Monthly Archives: September 2023

LTV of Car Buyers

Customer Experience, 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.

The car business is interesting because the Customer Lifecycles can be so long and the value of a customer beyond just the car (service, etc.) is a huge factor. Can this industry use Lifecycle ideas? You betcha, Drillin’ is Drillin’ …

Q: Do you happen to know approx. calculations of LTV for the car-industry? I wonder what this might be for a person that buys every a new car every 3 – 5 years, including service profits, etc.

A: The only published, verified study I know of on this was done by General Motors for their Cadillac division. To quote:

“Each new customer that comes through the door of a Cadillac dealership represents a potential LTV of more than $322,000. The figure is a projection of the number of automobiles the customer is likely to purchase over his or her lifetime, as well as the services those automobiles will require over a lifetime.”

Take that number and extrapolate based on the average margin on sales and service for any other car, and you should get pretty close. Looks to be somewhere around 6x – 8x the original purchase price, perhaps?

Continue reading LTV of Car Buyers →

RFM and Customer LifeCycles

Analytical Culture, Analytics Education, Customer Experience, Digital Analytics, 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.

Today we have a bit of confusion between RFM modeling and tracking Customer Lifecycles. Each has benefits and downsides, but the most important idea is to make sure you know what each is best at. Make sense? Let’s do the Drillin’ …

Q:  I have a small sampling of the RFM scores that correspond to the various lifecycle stages.  For instance, 111 & 112 correspond to the acquisition stage, 333 & 443 to the growth stage, etc.  However, I’m looking for a complete listing of all 125 possible RFM scores and their corresponding lifecycle stages.

Can you please send this my way?

A: Wow, I certainly hope you didn’t get this idea from me; if you did, I have done a terrible job of explaining something somewhere. I would be very interested in the source of this idea, that a LifeCycle stage can correspond to a single RFM code or score.

An RFM code or score is the ranking of a single customer against all other customers for likelihood to respond and future value at a specific point in time. High scores equal high future value; low scores equal low future value.

A single RFM score represents this ranking at a fixed point in time – the day the scores were created. There is no “cycle,” which implies “over time,” inherent in an RFM code. Only if you knew the previous RFM code or sequence of codes could you imply a “LifeCycle stage”. This is, of course, what my book is about – using a modified version of RFM to track and profitably act on customer LifeCycle behavior. If you know the LifeCycle, you can predict behavior. If you can predict behavior, you can dramatically improve marketing ROI.

Continue reading RFM and Customer LifeCycles →

The Cost of Queuing Customers

Analytical Culture, Brand Management, Customer Experience, 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.

If customers have to “wait” for service, does the inconvenience / possible frustration impact their value? Great question; problem is, most businesses don’t know how to answer it in a way that will be meaningful to the value of the business. You know our Drillers though, they’ll get about it with actionable results in mind. On to the Drillin’!

Q:  Are you familiar with (or can you refer me to someone who is familiar with) customer satisfaction around queuing up for service?

A:  This is a Frequently Asked Question for sure, and not one there is a lot of statistically believable data on…at least that people are willing to release.  Kind of a sensitive subject, as you might think…

Q:  I work for a large bank.  We have perceived queuing problems in some of our branches – generally due to layout restrictions. I say perceived because although a queue is long, it moves fairly quickly with the actual wait time to see a teller often less than 5 minutes (considered at par with our competition). 

However, customers grumble when they walk into the branch and see the line and continue to grumble out loud until they reach the teller  and then continue to communicate their dissatisfaction to the teller.  Do you know if any work has been done in this area with other large companies that tend to have long queues (like airline ticket counters, large retailers)?

Thanking you in advance for your response.

A:  I think this issue can be an illusion; let me tell you what I mean. 

For e-commerce, somebody like Gartner does a survey that says people hate shipping charges, and every web site kicks in “free shipping.”  Guess what? People have always hated shipping charges since 1850 when the catalog business started.  And why not?  It looks like extra cost to the customer.  But if you run your business correctly, you price with shipping in mind and manage costs so that you still make a profit.

Continue reading The Cost of Queuing Customers →