Calculate Customer Lifetime Value

Occam's Razor 
by Avinash Kaushik
Digital Marketing and Analytics Blog

Excellent Analytics Tip #17: Calculate Customer Lifetime Value

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Some Marketers / Analysts use Click-thru Rate (CTR) to measure success of their acquisition campaigns. Nothing much to write home about, but certainly better than executing faith based initiatives.
A smaller percent of those Marketers / Web Analysts will move beyond clicks and measure Visits / Visitors and Bounce Rates to measure success. Lovely, warm hugs and smiles for them.
A fraction of those Marketers / Directors will calculate Conversion Rates for those marketing campaigns. They deserve our love. [And if they measure Micro Conversions they deserve our love AND respect for exhibiting savviness by using economic value.]
But all of the above is still focusing on short term success. Even measuring Visitor conversion rates (Visit based conversion rates promote bad marketing behavior) is akin to declaring success after a one night stand.
I reserve the best hugs, kisses, smiles, love, respect and my deepest admiration for Marketers and Analysts who use Lifetime Value computations!
That is focusing on real success, not simply the first conversion (the one night stand!).
That is focusing finding the customers that create value for the company, long term.
That is truly doing the kind of Analysis Ninja work that solves tomorrow's problems today!
For the above reasons I have been meaning to write a post on computing Lifetime Value for a very long time. But perhaps a better idea is to get an expert to do it, the result will clearly be far better than anything I would write. So I emailed my friend David. : )
David Hughes is the Co-Founder of the email marketing consultancy called The Email Academy and the author of one of my most beloved phrases: Non-line Marketing! His blog, Non-line Blogging, is a favourite of mine.
There are a handful of people in the world I could spend the whole day talking work and still have things left over to discuss, to learn. David is one of those super-smart, funny, and nice people. I have consistently found his ideas to be practical, grounded in common sense and instantly useful.
I could not be more thrilled that he agreed to cover this tough, yet rewarding, topic.
In this post David covers:

• Why Life Time Value is important (especially in context of Acquisition)
• How to optimally leverage value based segmentation & Lifetime Value
• Share a sample analysis and, this is so sweeeet, a spreadsheet with a sample model that you can use to jump start your own LTV journey!

Buckle up, this is going to be fun and it just might change your life! :)
Here's David. . .

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Solve tomorrow's problems today – introducing Life Time Value.

Acquiring new customers isn't getting any easier: We've picked off the low-hanging SEO fruit, we're paying more for quality clicks in AdWords and the going rate for affiliate deals just keeps getting higher.
We are also haunted by the specter of "marginal cost": The more customers you need, the more impressions and clicks you need. But as we drill deeper into worse performing media, or pay out for lower-volume-lower-relevance search terms, our cost per sale gradually rises.
There is a better way to analyze your acquisition strategy than simply using Conversion Rates or Cost Per Acquisition (CPA). Using Life Time Value might be a much better idea.
Life Time Value (LTV) will help us answer 3 fundamental questions:

1. Did you pay enough to acquire customers from each marketing channel?
2. Did you acquire the best kind of customers?
3. How much could you spend on keeping them sweet with email and social media?

I'm going to suggest that maybe you should be paying significantly more money for the right customers.
Let's start at the very beginning…
…that's a very good place to start. Take a snapshot of your customer database for the past 2 years and it may look like this:

That is an average.
The trouble with averages is they conceal all the really interesting stuff that's going on beneath the surface.
If you look beyond the averages you'll find that some of your clients are "better than average" and some are "worse than average".
Try and segment the customer base by total purchases over a longer time period, say a year, or total spend and you may come to a conclusion that says something like:

My most valuable customers last year bought 4 times compared to an average of 2. They tended to spend 40% more than average per order. However, they might cost significantly more to acquire.

