Customer Relationship Management:

To get it right, add customer insight

Last time we talked about measuring how your commitment to CRM principles (IDIC) can be measured according to your investment in particular initiatives. Ideally these investments create value and delight for your members and other stakeholders, whom we call your customers.

This article rounds out our discussion of CRM with tactics for assessing how much your CRM initiative is driven by true customer insight. You’ll be able to assess what you’re measuring and why, so that you can see how your investments result in greater customer value and loyalty.

Defining some common terms

Most CRM initiatives depend on metrics that are easy to acquire. That doesn’t mean they provide any customer insight, however.

On the other hand, you may be able to use some of these metrics to improve your customer insight, provided you can correlate them to a hypothesis about what your customers want – individually and in segments.

Transaction and Analytics Processing

Transactions include membership purchases, phone calls, and journal article sales, for example. None of these numbers have inherent strategic or tactical information, which is best derived by establishing relationships among various other data sources, such as direct mail or email campaigns which may have driven membership purchases, or web discount specials which may have driven sales of journal articles. These related transactional and enterprise data sources let you analyze how tactics are helping you reach your goals. In the case of customer-centric behaviors, you would look for evidence that your well-defined customer groups each have participated in a high-value interaction. So you can’t have decent customer-centric analytics unless you capture customer value – as a metric – in your data sources.

Customer Profiling

Customer profiling is sorely misunderstood in the CRM and business analytics marketplace, mostly because people have in mind that they need to have 360-degree view of the customer lifecycle so they can upsell, cross-sell and “retire” customers to manage better for profit. The actual benefit of customer profiling is to understand and ideally predict what a given customer values about your organization’s offerings at a given time and in a given interaction environment. You have to collect key information about the customer over time to make their profile predictive.

Customer Profitability

This is the amount of revenue brought in directly by a customer, minus the costs of acquiring and maintaining the customer relationship. Obviously, well-targeted marketing and streamlined operations directly affect customer profitability.

Customer Value Analysis

CVA is the Holy Grail of customer analytics. It is based on metrics that identify why a customer or prospect makes a decision to buy (or to join!). This decision is driven by a perception of value, either in comparison to competitors, or in comparison to not buy or join. Some of these perceptions are driven purely by measurable quality divided by price but many of these perceptions are driven by a brand identity. In the world of small and medium enterprises, brands are built in part on its people and their integrity. Thus, “value” and “values” often blend in creating a perception of value. Nevertheless, in the customer eco-system, “values” often take a back seat to “value.”

Customer Loyalty Analysis

For purposes of creating a manageable customer-centric enterprise, we should avoid the “soft” sense of loyalty. Instead, you should measure loyalty by a blended metric: Total Lifetime Customer Value and the number of times a member or customer refers a prospect to you. You can use metrics such as RFM (recency, frequency and monetary value) to predict Total Lifetime Customer Value.

With these terms in mind, you can now fill out this assessment form.

Modified from Jay Curry,  http://www.customermarketing.com

What to Notice

This chart combines traditional CRM metrics with value metrics such as customer satisfaction, perceived value and customer loyalty. You’ll recall from prior articles (which we’ll recap in this article) that customer satisfaction tends to be a backward-looking metric, while perceived value helps you predict customers’ and prospects’ future choices. And as we’ve mentioned, loyalty is a blended metric of actual customer  purchase patterns (recency of purchase, frequency of purchase and monetary value of purchase) and the number of referrals a customer provides.

Thus, the systems and metrics you must put into place require you to look beyond transactions to gain insight into what drives customer choice.

If you can find meaningful correlations among transactional data, analytical data and customer value data, you will start to create a more strategic marketing operation.

Let’s recap some of the points we’ve made in prior articles, and look at some tools you can use.

Perceived Customer Value and User Group Analysis

What are we trying to optimize in Customer Relationship Management?

Customers? Relationships? Management data?

You’re actually trying to optimize the perceived value of as many of your customer and prospect member interactions as you can.

Most CRM metrics miss this point entirely, instead trying to optimize for transactional-based metrics like total purchase size, or frequency of purchases.

But how are these metrics often misused? Usually by driving sales processes – not marketing processes.

Isn’t it annoying when we get a phone call from some marketing rep who says, “According to our records, you recently bought something from us. We’d like to know if you’d like to buy something else?” Of course, they don’t say it quite like that. But the call was inspired by some computer printout that is predicting that you’ll buy again because you’ve bought in the recent past.

Notice that such metrics tell the organization nothing about the buyer’s state of mind. In short, if you’re looking for true customer insight, you can do a lot better than the metrics and analytics offered by the vast majority of CRM applications – including the big ones like PeopleSoft and Seibel.

