Tag Archives: Customer State

Customer Modeling for Finance Folks

DataBase Marketing, Driller Q & A, Measuring Engagement, Newsletters,

Jim answers questions from fellow Drillers
(More questions with answers here, Work Overview here, Index of concepts here)

Q: My boss (VP of Phone Sales) is really looking to try out some new ideas and RFM is one he has latched onto. He actually has explored this concept for a few years but never acted upon it. Anyway, he just purchased your book and after finding that he did not have time to read it he gave it to me. My job was to read and understand at a high level and to lead a discussion with the marketing group to get them excited about the concept. I am a finance guy by trade so this concept was very interesting.

A: That’s funny, the people who really “get it” the most are Finance people and IT people, because my approach is very numbers driven.  Stuff either works or it doesn’t – did you make money or not?  Many marketing people seem to dislike the idea of accountability…..hmmm…

Q: Obviously I either did not do a good enough job explaining RFM, Latency Tripwires, etc. or they just are unwilling to have someone from their team tackle the concept. My feeling is they felt this is a sales tool. The question they always wanted answered was “Why did the customer behave the way they did? We find that out and make a sales call, not engage in ‘marketing air cover’ tactics.”

A: Not sure what you mean by this…in fact, depending on the value of the customer, a sales call might be exactly what is needed. If you have a formal “wall” between sales and marketing, usually the issue can be decided by “degree of pain” e.g. how painful will it be to lose the customer?  Generally, a personal call is more effective than Marketing but more costly, so you use those guns sparingly.

If you have a small number of very high value customers who look to be defecting then a sales call is triggered. If you have lots of medium to low value customers who look to be defecting, then a direct mail campaign is probably what you need, which is probably Marketing. Match the value of the effort to the value of the customer; this is how you get gigantic ROI’s (or since you are a finance guy, more accurately something like ROME’s – Return On Marketing Expense). The scoring approach to customer value is about allocating scarce resources to the highest and best use.

I think what Sales is saying is this: if you know a specific thing about a customer, we handle that “one to one” thing; Marketing does the “all customers” messaging. And this is precisely the point of customer models – they allow Marketing to do the “one to one” thing, as opposed to the “air cover” thing.

Q: So it has fallen upon me to develop a project plan and come up with some ideas to implement.  If we can not get marketing support we will run with it ourselves.

A: Good for you! A good old fashioned skunk works operation, I love that! And led by a Finance guy on top of that.  Bravo!

Q: I am now reading the book for a second time and I have a slight problem with how to best implement with our business. I can see how this concept could be used to radically change our sales channel, but I do not think I have that much pull.

A: Well, let’s take a look at it. Typically, and particularly since you are in Finance, what you do is look to prove out a high value concept, then share financial success up the chain. This builds momentum for the approach and gets people really interested in knowing more, which leads to taking concrete action.

So for example, find your very highest value potential defectors using either Recency or Latency. Then split them into two equal groups – test and control. Have sales call the people in the test group and find out what is causing the defection behavior, try to save the customer.

Then 90 or 180 days later, look at the number of test and control that stuck with the service. Subtract the control number from the test number, this is the “net” retained due to your calls. Multiply by value of the contracts, and you have sales due to your program.

Q: We are a subscription service in which customers pre-pay for the service they expect to use. Our sales (and I guess marketing to some extent) are responsible for driving customers to use their service throughout the year. Usually if a customer uses more than they committed to then they raise the commitment the following year. For us sales leads to higher revenues leads to higher sales, etc, one big circle. So I guess my question is this: Can RF scores be used for a pre-paid subscription service?

A: Sure, but perhaps not in the “classic” sense of transactional revenue. For many service biz, particularly subscription ones, you profile activity other than billing, since the billing tends to be static.? Sounds to me like what you want to profile is **usage** – the more Recently and Frequently a customer has used the service, the more likely they are to continue using it. I assume you are authenticating subscribers to the service on your web site, so this shouldn’t be a big deal.? Then your scores would rank customers by likelihood to “continue using the service” and their value.?

High value customers with falling or low likelihood (falling RF score) to continue using  the service get a sales call, mid to low value customers with low likelihood to continue get a direct mail piece from marketing.  Dramatic changes in score require the most urgent attention, in terms of allocating resources.

Q: As an FYI, we have customers who pay as they go and customers that sign a yearly commitment. Would it be best to segment the two groups individually for the RF model and Latency tripwires?

