Optimizing for Customer Value
Newsletter 114: 2/2011
Drilling Down - Turning Customer
Data into Profits with a Spreadsheet
Customer Valuation, Retention,
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Hi again folks, Jim Novo here.
I assume most analysts have a finite amount of time to do their
jobs. This means we all have to make trade-offs to optimize our
own time towards highest productivity. Or at least that's what
most employers would hope for: given an hour of your time spent
in analysis, how can you maximize your value?
For most, optimizing your own analytical productivity boils down to
Will you go wide, or will you go deep?
In other words, can you generate more value by analyzing
hundreds of scenarios only at the surface? Or are you more
productive by concentrating on a dozen or so high value
scenarios and going deep, tracing out how they directly impact the
Lots of analysts talk about how people at the company don't take
their work seriously, will not make changes based on their analysis.
Nine times out of ten, these people have decided "going
wide" is the answer to creating value for the company, more is
I politely suggest they go deep instead.
Let's do some deep Drilling, shall we?
Questions from Fellow Drillers
Optimizing for Customer Value
Q: Thank you for creating this useful website!
A: You're welcome!
Q: When figuring out retention rate for an annual or a 8 months life time
cycle period, how do I pick the starting period? Do I look at their first
orders on a date? Or I pick a time frame such as one month?
A: It depends on:
1. What kind of "retention" you are talking about, the definition, which is probably
impacted by the audience for the data
2. What you will do with the retention data, what kind of decisions will be made
and actions be taken because of the data
You should always ask these questions above when someone requests "retention
data" - or any other kind of analysis, for that matter!
For example, there probably is a huge difference in what you would provide to the Board of Directors for
an annual benchmark and what you would provide to Marketing people for executing
In the first case, the data would probably be used to inform
Strategic decision making, for example, should we change our product
mix or approach to pricing given the market?
In the second case, the data would probably be used in a Tactical
way, for example, to target new customers who are predicted to defect
because of the campaign they responded to or the product they bought.
If providing data to the Board, "annual retention rate" would probably make the most sense (again, you should ask, what's it for?). If that's
what they want, you would pick a starting period, probably aligned with the fiscal year (Jan - Dec?), and find out what percent of people who purchased Jan - Dec 2009 also purchased Jan - Dec 2010.
That's the annual retention rate. Useful information,
perhaps leading to the Board requesting action of some kind. But
by itself, you really can't "do" anything with this data,
there's no source or targeting information, there's no customer value
However, if you segment by campaigns, product of initial purchase,
price points, offers, or other actionable variables, the retention
rate could be just about any formula, e.g. what is the retention rate:
a. Today, of people who made their first purchase in 2005?
b. End of 2009, of people who made their first purchase in 2005?
c. Today, of people who ever bought Product X as their first
d. Today, of people who bought Product X as their first purchase in 2009?
e. Today, of people who had at least 2 service calls in 2010, who
became new customers in 2009, who used a 50% off promotion?
and so on. Retention rate for anything tactical almost always requires and audience and time frame to be defined.
Q: You mention in your article, "Total number of customers" as the
denominator for calculating the customer retention rate, do you mean the
total customers at the end of the period? Or those total customers came in
on the first date of a fixed period? Or the first fixed period that I'm
A: Whatever definition is the correct definition depending on the need of the audience.
There is no standard, other than perhaps the very first one, the Strategic "reporting" idea of year over year retention.
This is commonly used in reporting to Wall Street, for example.
While discussing this particular idea of "customers", one might encounter the common problem of not knowing the definition of a customer, at least in terms of retention.
When does the company declare a customer is no longer a customer?
Is a customer "everyone" who has ever purchased? If the company has been around 10 years, and you are calculating retention rate "today", as in how many of these total customers purchased in the last year, you may find you have a very low number, one that won't mean much to anybody,
and is not actionable.
On the other hand, if your definition of "customer" includes a level of activity, for example, "must
purchase at least twice, one of those purchases in the past 3 years", now you are talking about a highly actionable kind of retention definition.
Because there is some hope that people who have purchased at least 2x (Frequency), at least once in the past 3 years (Recency) could actually still be customers, as opposed to defected customers.