So what’s the solution? Is there a way of getting insight into what your members and customers want – an insight that you can actually put into a database somewhere so you can track how well you’re doing in understanding what your stakeholders want?

And if you give your stakeholders what they want according to their profiles (either personal or segment), you’re must more resistant to the threats of competition – even if that competition is Google. (See my last article on why Google is a threat to your association.)

That, in a nutshell, is the definition of perceived customer value, and it’s the missing link in CRM. Add the two together and you’ll get a set of processes and technology that let you improve the perception of your value to a well-differentiated customer base you’ve identified and for whom you’ve customized your offerings.

PCV Works

A colleague of mine, C.J. Kirk of Gale Consulting, told me that he applied the principles of perceived customer value to one of the worst-performing paper divisions in the country. In two years it became the top-performing division and now is a cash cow for other divisions.

Perceived Customer Value (PCV) works. It lets you create value for your members, it helps define budgets, staffing and training, and gives you a specific metric against which you can measure your association’s new processes and technology.

Let’s rework the worksheet you first met in the previous article, but with a PCV slant.

Providing Perceived Customer Value 

When you’re done, circle the resource allocations that seem the most out of whack, based on the weighted preferences for each item.

Once you know how much your members value about your products and services, you can then determine the extent to which you fulfill that value. For example, if young audiologists give the idea of an annual meeting a value of 100 points, and yet they rank your actual delivery of that meeting at 80 points, you can see you’ve got some work to do.

If you add up how you score on all your products, services and interactions (which are, after all, part of the service you provide), then divide by cost, you have an index. This is your baseline metric that you’ll be working to improve.

Product and services

Let’s take a look first at a product. Consider the journal, Language, Speech, and Hearing Services in Schools, a popular publication of the American Speech Language Hearing Association (ASHA). This is probably not the only resource that educators and audiologists use as they develop their skills, programs and careers. In fact, it may not even be the most useful to them. But if ASHA were to do a normal customer satisfaction survey, it might find that LSHSS gets high ratings. Why? Because respondents would not comparing it to all the other resources available to them.

A perceived customer value survey is conceived differently. Let’s examine a comparison between customer value surveys and customer satisfaction surveys.

Contrasting Customer Satisfaction and Customer Value Paradigms

Source: Bradley T. Gale, "Satisfaction is not enough," Marketing News, 27 October 1997

Obviously, you need good data if you’re going to optimize the perceived value of your products, services and interactions. And perhaps just as obviously, customer satisfaction surveys only take you so far.

We’ve already identified another problem you face: If you survey members and prospects about anything at all, it should be about all the options in their environment and in the market that pertain to how they do their work, run their lives, deal with their colleagues, create positive outcomes for their patients, and so on. Your products and services have a function in the lives of your members, and you must see to what extent you are successfully fulfilling that function.

This means, for example, that you may benefit as much from a time and motion study as from a paper survey.

Let’s assume for the moment that you’ve surveyed your members and prospects using the PCV methodology and gotten good information about how they weight their preferences concerning products and services of the types you provide.

Look at the numbers. You may find that certain types of members (say, young audiologists in educational settings) have a distinct list of weighted preferences, whereas another group (say, young audiologists in graduate school) have the same list of preferences, but with different weightings.

What’s the consequence of this result? Remember, you want to manage for greater perceived value. Now you know how to do that with these two segments. In short, you can use the different PCV scores of your member and customer space to divide that space up into market segments. This is the Holy Grail of marketing: Choosing meaningful segments that let you create more perceived value over time.

PCV also helps you interact with your customers, because you can use a PCV score for a given customer segment as a guide to creating successful interactions. That is, if you measure how your customers want you to interact with them.

This is why I view interaction modes as a type of service. Do you want snail mail? E-mail? Phone calls? Faxes? Handshakes? How often? With what content? And if I’m a customer of yours, is it easy for me to change the way you interact with me? Where do I select those preferences?

The Use Case

This brings up the topic of identifying how you actually create value for your customer in their daily lives. If you could actually create a positive interaction with your customers each day, wouldn’t that be a great boost in your perceived value to your customers? Most associations are happy when their members visit the web site once a month.

There’s no hope for most associations to create this kind of daily relevance unless they actually study how each customer segment spends their day. This lets you identify interaction opportunities that can provide relevant, timely value.

You can do this using a methodology called Object Oriented Analysis, which is commonly notated in something called the Unified Markup Language. Geek talk aside, what this means is that it is possible to draw pictures and write descriptions of how you can vastly improve your relevance to member segments.

