Category Archives: Analytical Culture

Intra-Company Promotional Risks

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

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.

Eating Your Own is not a great idea. Yet in many large companies, different divisions literally try to steal customers / sales from each other using the common customer database. Sure, everyone gets real excited over the plans to merge databases across the company and get the “full view” of the customer, and it makes perfect sense. Perfect sense – if you’re also institutionally prepared for wild battle over customer ownership and value stealing to come. This is particularly true (and difficult to deal with) in multi-channel retail environments.

Got your Drillin’ shows on? Let’s take a stroll through subsidy cost land …

Q:  Hi Jim,

Our company has 8 divisions and we completed the integration of all the customer databases a couple of years ago.  We have the 360 degree view of the customer, at least as far as sales transactions, across the entire company in one database.

A:  Congratulations!  However, I note not joy, but some kind of concern in you voice.  I’m just waiting for the “But…”

Q:  The database services group I am part of is under IT.  We respond to requests from the different divisions for customer analysis and the creation of promotional lists for email, direct mail, and telephone campaigns.  It’s interesting because our group is finally directly involved with increasing the profitability of the business and we have some input, which makes the job more rewarding.  I picked up your book because I thought reading it might increase our ability to contribute.

A:  Well, again, congratulations!  But I’m still getting that nagging feeling from your tone.  Still waiting for the “But…”

Q:  I’ve got a two part question for you:

1.  What I am seeing is the different divisions promote to “best customers” of the company as a whole, or even try to target best customers of another division for their campaigns.  It seems to me that contacting these same people over and over from the different perspectives of the divisions is not optimizing customer value, and might actually be irritating to the customers (I know it would be irritating to me).  

The contact frequency across all divisions to the same customer can reach 4 – 6 times a month through various media (phone, mail, e-mail).  Also, there is no customer retention effort going on that I am aware of, it appears it is all acquisition oriented but the main targets are customers of other divisions.

A:  Oh boy, the database marketing pendulum has swung the other way, from “we don’t know what to do with all this data” to “we’re really maximizing that database asset”. You are correct to be concerned about this issue.  Talk about “push marketing”… the intent of each division is “pull” because of the targeting but the result is “push” because of the volume and “noise” created at the customer level.  Too much too fast.

Continue reading Intra-Company Promotional Risks →

Discovering Customer LifeCycles

Analytical Culture, 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.

Today, we’re asked for a simple definition of retention. Problem is, the data / biz model really creates the definition. Meaning, you gotta match the creation of metrics with the actual actions.  So I call for segmentation first so we can put some “actionable” stuff in the mix.

Make sense? Let’s do the “simple” (easy? maybe not) Drillin’ …

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.

Continue reading Discovering Customer LifeCycles →

Difference between RF(M) Scores & LifeCycle Grids?

Analytical Culture, Analytics Education, DataBase Marketing, Driller Q & A, 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.

Both RF(M) scoring and Lifecycle Grids use the same key predictive metrics – Recency and Frequency. So what’s the difference? RFM is a predictive “snapshot” at a specific point in time; LifeCycle Grids are more like a “movie” designed to be predictive over different periods of time. Another way to think of this: RFM is tactical, LifeCycle Grids are strategic.

You dig? Let’s Drill …

Q:  We’re a telecom company trying to get a handle on customer churn and defection, so we can come up with some programs that will hopefully extend customer participation.  We live in the no contract space, offering a service that’s an add on to wireless phone service, so we don’t have a good indicator as to when the customer relationship might end.

A:  Ah, yes.  Your business model is “built for churn”, as I said on my blog the other day.  The behavior then is more like retail, where independent decisions are made in an ongoing way, deciding again and again to purchase.

Q:  I think your LifeCycle Grids method will show best what is happening to our customers.  If using this method, there doesn’t seem to be any reason to do the RF scoring as customers are just going into cells based on where they fall in the Recency and Frequency spectrum.  Is that correct?  Is there any real  difference between RF scoring and the LifeCycle Grids approach?

A:  You are partially correct, they are two versions of the same idea – both are scoring using Recency and Frequency. The traditional RF(M) scoring where customers are ranked against each other is a “relative” scoring method used primarily for campaigns – it is tactical, an allocation of resources model. 

Continue reading Difference between RF(M) Scores & LifeCycle Grids? →