A:  Yes. Annual subscriptions and Pay As You Go are two fundamentally different behaviors and mindsets, so mixing them will confuse the scoring. You have a Long cycle (annual) and a Short cycle (PAYG) decision being made; both the models and the actions would be different. For example, PAYG will be a more sensitive model with action required more immediately. Also, these are probably low value customers so you’re talking about e-mail or direct mail.

And, your measurement cycle would be different. Taking the test example above, you would check for “net results” on PAYG probably at 60 days; annuals you would wait for renewal date unless the offer affected this date in some way.

Q:  We also have different size customers some spending more than $10K / year and some $1K, should we segment based upon dollar values as well since the more they committed to the higher their FM scores (you would expect)?

A:  You can make anything really complicated with segmentation if you want to! Just starting out, my answer is Segment in terms of message yes, but Segment in terms of scoring and triggering action, no.

Keep in mind the Current Value / Potential Value model; don’t confuse the two behavioral vectors and their meaning. Current Value – what they have paid so far – is about how valuable the customer is to the company and determines what action is taken. This is the “personal call” versus “send e-mail” part of the equation; the cost component.

The Potential Value (Recency, Latency) is about predicting the likelihood for future business, it’s about “when” to act. This is the risk of losing the business in the future.

So I would not segment by value in terms of predicting defection, because thelikelihood of losing the business is really unrelated to the Current Value of the customer.You can have High Value and Low Value customers with the same defection likelihood, whether “value” is measured as Sales, Page Views, Engagement, whatever. Value is largely independent of likelihood to defect. But once defection is predicted, you then segment between High Value and Low Value and take action based on the value of the customer or visitor segment.

The two primary rules of High ROI Customer Marketing are:

1. Don’t spend until you have to
2. When you spend, spend at the point of maximum impact

Current Value = What to do
Potential Value = When to do it

That’s why this approach is so much more profitable then dropping Marketing on a “batch and blast” calendar schedule (you called it “marketing air cover”). Right message, to the right person, at the right time.And itworks especially well online because Relevancy (right message, right time) is so important and switching costs are low.

Q: What kind of Marketing should we do?  Is there any other segmentation we should try?

A: Well, that’s a little tough without knowing more about the business, but there’s a good way for you to find out!

With a service, you hopefully know why people stop using it. To prepare for these campaigns from a Marketing perspective, find defected best customers (high value cancels) and look at why they stopped using it (or interview them if you don’t know, offer a free month or whatever to get them to talk to you). Create Sales / Marketing – pitches / materials / offersto address their issues.

Then when you see a client engaging in a defection pattern on usage (drop in RF score, Latency Tripwire), engage the appropriate response (Sales or Marketing) based on the value of the customer.

And sure, the more you segment your customer base, the better it works. You should start at the bottom, however. Don’t “out-think” the segmentation; let the data speak to you. Try something at a very basic level and look for the hands to be raised; this will tell you what works and put you on the right track for more complexity.

For example, let’s say (and I imagine it would be true) that SIC codes play a role in your sales and retention. Certain types of businesses are simply going to be more likely to realize value from the services. So you do a campaign (sales, marketing, or both) to *all* customers in a particular defection state and let the SIC data speak.

Let’s say for simplicity that you find if a PAYG subscriber doesn’t use the service for 10 days that’s a warning flag for defection. You prepare and drop the retention campaigns to any accounts that “trip” this trigger – right message, at the right time.

What you see when the data comes back is certain SIC codes had a very high response and “activation” and start using your database again, and others do not. The data has now spoken, told you which SIC’s it is worth spending time / money on.

Then you look at bit deeper, and find that within an SIC code that looks to be a “bad idea” overall, the results are pretty good as long as the offer is made by direct mail in the South.  So you keep this particular segment of the “direct mail” campaign and kill the rest of the marketing activity for that SIC code.

You can look for other segments by value, by region, by services subscribed to, by type of data they look up, whatever. As you subdivide segments, you will find new pockets of profitability. You could spend a LifeTime chasing down all the segments – I have never, ever finished this task on any particular engagement. In fact, clients call me years after they have stopped using my services to tell me they have discovered unique new segments that are extremely profitable.

I’m not saying you should?abandon traditional customer communications,the batch and blast that you do. What I am saying is there is a deeper, more Strategic Objective you can drive through either customization of current programs or by adding an additional layer -maybe cut back on a little of the blasting at the same time?

The basic idea is really no different than optimizing Campaigns – except you’re optimizing Customers by recognizing problems with individuals and offering solutions, instead of always being in their face asking for something – especially when the customer is already demonstrating to you there is a problem of some kind. A little “Is there something we’ve done wrong”? or “Can we help you use our product more efficiently?” or “Would you take a survey?” to specific customers could not hurt.

