Finding LifeCycles & Retention Profits
Drilling Down Newsletter #109: 4/2010

Drilling Down - Turning Customer
Data into Profits with a Spreadsheet
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Customer Valuation, Retention, 
Loyalty, Defection

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Topics Overview

Hi again folks, Jim Novo here.

This month we're focusing on how to create retention metrics and use them to prove out the ROI of your programs.  We have one example from Retail and one from Wireless.

In the first, we're asked for a simple definition of retention, but I call for segmentation so we can put some "actionable" in the mix.  Next, we run a simple model to calculate the value generated by customer retention.

Let's do some Drillin'!

Questions from Fellow Drillers
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Finding Customer LifeCycles

Q:  For an online retailer, what is the best way to gauge retention in its most basic and simplest form?  % of orders that are from repeat buyers?  % of orders in month 2 who are repeaters that first bought in month 1?

A: I would take direction on this from the actual results of campaigns.  Basically, at the point a customer no longer responds, they have defected.  Perhaps this averages 3 months or 6 months after 1st purchase, and there will be category or price segments within these "time" segments.  Retention is really measured by the defection.

Now, that's not to say that % orders from repeats or the other one you mentioned are not valid, but I suggest you think about the specific  question you want answered by the metric you choose.  % orders from repeats, for example, is a common metric in mail order but is often biased by campaigns, e.g. if you ratchet up customer acquisition during a single month you poison your own metrics.

You can "reverse engineer" into it by looking for people that have already defected and then find their start date, then take the average length of time between start and finish.  Let's say you agree that a person who has not  bought in over 12 months is probably no longer a customer.  Find all those people, find their first and last purchase dates (exclude 1x buyers), calculate average months between first and last purchase.  

If this number is 8 months, then your average LifeCycle is 8 months long, and your "active" customer base is therefore everyone with a purchase in the last 8 months.  Divide this number by total # of customers, and you have your  retention rate.

But if you are going to act on this information, averages are not very useful.  So I would further segment this group by original campaign source, category of first purchase, price point, and so forth so you begin to see patterns that can be acted on.  

For example, let's say you find new customers from PPC campaigns have a 10 month LifeCycle and new customers from Display campaigns have a 6 month LifeCycle.  This is an incredibly important and highly actionable piece of information on several fronts, from allocating campaign spending to the triggering and content of customer retention campaigns. 

Oh yea, I forgot, you said "simple".  OK, for simple, the "Wall Street" standard used throughout the direct retailing industry is "12 month active".  What percent of customers have made at least 1 purchase in the past 12 months?  That is retention rate.

The problem with this approach is it begs for a "last ditch" retention marketing effort at 12 months since last purchase.  But if the LifeCycle is really 6 or 10 months long, you will be late and the program will lose money.  This is often why so many people say they can't retain customers - they are using the wrong metrics, and acting too late to really save the customer.  "Winback" is not retention.

That's why I always prefer to match the metrics to the actions.  It simply doesn't make sense to me to know customers have an 8 month LifeCycle and then use a retention metric called "12 month active".  

You should at least use "8 month active", if you have the resources to figure out it is in fact 8 instead of 12.  The "12 month active" is used as a default because it lines up with the annual reporting of financial statements, but is often not a true measure of customer behavior - it's simply "convenient".

Jim
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Marketing program designs, click here.
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Determining Retention Program Profits
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Q:  I got the job of servicing the top users on our network.  I must confess I dazzled the interviewers with statistics from your Recency, Frequency, and Monetary model !!!

A:  Congratulations!  Well done.

Q:  I know I should be paying you for this but I would like to communicate with you once in a while to tell you what's going on..?  If you are not happy with this I really understand.

A:  I'm fine with it, as long as it doesn't become a full time job!

Q:  Here's my plan:

1. I would like to start by segmenting high users by usage, (usage bands)
2. Next I would like to profile demographics for each usage band
3. Next I will keep a Monthly tab on their recharges i.e. Frequency of recharge in a month and Monetary value of recharges
4. A special helpdesk will be set up specifically for them (top users) to log complaints hence we will have a log of their complaints.   All their complaints are to be resolved in four hours (if it is not network related)
5. We will communicate with them by calling twice a year (they don't like being called too often) also we are thinking of sending birthday text messages (it is a form of communication)

That is all I can think of for now.  If you have any tips I would really appreciate it.  Thank You for helping me get this job.

A:  You're welcome, glad it worked out!

I'm not sure how helpful the demographics will be, at least in the beginning, that would typically be a topic for "Phase 2".  Ultimately, you will be judged on the increased retention and related profitability of these top users; you are going to have to prove what you are doing is working.  So it is very important to first establish exactly where you are with retention.

The usage bands idea is a good one, but that only gives you the segments, you need to then determine defection rates for the segments, since a drop in this defection by usage band metric is probably the best proof you will have that your program is working. And once you have the defection rate and the value of a customer in the band, you can get to program profits.

For example, let's say you find out there are 1,000 customers in the "best" usage band, they are worth $100 in profits annually, and their 1 year defection rate is 30% - a year after these 1,000 customers start, there will only be 700 of them left.  You implement your programs, and the annual defection rate drops to 20%, meaning there are 800 customers left at the end of the year.  

This means your programs are responsible for retaining 100 customers with an annual value of $100 - you generated an additional 100 x $100 = $10,000 to the profit line before the cost of your programs.  If your programs for these 1,000 customers cost $2,000, you increased cash flow by ($10,000 - $2000 = $8,000 or $8 per customer ($8,000 / the original 1,000).  This is the kind of "proof" you are looking to have - the kind of proof that will make management really sit up and notice!

So, go back 2 years or as far back as you can, and look at all the customers who joined, and segment by usage bands / recharges.  Then ask this question: what percent of the customers in each band are still customers after 1 year, and what percent are still customers today?  These are your baseline 1 year and 2 year (if you can go back that far) retention rates for each band.  Your mission is to improve these rates, and in so doing, you will increase cash flow / profits.

Then perhaps you can look at demographics to help design your programs, but I would do something else first, if possible.  Interview defectors, and find out why they are leaving.  You can interview Recent defectors from each band, you don't need to talk to the ones from 2 years ago.  What they tell you will be more important to designing your program than any demographics (save geography, which will highlight potential service problems).

You should be really most interested in what people do and why, rather than who they are, because behavior predicts behavior, demographics do not.

Jim
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That's it for this month's edition of the Drilling Down newsletter.  If you like the newsletter, please forward it to a friend!  Subscription instructions are top and bottom of this page.

Any comments on the newsletter (it's too long, too short, topic suggestions, etc.) please send them right along to me, along with any other questions on customer Valuation, Retention, Loyalty, and Defection here.

'Til next time, keep Drilling Down!

- Jim Novo

Copyright 2010, The Drilling Down Project by Jim Novo.  All rights reserved.  You are free to use material from this newsletter in whole or in part as long as you include complete credits, including live web site link and e-mail link.  Please tell me where the material will appear.