Category Archives: Analytics Education

Segment to Best Determine LifeTime Value (LTV)

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.

LTV has to be actionable.  If  you can’t take action on the information, it’s not relevant anyway.

There you go, the most universally true rule when attempting calculation of LTV.

And the best / easiest way to accomplish this is to identify similar customer behaviors and segment the customers by these behaviors – THEN figure out LTV by segment.

If you can’t actually take action on the information, then why spend countless $$ and hours fussing over all the reasons the number you come up with might be wrong and trying to solve unsolveable data or corporate issues? The best idea to implement when developing / using LTV is consistency – let’s get the team to agree on what LTV is and how to measure it, stick with those ideas for at least several years, test and take action on the results to uncover value, THEN (perhaps) discuss improvements!

Q:  I have just been reading your series on Comparing the Potential Value of Customer Groups. I am having trouble calculating the lifetime value of our customers.

A:  Yes, well, everybody does for some reason!  Often the problem is too much
focus on trying to look at the “average customer” as opposed to segmenting
customers.  By segmenting first, it’s both easier to get to LTV *and* more useful since it’s easier to take action on  a segment than the “average customer”.

Q:  Our company provide accounting software solutions to small to medium sized owner operated  businesses.  Because of what we sell and who we sell to, a lot of our customers are most likely to just buy one or two of our software products and unless they sign up for support (only around 15% do), we may never here from them again.  It is therefore very difficult to determine an average / standard lifetime that customers use our product.

A:  Sure.  First, the 15% segment that does sign up for support sound like good customers to me.  So that’s one segment.  How long do they typically stay signed up?  That’s the average life for this segment.

Then there are probably people who upgrade over time, right?  I can’t imagine an accounting product that people would not upgrade – perhaps not every cycle, but every 2nd or 3rd cycle.  That’s another segment.  Then there are probably some who both follow the upgrade cycle and pay for support.  These are probably the “best customers” and they are a unique segment as well.

And finally, you have the buyer who makes one purchase and you never see again.  These people are also a segment.

Q:  What should I base it on, how long our customers use our products (which would be almost impossible to determine), or how long they spend money with us?  So I measure on average the time between the first and last transaction of customers who have the highest Recency???

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When Acquisition Spoils Retention

Analytical Culture, 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.

OK, here’s a bit of a tough one – what if while investigating customer retention problems you find out that customer defection is highly correlated to specific salespeople or marketing programs? What if I told you this correlation is pretty common – but unrecognized, because hardly anybody goes looking for it? And if found, find trouble doing something about it?

Two issues – you can try to predict / save a customer in the process of defecting, and / or you can hunt down / fix the source of the defection – why is it happening in the first place?

Welcome to the politics of customer retention – and make sure to put your Drillin’ shoes on …

Please note: XXX is a major cell phone provider…

Q:  I’m an XXX customer – I saw an ad for a new phone I wanted for $230.  I went in to the XXX store and asked for the phone – the clerk rang it up at $580!! I showed him the ad.  He said that price is for new customers and he could not give it to me at that price.  So it made me feel that XXX did not value my business.  I then cancelled with XXX service and have told about 10 people about this situation.

A:  Right, this is a pretty common problem with companies that don’t understand
customer retention.  They’re so focused on acquisition that they cause defection and that’s where a lot of the churn in that particular business comes from.  I’d chalk it up to totally clueless marketing management.  

The irony of this situation:  XXX used to be one of the “gold standard” 1-to-1 marketers in the good ‘ol days.

In the first place, companies should not “broadcast” these kinds of offers, because you understand the impact, the leverage, the “costs 5x as much to acquire a customer as retain one” and so forth. If you want to make offers like that, you try to use discrete channels – direct mail and so on, as opposed to newspapers or radio / TV. The strategic issue is people are defecting at such a high rate the company thinks they need to really drive acquisition to make up for it instead of concentrating on retention, which would be less costly and more profitable overall. But even worse, these aggressive acquisition programs are actually increasing the likelihood of customer defection!

Continue reading When Acquisition Spoils Retention →

How to Define “Frequency” Metric in B2B

Analytics Education, Customer Experience, 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.

If you’re not really clear on what you’re trying to accomplish, designing a successful customer retention program can be a bit of a struggle. Hey, maybe you just don’t know what to look for / what needs fixing / where to start? Gotcha, fellow Driller, the current value / potential value matrix is a great place to start – for you, and perhaps more importantly, your boss / the CFO. Ready to try on some focus? Let’s get to the Drillin’ …

Q:  I am totally getting into your book.  I am up through chapter 17 and have completed my RF Scoring.  My company [my day job] is a custom software company.  It was difficult for me to get my head around the units thing yet, so I just used the “M” as you put it.

A:  Thanks for the kind words, I’m glad it’s working for you!

Q:  In term of companies, we are probably like the B2B example you used in Chapter 8.  So, I could not get my head around the units deal yet because I have not studied the data enough to see if there is a progression.  I think I would need to look at it year to year; but should I stop now and do it first?

A:  Well, customer analysis always starts with an objective…what are you trying to look at / prove / do?  It’s hard to comment without knowing the business problem or issue you are facing…and without any information on how your business really works.  I can rarely find that out from looking at a web site…

“Units” would probably be the total number of “jobs” you have completed for a client.  It also could be the total number of hours the client has used, if that is more logical for the business.  It’s hard to tell without a bit more information.  The point of the “units” variable is to look at the Frequency of commitment, so use whatever makes sense for the business.

Q:  So, my question is, should I go back and do what you suggest in chapter 9 – setting up a look at Latency by customer to get the progression before I continue with Chapter 18.

Continue reading How to Define “Frequency” Metric in B2B →