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Using Latency to Map the Customer LifeCycle

Let's say you look at average behavior across all customers, and end up with a "Latency Sequence" that looks something like following:

Time between 1st - 2nd event: 90 days
Time between 2nd - 3rd event: 60 days
Time between 3rd - 4th event: 30 days
Time between 4th - 5th event: 60 days
Time between 5th - 6th event: 90 days
Time between 6th - 7th event: 120 days
Time between 7th - 8th event: 150 days

What does this pattern say to you? Think about it.

I'll tell you what it says to me. First, as you probably realized, you are now starting to see something that looks like a "cycle," as in LifeCycle of the customer. It's a series of events you can graph with a line and make charts of. If you can measure it, you can try to manage it in a positive way, and determine the results of your efforts. Second, you now have a series of seven "trip wires" you can use as described above to more finely sift and screen behavior looking for deviations from the norm. If the average number of days between events for any single customer starts to exceed the average for all customers, a trip wire call for action is triggered on that customer. And third, somewhere around the 4th event, something significant happens to change customer behavior in a very noticeable way. The customer accelerates into the 4th event (the time between events gets shorter and shorter), and then begins to decelerate in terms of behavior (the time between events gets longer and longer). Depending on your business, this may be positive or negative.

How do you act on this information?

Regarding the Lifecycle and the trip wires, you could have a series of seven actions ready to take at any point in this LifeCycle where the customer deviates from average behavior. As long as the customer stays on track, save the money and take no action. But as soon as the customer misses or "rolls over" past one of these LifeCycle milestones, you know to pull the trigger on your action. If you follow this model, you will end up maximizing every cent of your budget and driving higher profits, because you don't spend unless you have to, and when you spend, it creates maximum impact. This is the recipe for High ROI customer management and marketing. Act only when you have to and always at the point of maximum impact.

Regarding the behavior change, if I was a retailer, this looks negative since the "ramp" in buying behavior reversed and went in the other direction. If I was running a pure service center, this may be a very desirable pattern; perhaps meaning the customer has "learned" the product and no longer needs as much service. It could be negative though, since opportunities to up-sell or cross-sell the customer are decreasing over time. It depends on your business. The important thing to recognize is this: there was a change in behavior, and you should try and determine how you might affect this change in a positive way. Reversals in the direction of a behavior like this are almost always significant turning points in the relationship with the customer.

Human behavior dynamics often take on seemingly "physical" properties. Inertia is one such property - an object in motion tends to remain in motion unless acted on by an outside force. This reversal in the direction of the customer "momentum" after the 4th event indicates there is something about your business - a process (or lack of a process), a product (or lack of a product), something - which causes the average customer to "slow down" and reverse their contact momentum. This reversal of momentum, fellow Driller, is evidence of a change in friction. Changes in friction can be positive or negative, depending on what activity you are measuring and the nature of your business and relationship with the customer.

In most business cases, more activity is better; you want more sales, more visits, more downloads, etc. In this business case, customers demonstrating a slowing in the rate of their activity means friction is rising; you need to find out why and do something about it. In some cases, primarily in service-oriented settings, less activity is better (think trouble calls). Under these circumstances, slowing activity can be viewed positively (through the eyes of the customer and business, fewer trouble calls is good) and this means friction is falling.

Let me say this another way to make sure you have the point: rising friction is always bad for the customer and the business because it indicates the likelihood to continue the relationship and potential value are both decreasing; falling friction is always good for the customer and the business because it indicates the likelihood to continue the relationship and potential value are both increasing. Whether a particular behavior is indicative of rising or falling friction depends on the business situation, as demonstrated with the case above.

The slowdown in activity at the 4th event indicates rising friction if you are a retailer; it may indicate falling friction if you are Help Desk and you actually help your users. On the other hand, if you know your Help Desk users are generally a frustrated bunch, a slowing of activity at the 4th event perhaps means they are simply giving up and friction is rising. Frequently in a service center or Help Desk environment, the "reason codes" for contacts help you understand whether a certain behavior indicates rising or falling friction; you might want to run your Latency calculations not on all calls, but just for specific reason codes to gain more insight. And if you are not collecting reason codes for each call, what are you waiting for? That piece of data is important!

If I am profiling retail activity, this Latency sequence looks negative, a slowing rate of purchase indicates an increase in friction. If I had very limited resources, given the seven possible promotional opportunities listed above, but looking for the absolutely highest ROI on a single promotional event, I would send a promotion to the customer immediately after the 4th purchase - and no sooner. I don't want to spend money on a promotion or by reducing my margin if I don't have to, so as long as the customer is accelerating, there is no reason to spend any money. But I would really like the ramp to continue past the 4th purchase, and any way I can bring that 5th purchase in closer to the 4th is going to affect my bottom line, and perhaps lengthen the ramp into the 5th or 6th purchase and beyond. If I had more money to spend on promotions, I would test each of the seven trip wire opportunities, and pursue only those with the highest ROI, probably using a separate and unique discount approach for each of the seven trip wire opportunities.

If I am profiling contacts in a service center, this behavior might be a good or bad thing, depending on the circumstances. If this pattern of slowing contacts indicates frustration on the part of the customer, as in the retail example, friction is rising and I want to act on the problem. If I up-sell and cross-sell, I would look to weight more of this activity early in the process knowing I am not going to get as many chances as the customer becomes less likely to call.

However, on a help desk, slowing of contact behavior could mean the customer no longer needs as much help. If this is the case, what I am observing in the behavior is actually a reduction in friction. The fact it takes 4 calls to educate the customer in the first place might not be acceptable, and I would look for ways to decrease the length of time it takes, reducing friction earlier in the cycle.

Success in any of the cases above creates incremental value with very little expense; you're not necessarily changing what you do, just when you do it - to match more closely with the customer LifeCycle. The point of profiling the behavior is to discover the most profitable time is to act.

Of course, you can begin to subdivide the customer base, just as we did in the hardware / software example above. The Latency Sequence may look quite different for hardware buyers relative to software buyers, and it will certainly be different by the type of campaign you used to attract the customer in the first place. For example, those of you working with pay-per-click optimization will find different keyword phrases generate visitors with different Latency Sequences; the time between 2nd and 3rd visit or purchase will be different and so your trip wires should reflect this to achieve full optimization of the Customer LifeCycle.

Once you are able to compare and contrast different customer LifeCycles by product, campaign, customer source, or by any other data point meaningful to your business, you will begin to paint a more complete picture of what parameters positively or negatively affect customer behavior. Once you understand the behavior, you can learn to profit from it.

Next Article: Recency: Predictive Marketing

This article is taken from the book Drilling Down: Turning Customer Data into Profits with a Spreadsheet. The first article in this series can be found here.

Jim Novo has nearly 20 years of experience using customer data to increase profits. He is co-author of The Guide to Web Analytics and author of Drilling Down:Turning Customer Data into Profits with a Spreadsheet. If you want more visitors to take action on your web site, try using the free conversion metrics calculator, downloadable here. If you need to sell more to customers while reducing marketing expenses, get the first nine chapters of the Drilling Down book free at http://www.drillingdownbook.com.
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