The Web Retailing Example - Drilling Down
Newsletter # 33: May 2003
Drilling Down - Turning Customer
Data into Profits with a Spreadsheet
Customer Valuation, Retention,
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To find out more about this topic:
In This Issue:
# Topics Overview
# Best of the Best Customer Marketing Links
# Tracking the Customer LifeCycle: Recency
# Questions: Implement Marketing Database?
Hi again folks, Jim Novo here.
This month we've got the usual "best of" Customer
Marketing article links section, but only one link.
This is because we also have the final chapter on the Recency metric with IMissAsia.com, and
it's a doozy. Plus, a fellow Driller wants to know what is involved with using an
operational database for real-time marketing purposes (I can hear the
IT folks on the list pounding the desk)...
My favorite topic lately is this one: why are companies so afraid
to call an end to the customer LifeTime? If you can't peg the
LifeTime, you can't measure LifeTime Value, and if you can't measure
LifeTime Value, you leave the majority of CRM ROI off the table.
Sound interesting? If you want to find out how to attack this
issue and bring home the ROI bacon using simple customer models, check
out my searchCRM interview and webcast:
(on-demand, ignore "start time")
OK, let's do some Drillin'!
Best Customer Retention Articles
This section flags "must read" articles moving into the paid archives
of trade magazines before the next newsletter is delivered.
If you don't read these articles by the date listed, you will have to pay
the magazine to read them from the online archives.
Note to web
site visitors: These links may
have expired by the time you read
can get these "must read" links e-mailed to
every 2 weeks before they expire by subscribing to the newsletter.
Loyalty Breeds Success
for Drug Mart, Vendors
Expires May 27, 2003 DM News
What is it with those Canadians anyway? They sure love their loyalty
programs - and so do the program partners when they can drive instant sales and
share gains using the rich transactional database for targeting. Like they
say in the article, "past purchase behavior is the best indicator of future
behavior." Want to know more? Download the loyalty
case study and check out the book that teaches you how to use past
behavior to increase your profits.
Tracking the Customer LifeCycle:
Real World Examples
If you are new to our group and want to review the previous
LifeCycle metric - Latency - that discussion is
along with the Real World examples Hair Salon and B2B
Software. The previous piece on Recency is here;
this series on Recency starts here.
Recency: The Web Retailing Example
Recall last month, the owner of IMissAsia.com solved the question
of why response to the newsletter keeps going down but sales remained
flat: most of the buying activity was coming from people who Recently
joined the newsletter. Since the number of new people per month
joining the newsletter was flat, sales are flat month to month.
But as the newsletter list keeps growing each month, this "new
blood" - new subscribers who are the most likely to respond and buy -
becomes a smaller and smaller percentage of the total newsletter list.
So sales remain flat as response rate to the newsletter is falling.
So now we have a chain of events, or LifeCycle,
driven by Recency: the more Recent the subscriber, the more likely
they are to purchase the first time; and the more Recent the last
purchase, the more likely the buyer is to purchase again. In
fact, all subscribers and customers can be ranked for their likelihood
to make a purchase at any given time. The owner is quite pleased
with discovering this idea, since now this ranking can be used to
reduce the amount of the discounts offered, an area of
great concern at one time.
But on to the next challenge - how to increase newsletter
subs? The owner always tried to follow hot topics or trends
talked about in the online community at the site, both in the
newsletter and merchandising of the site. The owner felt it was
more logical to "put products in front of the traffic" than
try to force or bend the traffic to come to the products. Find a
group of people and give them what they are already looking for - it's
same reason why search marketing works so well for the
site. The owner was not sure if this was the right thing to do
on the content side, but there was really no way to prove anything in
For example, some parts of the site get very high traffic, others
lower traffic. Would more newsletter subs be generated if the
high traffic areas had more content? If the low traffic areas
were downplayed in the navigation? Who knows, and implementing
would be a lot of work, so just guessing was not a good idea.
The owner had done some content analysis along these lines. There were 10 major content areas on the site; all
the pages in a single area are set up as “Content Groups” in the visitor
analysis tool the owner is using. This means the owner can track stats at a
macro level for content areas as a whole very easily, instead of having to deal
with tracking down individual page views and aggregating them into a report.
