Tag Archives: Customer State

Second Purchase Marketing

Analytics Education, Customer Experience, DataBase Marketing, Digital Analytics, 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.

HIgh end hardgoods. One of the most difficult retail categories to deal with from a customer retention perspective, both offline and online. Only vehicles are tougher. In some ways, the category can be easier online, but perhaps not for a single local store due to competition. So what’s the best way to attack the repeat purchase peoblem? Focus on where you have the highest likelihood of success – 2nd purchase Latency. Ready for the Drillin’?

Q:  I loved your book, thanks.  Armed with it, I feel like I can achieve much more than most small retailers in terms of CRM.

A:  Thanks for the kind words!

Q:  I have a question though.  I sell relatively high-priced furniture and design items, and as this is our first year of business, our inventory is pretty small.  As a result, my Frequency totals range from 1 to 4.  That’s it, after a year of business.  About 75% of our customers have bought once and it “ramps up” to 4 from there.  I use “ramp” in the broadest sense of the word.

A:  Yep.  That’s the hardgoods business, especially on the web.  Don’t beat yourself up, it’s early in your game with lines like these, and don’t blame it too much on inventory either.  In the long run, it’s better to sell the *right* stuff than everything you can find, trust me.

Q:  So when I compute RF quintiles, the totals don’t cleanly fit within quintiles.  In other words, for RF scores of X1 ­ X4, customers have purchased once.  X5 customers have purchased 2, 3, 4, or 5 times.  If I raise the hurdle and only look at customers who have purchased more than once, I still can’t fit them cleanly in five quintiles.

A:  That’s one problem with RFM, it’s a bit robotic and works best with larger (usually meaning older) databases…

Q:  I read your article on durable goods purchases and avoiding the one-time-buyer problem.  I guess I’m looking for advice on how to make the “F number” significant until we’ve been in business long enough to get a broader range of frequency options.

Continue reading Second Purchase Marketing →

Using RFM Scores to Predict Profits

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.

Subsidy costs. You’re just starting to hear people talk about these ideas in online marketing, but they’ve been around for years offline in direct marketing. The basic idea is this: sending a discount to someone who is very highly likely to make a purchase without the discount is a waste of margin dollars best spent elsewhere. And you can measure this effect quite easily using Control Groups, another concept starting to get some recognition with online marketers.

Discussing / implementing these topics can be a bit difficult, though the Finance people will get it immediately and love it if you go in this direction. A plus for fellow Drillers out there is you can start to see some of these ideas in action BEFORE you start going deep using the RFM & Lifecycle data we’ve been talking about and using for years.

Below is a great example using RFM data from a fellow Driller. You ready to go ?

Q:  Since our last conversation few months ago, we went ahead and tested 3 different promotions using the RFM model.  

The 1st promotion was the test for RFM method itself to see what patterns emerge for response rate, incremental sales, etc.  The next 2 promotions targeted the customers from RFM cells with the highest incremental lift from the 1st test promotion.  Here is what we saw.  Since the targeted audience were our loyalty card members, they transact and spend at a fairly high level (the data below is modified but the trend is maintained).  For the response rate, we saw a sawtooth pattern:

(Jim’s note: RFM is the 3 digit score, Rate is Response Rate.  More on RFM here and here.)

A: Yes…

Continue reading Using RFM Scores to Predict Profits →

How Long is a Customer LifeTime?

Analytical Culture, DataBase Marketing, Driller Q & A, Marketing Research, 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.

There’s always two questions about the topic of Lifetime Value – how do you quanitify value, and how long is / how do you measure / decide what a Lifetime is? For now we’ll leave the value question unanswered, because a lot of that depends on company culture and what question you are trying to answer. Plus, it depends on how you measuree a Lifetime.

So let’s do the Lifetime thing first, shall we? To the Drillin’…

Q:  First of all thanks for an excellent web site – I often visit it to learn and / or get inspiration in my work.

A:  Thanks for the kind words!

Q:  Anyway, I work in a telco retention department and I’m trying to calculate a true and fair value for customer life time answering the question : “How long do we on average have a customer?”.

A:  A both noble and useful pursuit!

Q:  I have data on when customers signed up and when they left (or of course whether they are still here). My first problem is whether to include both lost and existing customers in the calculation.  If you only include the customers you lost you are only able to answer the question for those.  If you include existing customers you don’t know what life time to use for them.

A:  Well, yes, that’s correct.  But you’re really trying to accomplish several things at the same time, so you can break the analysis into different parts and then apply some business logic to get your answers. 

Continue reading How Long is a Customer LifeTime? →