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Drilling Down Newsletter # 12 - September 2001Drilling Down - Turning Customer Loyalty
Site Will End Cash Rewards Program Borders'
E-Mail Promotions Hook Readers I hope we're now on the same page - the above tirade was prompted
by your flood of questions in response to the first
article in this series on Behavioral Marketing. Latency is one of the simplest of the "trip wire" metrics you can use. If you know the average amount of time between two customer activity events, you can set up systems to recognize when a customer trips the wire (behaves outside the norm) and activate a response. But what if you were to look at an entire series of Latencies? For example, the average number of days between the first and second purchases, the average number of days between the second and third purchases, third and fourth, fourth and fifth, etc. You don't have to use purchases, you could use contacts with customer service, visits to a web site, any behavior important to your business. What would that look like, and more importantly, what can it do for you? It would look like a snapshot of the customer LifeCycle, that's what it would look like. And what it can do for you is start you on the path to predicting customer behavior and increasing the value of your customer base. Let's say you look at average behavior across all customers, and end up with a "Latency Sequence" that looks something like this: 1st - 2nd event: 90 days 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 affect it in a positive way, and
determine the results of your efforts. Second, you now have a
series of seven "trip wires" to can use as described
in the previous article to more finely sift and screen behavior
looking for deviations from the norm. And third, somewhere
around the 3rd or 4th event, something significant happens to change
customer behavior in a very noticeable way. The customer
accelerates into the 4th event, then begins to decelerate in terms of
behavior. Depending on your business, this may be a positive or
negative event. 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 upsell or cross-sell the customer are decreasing over time. Depends
on your business. The important thing to recognize is there was
a change in behavior, and to 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. If I was a service center, the fact it takes 3 calls to educate the
customer might not be acceptable, and I would look for ways to
decrease the length of time it takes. If I upsell 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 time goes on
and the customer becomes more likely to defect. Success at
either of these actions can create incremental profits 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. That's what I tried to find out, by sending all these searchers to
the same page - my home page, which covered all three subjects in a
generic sense, and had prominent links to the same pages searchers
were sent to previously - Custom Landing pages written to match the
search term used. Note: The current Home Page is
different than the one used when this test was run. The
Home Page used in the test was similar to this page
with links to the Custom landing pages displayed prominently at the
top of the page. What does this mean? Can we reconcile the "bad" and
the "good" in terms of the behavioral marketing approach?
Well, sure. Two possibilities: 2. It's also likely the targeting of the Custom Landing page itself is causing shorter visits / higher abandonment. In other words, a visitor types in "Customer Loyalty", a pretty generic concept, and lands on a page with a specific view on the search term. It's more likely this specific content differs from what was desired by the visitor relative to the Home Page, which by nature is meant to have a generic appeal. The generic approach gets the longer visit and deeper site penetration relative to the specific approach, but also ends up driving away the specific visitors I am looking for (those who might want to buy a book on measuring and tracking loyalty metrics) at a higher rate. This kind of effect is seen quite frequently in direct marketing
efforts; the more targeted you get on the front end, the lower the
"initial response" but the higher the "final
conversion" to the desired outcome you are looking for. The
results may seem intuitive to you (give them what they want and they
respond at a higher rate) but you don't know for sure until you
measure the effect. To maximize the ultimate conversion of the
whole site, you have to find the "perfect balance" between
the initial response and final conversion to the desired behavior. That's right, you guessed it. I'm going to have to go down
another layer and find out what the heck is going on. Next month
we'll have the last Drill Down on this topic, I promise. I've been reading the content on your website and so far it A: Well, that's good! I was starting to wonder if maybe I was wrong about the whole thing... Just kidding, thanks for the compliment. Q: I do have one question. You mention that if a company has less than 65,000 transactions Excel can be used to measure customer Lifecycle metrics. What was the time frame for the transactions? Was that 65,000 per year, month, etc.? Can you still use Excel if you have more transactions by "aggregating" the data? How would you go about doing this aggregation? A: Oh sure, you've got "one question". Good thing I don't have a limit on the number of questions per customer around here... It's 65,000 total transactions, the number of "rows" in an Excel spreadsheet (it's actually a tad more). Access can become unfriendly over 100,000 rows or total records. It seems logical if you have this many transactions, you would probably be using SQL Server, Oracle, or something else more robust than Excel to hold your customer data. That said, you can always aggregate data to keep it under 65,000 rows and still use Excel - just be careful what and how you aggregate. Generally, the lower the economic value the transaction has, the more OK it is to aggregate. So if you had a choice, you would aggregate page views, but not purchases. For example, you could aggregate an entire day's page views into one record, instead of keeping them as unique records. Or a whole week's worth. Instead of having individual page views, you would have an "activity record" that would look like this: Customer ID With purchases and other direct revenue items, I always try to keep as much data as possible, because there are other things you will want to do down the line with the detail once you see how powerful LifeCycle profiling can be. That said, people are running into "resource limitations" these days, so here is what I would do: prove it out and then beg for money. In the beginning, you could aggregate purchases, let's say monthly. Run these aggregate transactions through the software and create your LifeCycle models, which will be of "aggregate buying behavior". With an eye towards proving out ROI, track your marketing and show how you can double or triple response while lowering costs using LifeCycle profiling. Then say to the appropriate penny pincher, "This is what we can do with aggregate purchase behavior. If we could keep more details on each transaction, we could run these LifeCycle models based on category of product purchased, average price paid, time of day or day of week - any piece of data we can afford to store without aggregation. If we do that, we can begin to really see which products, prices, times of day or days of week create the most valuable, long LifeCycle customers and target correctly". The next sound you hear should be the cash drawer opening...ka-ching! Aggregation can also be thought of as relative to the frequency of profiling. If you want to profile customers intra-day (why?), then you need all the individual page views. But if you are only going to profile customers once a week, you could use daily totals, or once a month, use weekly totals. Whatever the next smaller logical unit is relative to the profiling cycle is a good place to aggregate. Since what is most important is not a customer's LifeCycle score, but a change in LifeCycle score, you have to pick a time frame that makes sense for the natural cycle of your business to profile customers. A lot of times biz owners have a pretty good feel for this. If it "feels like" (or you know for sure) your best customers buy 2x a month, then run profiles 2x a month. If they buy 2x a week, running profiles every 2 months may not help you much. You want to try to synch up your profiling with what you perceive to be the behavior, or better yet, measure the behavior first. If you synch to your best customers, you'll be on top of the rest of your customers, because their behavior is not likely to change as rapidly as it might among best customers. And after all, you want to be paying the most attention (from a tracking standpoint) to your best customers. Whatever changes you may implement based on LifeCycle Tracking for them should "trickle down" to the rest of your customers in a positive way. Hope that answers your question; feel free to continue asking until
it makes sense to you. And thanks again for the kind words on
the site - be sure and tell your friends! Get the book with Free customer scoring software at: Booklocker.com Amazon.com Barnes & Noble.com Find Out Specifically What is in the Book Learn Customer Marketing Models and Metrics (site article list) |
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