The owner used these Content Group reports to detect “hot spots” on the
IMissAsia.com site. By looking at the trend in total visits and page views over
time, the owner got a good idea of where the interests of the audience
were flowing, and used this information to “stand in front of” this topical traffic
with articles and products. But was following the traffic really
the right idea? Certainly not all traffic is created equal;
quantity is not equal to quality. But what else would you look
Wouldn’t you know it, the owner had just upgraded the visitor analysis tool,
and found out that it now supports visitor Recency as a native
reporting metric right out of the box.
Just in the nick of time for this Example, eh?
So, the owner excitedly turns Visitor History on in the analysis tool, and
it starts building a record of last visit date for each visitor. Then, looking
at the 10 different Content Groups, the owner ran a report on the average
Recency (average days since last visit) of visitors to each of the Content
Groups. What do you think the owner found? Yup. Dramatic differences in
average Recency by Content Group. In fact, generally the Content Groups with
high overall traffic had the worst average Recency (longest time since
last visit), and the low traffic groups had the best average Recency
(shortest time since last visit):
Content Groups, by Traffic and Recency
|| 7 days
|| 4 days
Well, there's a shocker, thinks the owner, who was getting used to
this kind of slap upside the head from the Recency metric by
now. But it made sense. The areas with specific, targeted
content had the lowest traffic but this traffic was on average more
Recent - visitors to these areas didn't just "repeat," they
were Recent Repeaters. The high traffic areas had relatively untargeted content
so they drew a lot of activity but not a lot of loyalty; after a few
visits that was it.
"How interesting" thinks the owner of IMissAsisa.com.
Perhaps the high traffic / low loyalty areas are frequented mostly by
new visitors and potential customers, where the low traffic / high
loyalty areas are frequented primarily by current customers.
Clearly there was an actionable idea in this chart, though it would
take some more crunching with the visitor analysis tool to draw it out.
"Wait a minute," the owner thinks. "I have
been tracking newsletter subscriptions by Content Group. You
Well, fellow Driller, can you guess what the owner of IMissAsia.com
is on to here? What will the data say? Here
Content Groups, by Traffic, Recency, and Newsletter Conversion
|| 7 days
|| 4 days
You guessed it. The more Recent the Content Group, the higher
the conversion of visits into newsletter subscriptions. The
owner, once again slack-jawed by the power of the Recency metric, sums
it all up:
"On average, the more Recent the visitor is, the more likely
they are to subscribe to the newsletter, relative to other visitors.
The more Recent the newsletter subscriber is, the more likely they
are to make a purchase, relative to other newsletter subscribers.
The more Recent the last purchase is, the more likely the buyer is
to make another purchase, relative to other buyers."
The owner continues on, a bit breathless with the rush of all this
stuff coming together.
"What I am seeing is that becoming a "best customer"
on IMissAsia.com can be seen as a process, one that starts with
a visit, moves on to a subscription, then a purchase, and hopefully
multiple purchases. I always sort of knew that; now I see it in
action. But what's really powerful is I can rank each member of
a group - visitors, subscribers, buyers - against all the other
members of their group for likelihood to move forward in the
process using the Recency metric.
Knowing this provides me with three benefits:
1. Having the source of the visitor, subscriber, or buyer, I
can "track backwards" and find out what sources (media type
/ offers) generate visitors most likely to become subscribers, buyers,
and multi-buyers - and using Recency, predict which of those are most likely to complete
any step in the LifeCycle process.
2. I can customize communications to the members of each
group based on their likelihood to move forward in this LifeCycle
By addressing specific people with the right message at the right time
(like I did with the discount
ladder), I will generally get higher response and conversion of
the visitor to
multi-buyer while lowering my marketing and discount costs.
3. I can track retention and failure to progress in the LifeCycle
and be proactive about trying to "save" customers who are in
the process of defecting. At any point in the visitor -
subscriber - buyer - multi-buyer LifeCycle, I can track decreasing
likelihood to progress and take special action with those who have
high potential or current value based on their source or past buying
It was late, and the owner was exhausted. No point in trying
to map out all the implications of these discoveries now, the owner
thinks; this Recency
thing was obviously quite powerful and it would take some time and
testing a few ideas to fully develop.
