Tag Archives: Analytical Culture

Marketing Model or Financial Model?

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.

Where does all this kind of thinking on customer retention and value over time eventually lead you? Well, often right to Finance. Because you see, the more you can do to convince Finance the activities you are in engaging in are increasing profits for the company – and Finance truly believes this because they participated in the creation of the systems, models, and validation – the more likely your budgets supporting these activities will increase.

Simple as that. You’re not afraid of Finance, are you? Good! On to the Drillin’ …

Q:  Been reading through your site a bit.  I run the CRM and online marketing at (large airline) – a business with roughly XX million customers and X.X million members in our loyalty program.  Interested in your thoughts about RFM algorithms as well as aggregated scoring.  My predecessors set up ranked scoring along spend – essentially taking paid purchases and ranking people from high to low in R, F, and M  and then built programs around this.

My issue with this approach is that we find very different behavior  in our top 20%, 10%, 5%, and even 1% (e.g standard deviation of  population is large).  Additionally, rank ordering often grouped  individuals with the same underlying behavior in different categories  because of the arbitrary nature of where the snap lines fell.  So I altered our scoring as follows…(long description of new model)

A:  Did you by chance see this article?

Latency may be a better way to go for an overall approach to airline behavior in the business class; Recency in the tourism class.

It sounds to me what you have done is a similar idea – recognized the generic RFM model is broken for your needs, extracted the essence of the RFM idea, and rebuilt it into a model that works for you.  Nice job!

Q. But,if someone spends $400 on a flight that is 400 miles vs. 1000, the revenue has differing implications – both in terms of customer and non-customer driven fixed and variable costs.  If someone spends $400 on a flight that sells out – we are  potentially spilling revenue (not holding inventory for a bigger spender) – and thus the opportunity value is greater than the  collected revenue.  But if the  flight doesn’t sell out…this may not  be true?

Continue reading Marketing Model or Financial Model? →

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 →

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? →