Much better than the average right?
So, where did you get the valuable customers from?
Simply knowing that you are getting lots of conversions is not enough, you might just be getting new low value customers.
This is where Lifetime Value becomes interesting: Some companies are getting really worried about the lasting impact of "buying cheap customers".
For example, in many markets the price comparison intermediary (/engines) is an easy option – you pay your money (affiliate fees) and you take your customer.
But how likely are these customers to buy another product? Or hang around for a few years? With no brand affinity there's no desire to cross-buy and maybe we're filling up our databases with low value, promiscuous customers.
A simple segmentation by channel can easily help us answer these key questions. The output may tell the following story:

But, I hear you cry, Search Marketing is labour-intensive, risky and costly compared to buying customers at a fixed price from an intermediary.
OK, so let's look at how much MORE we should be paying for Mr Right, rather than Mr Average.
Let's change the headings of the table above to be clear what we're talking about…
Best and Average customers will have different Year 1 buying patterns:

Once we have done this basic segmentation we can then factor in the cost of acquisition per segment to determine the Net Profit per customer per segment.
You'll work with your acquisition team or your finance team to get the cost data. For some of your campaigns this data might not be easily available in your web analytics tool (it is also quite likely you are doing all of this analysis in Excel).
The table you'll end up with might look like this:

It should be pretty obvious at this point that simply taking the short-term view with metrics like Cost Per Acquisition (CPA) might not be prudent since you are rewarding the source sending you Mr. Right and Mr. Average just the same. Yet they are not of the same value to your business (Net Profit!).
It is important to move away from a cost-based acquisition model to one that recognises the cross and up-sell rewards of acquiring the right customers over the duration they'll be our customers.
Spend an extra $8.00 per customer, if you have to, and you're still twice as well off than buying rubbish ones!
But we can do so much more… let's take a longer term view.
Value-based Segmentation & Life Time Value.
By now we have established this: Some of your customers are going to be spending more with you, for longer.
Let's say I am a car insurance company, or a subscription publisher, with a desire to sort out some of tomorrow's problems today.
I know that the initial cost of acquiring customers (or policies/subscriptions) will only go up as more of my competitors sail for the calm waters of "cost per acquisition" pricing.
So, if I need to sell 10,000 policies every year I have 2 options.

• Buy cheap customers and hope that a few may buy again
• Buy the right customers that stay with me for 2 or even 3 years

Without doing the value-based segmentation we'll never understand which channels bring in the best customers and that would be a terrible shame.
The ground truth is that I can re-new a policy or subscription for considerably less than buying a new one. How?
One strategy might be to spend an extravagant $1.00 of marketing costs to show my love an appreciation to our customers throughout the year via email or social media, increasing the chances they'll buy again.
That means I won't have to spend $20.00 buying a new one… a saving of $19.00 per renewal.
So if I can grow my repeat purchase rate from 20% to 40% that means I will generate 2,000 policies at $1.00, not $20.00.
That's a $19.00 savings on each of the 2,000 policies. BAM!!
Moving to a Life Time Value acquisition strategy will save my company $38,000. Not bad for a couple of days work.
Let's finish off the concepts of value based segmentation and lifetime value by going back to the original example we were working through.
If we can identify channels, campaigns, media or propositions that deliver "better than average" customers we can begin to see how much more profitable they are and decide how much more we should be spending on them.
Here's the (sample) analysis I (or you!) would do:

Ladies and Gentlemen – select your lifetime!
In the above example I've modelled a 3 year lifetime – that would be sensible for a typical consumer e-commerce player.
Publishers and financial services companies may take a longer term view… certainly off-line we have been building 5 year plans in publishing for decades.
If you're more comfortable with 6 months or 18 months, then go for it!
If you do you'll need to be looking backwards and forwards at the same time.
You may only have 6 months of on-going data for some segments, but use that as a starting point and build some simple scenarios from there:

• What if 50% of them spent 10% more in the next 12 months?
• What if 30% of them spent 40% more in the next 6 months?

Over time as you replace modelled data with real data you should be able to re-weight your acquisition spend, replacing one affiliate with another as the cross and up-sell orders begin to roll in (i.e. the customers you acquired begin to make additional purchases from you).
By rewarding the better partners / media / acquisition channels with higher CPA's you'll be building a defensive position that prevents competitors buying their way into the good sources ("How can they afford to pay THAT MUCH?!" they'll all be wondering). It will be our little secret.
Life Time Value is for Life, not just for Christmas.
We've really only just scratched the surface of LTV in this blog post.
Many people have devoted their whole careers to unlocking its mysteries so apologies to all of them for the "top level" content here.
However, it is a concept that deserves the attention of a new generation of digital marketer and it will alter the way many companies approach acquiring and retaining customers.

