Behavior Profiling for Long Sales Cycle B2B Customers

Customer Experience, DataBase Marketing, Marketing / Tech Interface, Marketing thru Operations, Measuring Engagement

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

So Jim, this customer behavior profiling / prediction is great for consumer businesses, but what happens if you’re running a long sales cycle B2B biz where buying decisions take months if not years, and may involve a dozen decision makers? Well fellow Drillers, the answer is not as complicated as you might think – it’s about where to look for the predictive behavior outside of the sale transaction. Interested? Let’s get to the Drillin’ …

Q:  I read your section about how “R” and “F” are better indicators than “M” which I agree. But for the problem I face, do you have any ideas on how I can redefine “F” for my purpose?  If not, I can always use RM, but will face the drawbacks you mentioned in the book which I think are legitimate concerns for predicting potential value. 

(Jim’s note: this Driller is referring to the modified RFM model used in the Drilling Down book.  For an overview of what he is talking about see this description of what is in the book and this outline of RFM.)

A: Just to ground this discussion, I assume you are talking about Company XXX …
(a major enterprise software company with many products. He said Yes)

You should look for R and F in other places, if “short term” prediction is what you are after  (I’ll discuss long term in a minute).  Long cycle businesses like enterprise software can be more difficult to model because the variables you are looking to do an RF scoring on are not as obvious.  The sales activity may not be particularly predictive of customer behavior because the nature of the business precludes frequency of purchase.

For example, think customer service.  Where in your organization would you see RF show up relative to customer satisfaction?  Perhaps at the call center, help desk, or “outstanding issue” logs of the implementation team?  There could certainly be other areas, depending on how customer care is set up.  The question is: how does the Recency and Frequency of customer care predict the likelihood of customer defection?

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ROI of Branding

Analytics Education, Customer Experience, DataBase Marketing, Digital Analytics, Measuring Engagement, Web Analytics, ,

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

Speaking of questions, you folks are starting to toss in some real zingers. We’ve moved on from the “How do I calculate Lifetime Value” type of stuff to some real mind benders, and this month’s featured question is a heck of an example. Speaking of questions, I always hide the identities of any organizations or people involved, so don’t be afraid to send them on in. Help yourself, and help others as well!

Branding is a much misunderstood topic and it’s beat to death in the forums and trades. I pretty much run in the other direction when it comes up, because I’m a numbers kind of guy and the branders out there never seem to have any numbers to back up their position. That said, there are ways to numerically quantify the value of branding….

Q. Jim, I send a monthly corporate custom-published magazine (content mix of product and broader lifestyle interests) via email to my house e-mail list – how do I measure ROI on what is a purely brand loyalty vehicle?

A: Thanks for sending in such an easy question – Geesh Louise, doesn’t anybody have easy ones any more? I assume you believe over the longer run, those receiving the magazine will either convert to customers, increase their level of business with you, or bring business to you through referrals.

If you have new business “source tracking” in place (where did the business come from?), it should be fairly easy to determine if the business came from someone who is receiving the magazine, or from someone not on the magazine list. Assuming you are also able to track where the non-magazine business comes from, you can look at expenses versus business generated and find out if the magazine is at least as efficient as other ways of generating business.

Hot links to product offers would be a perfect way to do this, and you can test varying offers by Recency to maximize the profit of different customer segments. Under this scenario, the magazine is not only branding, but selling merchandise. So you don’t have to worry about the “ROI of Branding,” the ROI comes from sales and you can easily quantify the ROI using merchandise profit versus the cost of the magazine.

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Profiling Subscription / Service Customers

Analytics Education, Customer Experience, DataBase Marketing, Marketing thru Operations, Measuring Engagement,

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

This Driller knows his stuff, using advanced database marketing techniques on the customer acquisition side. But in a business where the bill gets paid every month and it’s about the same (electric utility), how do you get to the R and F (Recency and Frequency) to model potential customer defections? Great question, and a pithy answer.

Remember, you can use RF profiling on any behavior not just payment related activity! If you don’t know what we’re talking about with this RF stuff, see explanation here.

Q. Jim, Ordered and read your book AFTER reading EVERY page in your website. Your newsletter is outstanding and you seem to be one of the few with real life experience in database marketing with the skills to simply explain with pragmatic examples of how RFM and LTV should be used.

We are a technology based Call Center company with over 70 clients – we do a lot of the “operational” CRM stuff you refer to – Siebel, Onyx, Kana, Webline, …….., as well as a lot of custom developed SFA solutions and data warehousing solutions we developed – mostly the premise of investing to collect enough information to do the 360 view of the customer across communication medium (email, chat, phone, fax) and reason for calling (campaign, sales, orders, info, customer service….)

We have a good mix of B-B as well as B-C. We already do a lot of the demographic modeling for list acquisition (SIC codes, size, number of computers, Geo ….). One thing I noticed is that we do a lot of lead generation based upon list acquisitions along with inbound marketing campaigns that seem to address one shot Sales, not recurring sales.

For example, we sell and service de-regulated energy for one client – this is sell once, then service. Since they pay every month for the service, how do you suggest the RFM model be used for service based sales since there is not really an R or an F??? We still have acquisition and retention problems, but we mainly focus on operational efficiency through technology, not strategic use of CRM data. I would really like to be able to add real value based upon the data collected.

I know this is not your forte, but I was just curious if you had any opinions using CRM data in an RFM model when the product is basically recurring service.

A: Thanks for the compliments on the site, book, and newsletter. I hope they will be helpful to you as we try to get a firmer grasp on these subjects this year!

It’s a little tough to provide you a direct answer to such a broad question without more details, but in general, R and F are highly predictive of any action-oriented behavior. In a “billing / service” business like a utility, you sometimes have to hunt a bit harder for the action you want to model as predictive.

For example, at Home Shopping Network, use of the automated ordering process (touch-tone interface to the ordering system circa 1990) was very highly correlated with Future Intent to Purchase. Not exactly a traditional RF action, to be sure, but a falling RF score on use of the interface was very highly predictive of a defecting customer.

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