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Recency: Web Retailing Example
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|
30-Day
Buckets |
All Customers | All Newsletter Responders |
| 0-30 | 3% | 31% |
| 31-60 | 6% | 18% |
| 61-90 | 10% | 18% |
| 91-120 | 14% | 14% |
| 121-150 | 16% | 10% |
| 151-180 | 20% | 6% |
| 181+ | 31% | 3% |
|
Total |
100% | 100% |
Is it possible that (top row of chart) almost 1/3 of the responses came from 3% of customers? That (top two rows together) nearly 50% of the responses came from 9% of customers? One thing appears clear: the more Recently someone had purchased, the more likely they were to respond and purchase again from the newsletter. The mirror image, of course, was also true: the longer it had been since last purchase, the less likely it was a customer would respond to the newsletter.
But what to do with this information?
As the owner of IMissAsia went about the favorite task of the day - reviewing and packing orders - thoughts were on this topic of "doing something" with this Recency info. The owner then noticed orders coming in from the "CRM program" started last month for best customers. Finally, some good news.
It was a very simple idea really - the owner took the time to identify best customers who had not shopped in 180 days and sent them a special discount. This idea came from a friend in town who had a hair salon. It was a really big discount thought, and the owner disliked seeing all that margin go out the window, but was happy to have the orders. If the only way to get them to respond was to be aggressive, so be it. After all, it was very targeted, and generated large orders.
Then it all hit the owner like a ton of bricks.
The less Recent a customer is, the less likely they are to respond. So you should be able to "rank" customers by likelihood to respond. But what if customers go through "stages" of being likely to respond, a predictable "cycle"? As the customer drops through 30 day, 60 day, and 90 day Recency, they become less and less likely to respond. With best customers, when they get to 180 days, it takes a huge discount to get them back, and not many even come back. What if I got involved in this cycle earlier? Why wait for them to get to 180 days before acting?
Right now, the owner thinks, I send the same 10% discount to everybody who gets the newsletter and the response varies by Recency - the more Recent the last purchase, the higher the response rate. So what if I altered the discount by Recency, giving a bigger discount to folks who were less likely to respond - the ones who are less Recent. In other words, vary the discount by the stage of the "cycle" the customer is currently in.
I could probably cut discount costs while increasing response rate, because I would not be giving away as much margin to those most likely to respond, and would be making more aggressive offers to those least likely to respond. Lower discount costs, higher response rates for the entire mailing.
But what is the right discount to offer for each Recency bucket? The more aggressive the discount offer, the higher the response, but higher response means more margin going out the window. Surely there is a "tradeoff" of low discount cost with high response for each Recency bucket, and it is probably different for each bucket - since "normal" response is so different in each Recency bucket. So all I have to do is test each bucket across a range of discounts to find out what discount is most profitable for each of the buckets!
Looking at the buckets, the owner chooses the 91 - 120 bucket to test first because that is where customer response seems to really start trailing off; customers in this part of the "cycle" appear to be the most at risk to never respond again. So the owner divides customers in the 91-120 bucket into 4 equally-sized groups, and each group is sent a different discount:
Discount Test : 91 – 120 Day Recency Segment
| Customer Sample | 1000 | 1000 | 1000 | 1000 |
| Discount Offer | 5% | 10% | 15% | 20% |
| Response Rate | 2% | 4% | 6% | 8% |
| Responders | 20 | 40 | 60 | 80 |
| Average Price | $80 | $80 | $80 | $80 |
| Totals Sales | $1,600 | $3,200 | $4,800 | $6,400 |
| Gross Margin | 30% | 30% | 30% | 30% |
| Gross Profit | $480 | $960 | $1,440 | $1,920 |
| Discount Cost | $80 | $320 | $720 | $1,280 |
| Net
Profit Before Media Expense |
$400 | $640 | $720 | $640 |
The most profitable offer for the 91-120 day Recency bucket, the one that generates the highest response while giving up the least
margin dollars, is 15% off - not the 10% off these people were used to seeing. And what is more, in subsequent repeats of this test, 15% off is
always the most profitable offer to use with the 91-120 Recency bucket -
the outcome of the promotion is consistent.
Well fellow Drillers, you can imagine how excited the owner of IMissAsia was to lower discount costs while increasing response rate. And if this approach works for the 91-120 day Recency bucket, it probably works for all the other buckets as well, don't you think?
(Jim's hint - it does).
But all the owner of IMissAsia.com has right now is a more profitable newsletter promotion. The biggest discovery - the one with the most potential to increase profits for IMissAsia.com - still lies right around the corner, as we will see next month.
If you would like to read the next installment of
Recency: The Web Retailing Example, click
here.
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If you are a consultant, agency, or software developer with clients needing action-oriented customer modeling or High ROI Customer Marketing program designs,
click here.