Sound like a good idea?

Jim

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Hitting the Wall

DataBase Marketing, Measuring Engagement, Web Analytics

Looks like Red Envelope is Hitting the Wall. What they need now is a Relationship Marketing Strategy based on understanding dis-engagement. It’s the only way to dig out of this.

They need higher Marketing Productivity.

Check out this statement:

“We hoped that our renewed creative statement would drive an up-tick in performance in fall and holiday, but unfortunately this was not the case” -CEO John Pound

Got some old schoolers there. That’s a “pray and spray”, offline Customer Marketing approach, not an interactive customer strategy. They have to understand why the behavior is different.

You know, the difference between Brand and Branding.

They have the data. But they didn’t do the analysis, because the effects of dis-enagagement were masked by new customer acquisition. They thought everything was just fine and changing creative could “give them an uptick”.

Not. I’m just guessing, but it seems to me this business model is a case where the Catalog – as they are implementing it – is only driving incremental business in very small segments, and is a loss overall.

In other words, a prime candidate for a Controlled Test to resolve this matter of catalog incrementality quickly by avoiding the “matchback” problem so common when one takes an old school approach to an “always on” interactive medium.

I’m not saying the catalog is a bad idea. I’m saying it matters more than most folks understand who you send it to and when.

So, have you ever shopped with Red Envelope? How was the experience? Did you purchase again from them? What’s your Net Promoter Score with respect to them (giggle).

More details on what Hitting the Wall is all about are here.

A Framework for Engagement – e-Mail Example

DataBase Marketing, Measuring Engagement, Web Analytics

Let’s take a specific example of what I was talking about in the last post in this series to show you what a Relationship Marketing Strategy looks like in action. I have stated, for example, in this interview, that email is both taking credit for sales that would have happened anyway and generating more sales than you think it is.

These statements are both accurate at the same time. When you use Control Groups to measure the incremental behavior generated by e-mail campaigns, what you find is both effects occur at the same time but each one happens with a completely different behavioral segment – Engaged versus dis-Engaging. Unfortunately, in most cases, the net effect is e-mail falsely takes credit for more sales than it doesn’t get credited with accurately, because the Potential Value (likelihood to buy) of the Engaged is far greater than that of the dis-Engaging.

Against a graph of Response by how long ago the last click in an e-mail occurred, these dual effects on the actual response rate of an e-mail drop versus control group look something like this (red line).

Click picture to enlarge:

On the left we have the highly Engaged, and moving to the right, the pattern of dis-Engagement. On the left, we have a much higher percentage of “would have bought anyway”, which decreases as we move to the right. The portion of the blue bars above the red line represent buying activity in the control group – they bought without receiving an e-mail.

As we move to the right, this effect decreases, until the blue bars are now below the red line  The space between the blue bar and the red line represents sales made because of your e-mail that were not tracked back to the e-mail drop. Often, this is a result of simply not tracking the “campaign tail” for long enough, which is difficult to do without using a Control Group to find the long-term lift.

The implication: for commerce, you should be sending a different message to these different behavioral segments depending on where they are in the LifeCycle if you want to maximize profit. In the segments with highest likelihood to buy, you should take it easy on the discounts; one way to optimize commerce profit across the entire engagement spectrum is to use a Discount Ladder.

For all other business models, it’s highly likely that you could benefit from the same approach, if you have clear value KPI’s and understand this dis-Engagement process.

Now, I am well aware the above sounds insane to offline retail folks. Most if not all of you lack the data to measure these effects, but that doesn’t mean they don’t exist. For the folks that do have the data, the day will come. Hey the web is interactive, the web is different, right? Well, yes it is, so why measure the effect of promotions like they do offline if you have a superior method of optimizing for profit?

When a visitor / customer is highly Engaged, they often generate visits or sales without needing any Marketing at all. That’s what the Relationship Marketing Strategy is all about – the Relationship drives the business. That’s why, for example, people have found that including a lot of relevant and customer-focused content in a commerce newsletter gets higher response rates than just sending people coupons. It’s why creating a new customer kit drives higher repeat purchase rates – it’s the Relationship building. And that’s why you will find (if you use Control Groups) that for the highly Engaged, your e-mail program is taking credit for sales it did not generate, and that if you are providing discounts to the highly Engaged, you are probably wasting money on them.