The first step is to map out how your member segments use products, services, information, skills, colleagues and tools in their normal day. This is called the use case. With use cases in hand, you can identify how to modify products and services so that you can insert your value right into the daily life of your members.

The beauty of use case design is that it provides a description that high-level managers can quickly grasp, while being rigorous enough to provide an outline for software design.

It’s an astonishingly powerful technique for building software systems, but it can be used just as well in describing all kinds of processes that build value, and that builds delight and customer loyalty. While we don’t have time to cover use case analysis today, I commend it for your further study.

Loyalty and Buy-In

You know much more about how that value is measured, how to determine which behaviors can increase that value, and how to focus your resources to create the most value you can, as quickly as you can.

All this revolves around CRM and perceived customer value.

But what about customer loyalty? Like CRM and customer value, loyalty is a buzzword we’d like to understand better. Wouldn’t it be great if your members were loyal?

In fact, there is no guarantee that a loyal customer will remain one. Not only is the customer eco-system at play, in which shifting contexts in the market change the standard against which you’re measured, but also the fact is that customers themselves change. A young audiologist becomes an old audiologist. That means their needs change. You can’t just segment your markets and forget to track the actual person as they move from segment to segment!

The best way to do this is to model the customer lifecycle for each segment, then get all your interactions with a customer into a system – track their use of your public pages, their members-only area activities, their phone calls, their letters … you’ll see a pattern. And once you’ve modeled how most members of a segment evolve into other segments, you’ll be able to anticipate, for each member, what they’ll need from you next.

That, of course, is good for loyalty.

But how will you measure that you’ve been successful at creating that loyalty?

The best answer I can give you in the short term is this: Even loyal members may not stay members. They may love what you do but bid you adieu for a hundred reasons.

So is that all? Can’t we optimize some metric or another that has something to do with loyalty?

Yes. First, you can approximately correlate the total lifetime customer value metric with loyalty. In fact, some companies wrongly assume that loyalty is total LCV. The reason this is wrong is because:

1. You can’t know total LCV until someone ceases to be a customer, at which point you may be looking at a person who has never been less loyal.

2. You may try to predict customer value based on how recently someone bought from you, how frequently they buy from you, or how much they’ve historically bought from you. Except that this may have less to do with loyalty than with necessity combined with deep pockets. Can’t poor folks be loyal, too? Sure they can.

3. Loyalty isn’t just what someone buys from you. There is another key behavior that you can measure that results from a customer’s state of mind. In short, this metric goes beyond total LCV transactional figures and gets into the mind of your customer. That metric: Referrals.

In fact, I have promoted the idea for a while now that loyalty is in fact a blended metric based on transactional information as well as measured referrals.

A not-very-useful article that appeared recently in the Harvard Business Review said that the most useful measurement of customer satisfaction is what people say about you when you’re not around.

It’s not a helpful comment because you cannot detect nor manage what people say when you’re not around. You’re stuck with other methods.

One of them is the referral engine: On your site, make sure everyone can forward a page to a colleague. Capture who actually forwards the page and you know who’s likely to be loyal.

Even better, identify the colleague by his or her e-mail address: If they’re not in your system as a member, your page has just been sent to a prospect. Now’s your chance to find out more about them using a PCV survey!

How else can you track referrals? Member-get-a-member programs are commonly used, with varying effectiveness. Simply asking how a new member heard of you may reveal the names of loyal members. You can also employ online social networks, which can allow you to track links between members and non-members. LinkedIn.com offers a partnership program you may find helpful.

Just make sure you capture all this referral data so that you identify whom those most loyal members are. And don’t be surprised if a few of them just pay their dues and are otherwise not generating a lot of revenue for you.

Summary

During this series, we’ve studied the basic CRM principles and its common metrics, outlined the shortcomings of CRM metrics, and suggested that perceived customer value overcomes most of these shortcomings.

In fact, PCV can help you budget, staff and focus your behaviors so that you create barriers to competition, higher margins and greater customer loyalty.

And when the day is done, you’ve done all this by asking the simplest of all questions:

Why does any given customer – or member, or prospect – decide they want to do business with us?

The good news is that you can answer the question and continue to track that answer across all segments and into the future. That’s something your association can bank on.

Paul K. Ward is a CRM, Branding and Customer Value Consultant www.Pkward.com.  Paul regularly meets with top Washington-area executives to discuss business best practices, and has recently inaugurated an advisory group for the American Society of Association Executives to assist in creating ASAE member value. He writes for ASAE Global Link, ASAE Association Management and Canada's The Canadian Association.