve, the urgency of that need, what other solutions to the problem have already been tried or are currently in place, the company’s fiscal health, and so on. All of these factors can and will influence the timing of the customer’s purchase decision.

Truly great salespeople intuitively understand how to incorporate their prospects’ buying cycle into their sales process—they listen to their customers and respond based on what they hear. To develop effective content, to develop effective nurturing programs, and to effectively qualify leads, Marketing has to understand and incorporate consideration of the buying cycle in their activities.

Incorporating the buying cycle stage into your lead scoring can be complicated (being customer-centric, almost by definition, adds complexity in several areas, but it is absolutely worth tackling!). A fairly crude—and, unfortunately, inaccurate—way to determine this is by collecting it as explicit data, i.e., asking the lead questions such as the following:

• When do you expect to make a purchase?

• Do you have budget for this?

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Most of your leads understand why you are asking these sorts of questions and will alter their answers one way or the other based on whether they want to be contacted by your Sales organization or not.

A more effective way to determine where the lead is in his buying cycle is to evaluate what content he is consuming. Is he visiting a lot of content that is very education-oriented; that is, it describes basic concepts regarding the type of product you sell? In that situation, the lead may just be trying to understand whether or not he should even be considering moving away from the way he currently does things. On the other hand, if a lead is spending a lot of time on content that has detailed product descriptions and pricing, then he is likely to be further along in the buying cycle and looking to make a purchase in the near future.

In order to score on dimension, you have to have your content tagged as to what stage of the customer’s buying cycle it is most applicable. And, you need to put a system in place so that you do not jump to a conclusion as to the lead’s buying cycle position based on a single Web page visit.

In short, proceed with caution when incorporating a buying cycle dimension in your lead score. Depending on your company and your Sales organization, you may want or need to have Sales actively engaged with your leads as early in the buying cycle as possible. In that case, this dimension may not be so much a scoring component as it is information for Sales as to what sort of conversation they should start with when engaging the lead.

SummaryA key first step in improving the alignment between Marketing and Sales is to qualify leads based on a well-thought-out lead-scoring process. The scoring model should be developed in collaboration between Marketing and Sales, and it will improve the effectiveness of your Sales organization.

Once base-level scoring is in place, though, consider making the score multidimensional. Chances are, most of your one-dimensional scoring is based on the profile match of the lead, although there may be some measures of engagement level included as well. By isolating these different attributes of the lead—their profile match and their level of engagement—you will have a process that is more testable, more tunable and more effective.

Tim Wilson is director of Business Process Analytics at Bulldog Solutions, the lead-generation optimization and management company. Visit www.bulldogsolutions.com to learn more.

Notes1 http://blog.startwithalead.com/weblog/2007/04/on_b2b_demand_g.html2 SiriusDecisions Research Brief: Effective Lead Management: MQL to SQL3 ibid4 SiriusDecisions Research Brief: Effective Lead Management: SQL to SAL5 If Sales cannot get the leads they are trying to contact to return their calls or respond to their emails, then they will start to believe – rightly – that their time is better spent on other activities. At that point the MQL-to-SAL rate starts to erode.6 Alternatively, recency and frequency values can be multiplied together so that one magnifies/dampens the other. This is actually a better way to go, but it requires deeper thought on setting the values and may introduce unnecessary complexity in the implementation of the lead-scoring processes.7 In most cases, I recommend not tackling this dimension directly in your lead scoring process until you have profile and engagement scoring dimensions implemented and tuned.

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