A portion of the Engaged segment would have bought anyway, and the fact that you dropped a coupon in their lap with e-mail is simply coincidence. Or, if you send a coupon every week on the same day, the customer simply waited for the coupon they knew they were going to get so they could make a discounted purchase they would have made anyway at full margin. That’s how e-mail takes credit for sales it does not generate, and anybody who is managing to ROI / profit should care deeply about this.

Now, if you’re a “share” thinker, this subsidy cost related to “would have bought anyway” doesn’t matter to you, because any sale the other guy didn’t make is a good sale. But last time I looked, you can’t put share in a bank account, and the logical extension of this share mindset is you can get 100% share by selling product below cost, so I have never understood it. If your directive is increasing gross sales, that’s pretty much the same thing – you get there by unproductive ad spending, which in the end is the same thing to the bottom line as selling product below cost.

By the way, I’m not saying the Engaged should receive no communications, but they should get a different kind of communications tailored to their behavioral state.

On the flip side, no matter what your directive, you should care about not getting credit for sales your e-mail generated. E-mail to another segment, those in the process of dis-Engaging, almost certainly generates sales you are not tracking and not crediting to e-mail. And that’s because the dis-Engaging are changing their behavior with the company for some reason. They are seeking alternate channels, for example. In other words, they are responding to your e-mail but they are not responding through your e-mail, they are not using whatever devices or links you give them in the e-mail but are still making a purchase because of the e-mail. Again, you don’t see this unless you use Control Groups.

A third segment, the dis-Engaged, does’t respond to your e-mails at all. And they’re not going to, because your company is now irrelevant to them. The company has not been tracking the dis-Engagement process so it didn’t take any specialized action to slow or stop the dis-Engagement. In fact, the company is probably just damaging their Brand by sending these folks any e-mail at all.

This is Relationship Marketing Strategy; it completely redefines how you communicate with customers based on where they are in the Engagement / dis-Engagement cycle. And it works amazingly well.  The bottom line is customers remain customers longer – this Strategy tends to extend the LifeCycle – with the result customers end up with higher LifeTime Value.

Are you surprised? You shouldn’t be. People talk about this incessantly on the web all the time, don’t they? Relevance? Customer centricity? Customer experience? Blah blah blah?

Then how come so few people are using a Relationship Marketing Strategy? How come so few are using Control Groups to measure the true net influence of e-mail? Why are people blasting out the same irrelevant message to all their customers once a week? A lot of talk and very little action, methinks. Perhaps you just needed a framework to put everything into perspective, a roadmap to getting it done?

Now, I realize many folks in the community don’t have the tools they need to measure dis-Engagement; typically only the high-end tools have metrics like Recency and Latency and even though Google Analytics tracks Recency, it isn’t easy to do much actionable segmentation for that metric in the tool.

There’s a very simple reason for this, if you think about it – it’s a lot harder to measure something that doesn’t happen than measure something that does happen. After all, servers are all about requests, they’re not really thinking about “did not request”, if you know what I mean. That job takes a database that’s remembering the last date a request was made forward in time, and calculating “did not request”. That capability is a lot more expensive, at least for now.

But, I hope the “tool problem” doesn’t mean the community will ignore the concept of dis-Engagement while screaming to the skies about how important Engagement is to measure. Those of you with access to a transactional database don’t have to wait for web analytics tools, you can profile customers for Engagement and the dis-Engagement process right in the transactional database with a simple query tool. And I hope you now have a Strategic framework to think about why dis-Engagement is so important, at least from a Marketing perspective, so when you get your hands on that high-end tool, you will know exactly what to do with it.

If you really take some time to think about the ramifications of the Relationship Marketing Strategy that Engagement is a Tactical part of, you just might come to believe that dis-Engagement is even more important to measure than Engagement.

To summarize this series, the idea of Engagement, and a lot of notions surrounding it – customer centricity, relevance, and customer experience – are concepts within a Marketing Strategy known as Relationship Marketing that tosses out calendar-based communications in favor of communications based on the customer’s relationship with the company.?The ability to do this depends on an understanding of the Customer LifeCycle, the results of each interaction between the customer and the company over time.? The LifeCycle?is tracked using various Engagement metrics, including dis-Engagement, which typically is the first sign?of a problem with the customer Relationship.

If your company is having trouble understanding why Engagement is important to measure, perhaps it’s because senior management lacks the context of the Customer LifeCycle for taking action and the strategy of Relationship Marketing as a game plan. Maybe you should send a link to the Wikipedia definition of Relationship Marketing to the CMO or CEO and ask, “Is this what you want? Because if you do want this, I know how to measure the success of it”.

Questions or comments on e-mail engagement and response?

Have you ever heard of the strategy called Relationship Marketing?