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Amazed?
Don't cha feel a little bad that you were making decisions about where to invest your precious marketing dollars based on either Conversion Rate or based on Cost Per Acquisition?
What's scary is that you could currently be using Conversion / Average Order Size / Cost Per Acquisition to invest more in one particular channel, all the while, unbeknownst to you, shoveling "poor quality" customers. Or "high CPA's" might have caused you to not spend enough on a channel where you can get lots and lots of high value customers.
Scary! Yet exciting that finally you can be so much smarter!!
Bonus: As a very special treat David's created an Excel spreadsheet to help jumpstart your Lifetime Value journey.
The spreadsheet has two tabs.
Comparison LTV lets you model two segments of customers by helping you walk through clearly articulated questions.
Detailed LTV kicks things up a few notches by allowing you to make better decisions by modeling out the long term performance for a given customer segment. [Create more copies of this tab to model out multiple customer segments and then compare / contrast to make wiser decisions.]
Download: Comparison + Detailed Lifetime Value Model.

[Please do not click on the link above, rather right mouse click and choose Save Link As or equivalent in your browser. Thanks.]

Closing Operational Thoughts:
I wanted to add a few thoughts about the operational things you need to worry about / keep in mind, as you revolutionize your company by using LTV:

1. You'll notice instantly that almost none of the data above is available in your web analytics tool. Not Omniture's Site Catalyst, WebTrends Analytics, Coremetrics, Google Analytics or Unica or whatever. This type of PII and financial data does not exit in these tools (often for a very very good reason).
Even the web analytics tools that say they create Lifetime Individual Visitor Experience (LIVE) profiles to compute Customer Lifetime Value (CLV) won't have the key Margin or multi-channel data, and hence not truly allow you to do the above, contrary to what might have been implied.
Web Analytics tools, even ones with lifetime visitor profiles, usually can't even stich together one person's clickstream behavior over the long term because of cookies and other data erosion issues. So plan on looking outside.
2. [Because of reasons immediately above and more...] Remember to focus not on the "Individual Customer", rather focus on the acquisition channel by analyzing segments of customers.
Individual anything ("you can track every single customer and understand every single customer and react to them in real time!!!") is over-rated.
Optimizing acquisition channels with LTV. Yea! Optimizing for Jim Sterne with LTV. Nah!
3. You'll do most of this type of analysis via your ERP / customer data storage system / financial data warehouse.
Your BFF will be the Finance team, both to initially teach you some of the financial intricacies and give you access to data you need. Look 'em up. Take 'em out for dinner. Trust me when I say that the LTV work will be a tremendous asset to your career and expose you to the highest levels of your organization. A really really good thing.
4. You are going to have to darn near sleep with your IT team/person to ensure the key meta-data required to do this analysis passes from your website to the sources mentioned in #3 above.
For example in my first job I had to request (ok beg) the corporate IT team (ok one person) to enhance the corporate system with two columns so each web order order could be distinctly identified and contain "campaign id" and "acquisition cost".
The lack of this meta-data is where most LTV efforts fail.
Even if you are a 100% web business you'll have to ensure the "backend system" that contains this key web analytics meta-data else you are doomed. Sorry.
5. If you are multi-channel company (web, call center, stores, catalogs) you'll want to ensure an equivalency exists in your backend system to [A] track the same customer's multi-channel orders correctly [B] contain cost data from all multi-channel campaigns.
This is really really hard to do. Don't try to climb mount Everest on day one. Start small and build over time. Remember David's tips on making do with just what you have.

I want you to be aware of these few valuable lessons I have learned in my own journey. I had to learn them the hard way. : )
If LTV sounds like it needs effort and love then you have understood it correctly. Everything worth it is hard in life, but if you put in the effort you'll create an enviable advantage for yourself and your company.
In closing:

1. Focus on long term success, acquiring truly valuable customers…
2. by embracing Net Profit and Lifetime Value…
3. and becoming BFF's with the Finance Team, good things will come of it!

Good luck!
Ok now your turn.
Have you used lifetime value or other such metrics to enhance your acquisition strategies? What was your experience like? If you have not used LTV, do you plan to use it now? What did you find to be of most value in this post? What would you disagree with? Did you want to run to England and give David a hug? :)
Please share your feedback via comments.