If I am calculating a "serious" retention rate, something to be used to take Marketing action, or pay out bonuses, or revise policies, I want to measure against people who actually have some Potential Value, some Value to the company in the future.
That's how I define a customer. To me, there isn't any point in
calling someone a customer who is unlikely to contribute to profits in
If you define as a customer "anyone who purchased over the past 10
years", you just have a dead metric that really does not reflect the reality of what taking action might produce.
In other words, you are including people who are extremely unlikely to still be customers, so what's the point of the "customer retention metric" you
Does the above help answer your question?
Q: I wasn't expecting you to reply me so fast and in such detail!!!
Thank you so much! I'm calculating this retention rate for marketing
and your answer is very helpful for me!!!
A: Great! So maybe ask them specifically how they want to look at it, and if
they seem puzzled, suggest to them various options.
I can tell you from experience with businesses like yours is the buying behavior
tends to peak early and you have to act quickly if you want to extend the
lifecycle. Perhaps not quite as time-critical given your "triple bottom
line", but probably not too different.
This argues for a tighter leash on the definition of a customer, perhaps
purchased at least twice, one of those past 6 months. You could also do 2x
purchase, at least once in past 3 years, and compare, it will give them a
feel for customer defection trend / rate.
The next step would be the Lifecycle map, which uses Recency and Frequency
in a more actionable way, like
Marketing people should be able to use this map to target specific groups of
customers, e.g. purchased 4 - 9 times, but not in the past 90 days.
These are good customers who are in the process of defecting, and require special
attention to keep them on board.
After all, the point of measuring retention is not retention rate
itself, it's about increasing the productivity and profitability of
the business system. Just as you can optimize for conversion,
you can optimize for retention, and sometimes you discover they
For example, one company I worked with featured certain products on
their home page because those products had a high conversion rate on
visits to the home page; they had "optimized" the home page
for this scenario.
However, a very quick and simple calculation showed these products
generated customers with terrible repeat purchase rates relative
to just about every other product with volume. A quick
survey of these customers found out why the repeat purchase rates were
so low - almost all customers disliked the product and thought the
company deceived them. Turns out the company
"over-sold" the product - and that's why the high conversion
In another case, PPC campaigns had been optimized for conversion
without regard to customer retention. Under a budget crunch, the
lowest converting campaigns were killed, but overall sales volume over
the next 3 months dropped much more than the sales generated by these
Reason? These low converting campaigns generated the
company's very best customers in terms of 30-day, 90-day, 180-day
value, while most of the highest converting campaigns generated low
value, single purchase customers on the same time frames.
This kind of analysis is simply not that difficult to set up and
execute, relative to the extreme amounts of value that can be created:
1. Pass campaign codes / info with the order to the backend
order processing. If you are not doing this yet, start right
2. Select a campaign, choose a time frame. If you want
to match up to financial statements (a good idea if you will be
talking to C-Level folks), say January 2010.
3. Grab all new customers who came in on Campaign X during
Month Y - what is their average value 1, 3, 6, 12 months later?
This is a Lifecycle by Campaign analysis, similar to the LifeCycle map
The new customer experience (channel, offer, product) is one of the
most powerful predictors of future customer value, and the value of
these new customers relative to each other tends to remain stable
regardless of how many other generic campaigns (weekly email) you
throw at the customer over time.
Across all campaigns, about 60 - 80% of these new customers will
have the same value at 12 months they had at 1 month. The
question to answer, as with any optimization, is this: knowing the
customer value created by these campaigns varies widely, are we
allocating the acquisition spend optimally? For example, are we
spending 70% of the budget to generate 20% of the annual
customer value? Are we willing to pay more for clicks that
generate new customers with 10X higher annual value?
Retention rate isn't just some mystical number, retention rate quickly
turns into profit dollars and can have incredible financial impact!
Need help with creating action-oriented customer analysis or High ROI
Customer Marketing program designs? Click
That's it for this month's edition of the Drilling Down newsletter.
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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
'Til next time, keep Drilling Down!
- Jim Novo
Copyright 2011, The Drilling Down Project by Jim Novo. All
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