For example, rather than determining "what's hot" just by
visit volume, if I look at the Recency of visitors I can make a better
guess on whether the issue is important to core customers or
casual visitors, and adjust the message and offers appropriately.
To think all of this came out of
trying to answer one simple question on newsletter
Having now discovered the secret of the Recency
Chain, the owner was confident IMissAsia.com could be taken to the
next level of profitability. Things are
the owner thinks, as she turns off the light and "heads
home" - down the stairs to her living room.
End of Recency: the Web Retailing Example
Jim's Note: The capability to track Recency (or Latency)
has up until now been addressed with either a home-built system (all you need
is a way to recognize users and store last visit date) or a data warehouse solution like
WebTrends Intelligence Suite , CoreMetrics, Quadstone, or one of
What is new is the availability of Visitor History tracking without building it yourself or getting
into a solution that has too much horsepower in other areas for what you need.
In other words, it just got a lot cheaper and easier to track visitor history - and also to
have these critical metrics integrated into the rest of your web site reporting.
WebTrends Reporting Center provides Visitor History capabilities in the
Enterprise Edition, storing Recency and Latency data, plus many more "source" variables such
as 1st campaign, 1st referrer, etc. Intellitracker out of the UK also provides reporting on Recency
Bottom line: You've got no excuse now...
If you are in SEO and the client isn't converting the additional
visitors you generate, you can help them make it happen - click here.
Questions from Fellow Drillers
If you don't know what RFM is and how it can be used to drive
increased profitability in just about any business, click
Q: As of today, I am in the early planning stages of
an Operational database. This Operational database communicates
with merchant terminals. Loyalty cards will be distributed
to merchants' customers. The loyalty and gift card
functions are not problematic, but the expense to track migration of
customers at the Operational database level is questionable.
With a marketing database created using the software that comes with
A: Ummm... I don't know how many customers you
are talking about, or what kind of operational systems you have, but
the scoring application that comes with the book is just a Microsoft
Access application. My application doesn't "create a
marketing database"; it runs on a database you have already
created. You probably know that, but just to make sure...
Q: Can various reports be made on the Marketing
database that track: who (of a particular segment) had a particular
offer (specific to their buying behavior) and report the redemption or
non-redeemed offers in a specific duration of time? Can I avoid
this expense on an Operational database with a Marketing database?
Q: Well, you can report on anything that makes it into
the database. As long as you can get "who the offer was
made to" and "who responded" data into the Marketing
database, yes, you can report on it, and use it to create new offers.
A: The programmers of the Operational Database
encourage using a Marketing Database for various reasons. First, the
specific offers made to particular customers at a particular merchant
will be communicated to the merchants' terminal using the Operations
database. This protects merchants from customer fraud or abuse
of repeat redemption. Second, they want to make more
money. What do you recommend?
Q: I'm not sure I am following this completely, but I
think the situation is this: your ops people don't want you running
marketing stuff on their database, because they are afraid it will
slow down performance, and that is bad for them. So they want
all the coding, scoring, tracking, and development of offers to take
place "offline." This is quite typical and pretty much
Usually the marketing database doesn't have to be "real
time" where the operational database does. So each night,
the operational database updates the marketing database with
transactions and you do whatever you want on the Marketing database -
analysis, scoring, creation of promo codes, and so forth - without
slowing down operations. You get
the update, then do all your analysis work outside the operational
Now, if you want the ops database to be able to respond in
real time based on customer scores and provide promotional codes or
other data, what you do is send "customer codes" back to the
ops database from the marketing database after you run your scoring.
For example, you get data from ops at 1 am, run scoring until 2 am,
then send promotional codes back to the ops database at 3 am. So
the next day, the operational database can respond to customers in
real time based on scores and codes but it doesn't have to do any
calculations because it has the scores and codes already. This
dramatically reduces the "load" on the operational system,
while still allowing it to be "smart" in real time.
Scoring of transactional data for real-time use in operations is a
classic benefit of RFM, because the scores are
"standardized" and are the same format each time. Since the
scores rank likelihood to purchase and customer value, it is fairly
easy to set up a rules-based system to make offers accordingly.
Am I understanding the question correctly? If not, feel free
to clarify and ask again!
If you are a consultant, agency, or software developer with clients
needing action-oriented customer intelligence 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 2003, The Drilling Down Project by Jim Novo. All
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