If you are in SEO and the client isn't converting the additional
visitors you generate, click here.
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Questions from Fellow Drillers
=====================
Jim's note: If you still don't know what RFM is
and how it can be used to drive increased profitability in almost any business,
read
this.
Q: Hi Jim! I'm putting together a college course on Relationship Marketing, but find sources on the subject conflicting with each other. Is there any quality material out there on this topic worth using as a college textbook? And here's a confusing issue for me doing this research: is there a difference between Relationship Marketing and CRM?
A: There are quite a few opinions on the definition of Relationship Marketing, and I have to state at the start I am not part of the "new thinking" group (mostly CRM "experts") who believe something has fundamentally changed about customer behavior in the past 4 years. This is where a lot of the confusion starts.
There is a big difference between a new channel and a new behavior. Customers may do things faster or more often now with the web, but that does not mean the overall behavior or even attitude has changed. Customers have always wanted sharp pricing and good service. Just because it is much easier for a company to fail to provide what the customer wants on the web, and this failure is so much more obvious, does not mean customer behavior has changed.
The fact is, many companies never had customer data before and now they do, and they don't like what they are seeing. People who claim things have changed are simply seeing evidence for the first time of what was always there, and calling this evidence "new".
Many CRM experts focus on the "intangible value of the customer relationship" and spend a lot of time theorizing on the future value of a "loving customer" having a "relationship" with the company. Even if this mattered, you can't measure it, so this track is a perfect excuse to expand billings with endless navel-gazing. I believe customer loyalty is measured in sales and profits, and the customer isn't interested in having a "relationship" with a company. I don't need abstract theory to make the ROI work out - I have always proved it with hard data. As soon as you start "estimating the intangible value of the customer relationship" to bolster your ROI, you are entering into never-never land, in my opinion.
Relationship Marketing, as originally defined, is not about having a relationship with the customer. It is a strategy which matches the marketing approach to the ebb and flow of the Customer LifeCycle, and creates very high ROI customer retention and value-enhancement programs using this information. Anything else is a dream, in my opinion.
You appear to be teaching this course at several difficulty levels. Now that you know where I am coming from, I will provide the fundamental list of books every serious student of this area should read.
Personally, I follow the original definition of Relationship Marketing as defined in this book: Relationship Marketing - Successful Strategies for the Age of the Customer by Regis McKenna (1993).
McKenna is a true visionary who "got it" way before CNBC created visionaries every day. The essence of this book: Marketing has a much higher ROI if it is "tuned" according to the Customer LifeCycle. For more on the Relationship Marketing concept, click here. FYI, CRM as most "experts" describe it is not Relationship Marketing. More on this below.
This next book essentially provides real world examples as proof the core ideas McKenna put forth actually work and are very profitable - The Loyalty Effect : The Hidden Force Behind Growth, Profits, and Lasting Value by Frederick F. Reichheld (1996) Let me be clear: the intent of this book was not to prove McKenna was right, but that was my take on it. If you read the examples carefully you will notice high retention / high customer ROI companies intuitively change their approach to the customer as the LifeCycle plays out.
The next book takes some of the ideas from the previous books and updates them for the web; it is lighter on background and theory, and more organizationally / implementation oriented, which makes it the perfect 3rd book to read - The Engaged Customer: The New Rules of Internet Direct Marketing by Hans Peter Brondmo (2000) Brondmo "gets it" and delivers it straight without the navel-gazing. This book is the right one for the VP level people who need to understand how things fit together at the macro level but don't need all the gory implementation details.
This next book is mine and focuses on executing the specific tactical elements of a Relationship Marketing strategy: defining / tracking the Customer LifeCycle, and turning this information into higher profits through targeted marketing programs - Drilling Down: Turning Customer Data into Profits with a Spreadsheet by Jim Novo (2nd edition 2002)
My book is for the Director level people who have to implement. It uses simple customer models to identify customer value issues early in the LifeCycle, and shows how to proactively address these issues in two ways: by fixing customer acquisition campaigns so they increase initial customer ROI, and by creating high ROI customer retention programs that increase customer value. The following are examples of two of the models from the book, along with how they are implemented and how to measure the ROI of the implementation: Latency Recency
Good luck on putting together your courses!
Jim
-----------------------------------------
I can teach you and your staff the basics of high ROI
customer marketing using your business model and
customer data, and without using a lot of fancy software. Not ready for the expense and resource drain of CRM?
Get CRM benefits using existing resources by scheduling
a workshop.
-----------------------------------------
That's it for this month's edition of the Drilling Down Newsletter. If you like the newsletter, please forward it to a friend - why don't you do this now while you are thinking of it? Subscription instructions are at the top and bottom of the newsletter for their convenience when subscribing.
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 right here.
'Til next time, keep Drilling Down!
- Jim Novo
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