Category Archives: Analytics Education

Context Parameters for Best Use of Recency Metric

Analytics Education, Customer Experience, DataBase Marketing, Driller Q & A, Lab Store

Jim answers questions from fellow Drillers
(More questions with answers here, Work Overview here, Index of concepts here)

Topic Overview

Hi again folks, Jim Novo here.

Time to take a look at some basic strategy framework ideas in a customer retention program. You have to know where you are first before you can decide what actions to take, and this initial analysis will prompt ideas for action. Trust me, finding out specifically what is happening in an actionable way is the most critical step to the design and execution of a customer retention program. Not doing this is why so many of the programs fail. Ready, Driller? Let’s do it.

Q: I’m reading some of your information you have on your web site, regarding Recency / Frequency. I’m curious about the statement that Recency is the number one most powerful predictor of future behavior – if you did some thing recently you’re more likely to do it again.

A: Yes. Funny thing about web sites, it’s hard to control what sequence people read things in. From the questions below, I believe I have failed to introduce you to the Recency metric in the right context. Shame on me!

Q:  With regards to purchases, how is this so?  I can think of numerous instances where this might not be true.  In fact, I would guess that price of purchase would be a more likely indicator of whether or not someone would purchase again.  If I’m running Best Buy, and someone comes and buys a washer / dryer, I would not expect they’d be buying another one anytime soon.  Ditto furniture, cars, travel bookings, etc.

A:  Two important “context” issues surrounding Recency.  First, Recency is a “relative” metric, it doesn’t exist by itself, but “relative” to other data points.  In the case of customers, Recency and the “likelihood” is a relative comparison of two customers, two customer segments, or a customer versus the average customer, for example.  So for a washer / dryer purchase, looking at the customer in question, Recency answers the question, “how likely is this person to purchase relative to another customer”.  It’s a scoring system, a ranking of likelihoods to (in this case) buy, or visit, or download, or whatever.

Continue reading Context Parameters for Best Use of Recency Metric →

Customer Marketing for a Carpet Store

Analytical Culture, Analytics Education, DataBase Marketing, Driller Q & A, Marketing thru Operations, Measuring Engagement,

Jim answers questions from fellow Drillers
(More questions with answers here, Work Overview here, Index of concepts here)

Topic Overview

Hi again folks, Jim Novo here.

OK Jim, so what if the small business is “old school”, you know, not a lot of computer stuff other than billing / scheduling and so forth, and knowledge of spreadsheets is limited. Can the business till take advantage of the ideas you are putting forth without a lot of Excel going on?

You betcha fellow Driller – as long as you don’t mind a little paper and pencil madness …

Q:  Like most of your readers and visitors, I am absolutely bowled over at the prospect of what can be achieved by studying customer behaviour on a simple database/spreadsheet and using the resultant insight to drive unique High ROI customer marketing programmes to increase profits and reduce marketing costs.

A:  That’s a mouthful!  Welcome to the club.

Q:  I have to say that prior to meeting you, on your website and in your book, I had been intrigued by Arthur M. Hughes’ Strategic Database Marketing, but regretfully had reached the conclusion that its inspirational techniques were just not capable of being actioned by me, an Access/Excel illiterate and not so good on the figures either.

A:  Arthur Hughes is a hero of mine though I have never met him.  Some very nice folks have told me my material reminds them of Hughes, sort of a “next generation” Hughes.  That’s very good company for me to be in…

Q:  But your Drilling Down methods and the possibility of your consultancy help, has revived my enthusiasm to learn all I can about these wonderful techniques and to make use of as many of them as I am able.

Here is my challenge:  Father and son business.  Together about 12 years, but moved to present premises four years ago when they extended their product range and re-launched with new branding- under our stewardship!  They are a typical, small company turning over just under the $1M mark and spend around $30,000 – $40,000 pa on their marketing, mostly direct mail (works for them) and email.  Their product range has consisted of fitted carpets, flooring and Oriental rugs.  They have now doubled the size of their store by taking the first floor too.

Continue reading Customer Marketing for a Carpet Store →

Actionable Customer Retention Measurement

Analytical Culture, Analytics Education, Customer Experience, DataBase Marketing, Driller Q & A, Marketing thru Operations, Measuring Engagement,

Jim answers questions from fellow Drillers
(More questions with answers here, Work Overview here, Index of concepts here)

Topic Overview

Hi again folks, Jim Novo here.

Simple question below, not so simple answer. There’s a lot of conflicting ideas floating around on the subject of how to measure customer retention properly, and to be honest, it really does depend on the type of business we’re talking about. Further, in order to properly measure customer retention – in a way you can take action to improve retention / increase profits – you have to define it first, and that can be as much of a challenge as the actual measurement. Ready for a trip down into the depths of this area? Hang on, it’s quite a ride, you Driller you …

Q:  How do most companies measure customer retention?  Is there a formula?

A:  The short answer is not many companies outside of specific industries are very adept at customer retention – yet.  For traditional (not-online-born) companies, it is most commonly used in telecommunications, financial services (including insurance), direct marketing (catalogs / web sites, etc.), subscriptions / publishing, and the travel industry.

The reason for this concentration: these industries have traditionally collected detailed data on customer interactions as part of the offline business model.  Now that many other industries are collecting data on customer interactions online, the lessons learned in these “lead” industries are proving quite valuable for industries new to direct customer interaction.

A “standard” way to measure it, if you are looking to align your metrics with Wall Street and your financial statements for example, is “12 month active”.  Any customer you have had contact with in the past 12 months is still a customer, any customer with no contact in the past 12 months is a defected customer.

This is a retail / mail order oriented view, and if you sell products, then “contact” means “purchase”.  If you are in the services business, it could be any contact – phone call, e-mail, sales call, download.  Divide the number of 12 month active customers by the total number of customers and you have your retention rate.

There is no reason you can’t use “24 month active” or “36 month active” or “5 year active”.  The point is to define what retention is for your particular business and stick with it.  Get agreement on what makes sense for a measuring stick and try to improve.  Often your own data will tell you what the best “no activity cutoff” is for your business.

Retention is really a “continuum”, and retention rate is always “relative” to your perspective. If you use a very “tight” definition like “12 month active”, you will lower your retention rate. As you expand the time period, your retention rate rises. The problem with most companies is they expand this cutoff time period to infinity, meaning every customer is still a customer unless they notify you they are not. Is this a useful measurment? Doubt it…

Continue reading Actionable Customer Retention Measurement →