# How To Calculate Lifetime Value – The Infographic

One way to analyze acquisition strategy and estimate marketing costs is to calculate the Lifetime Value (“LTV”) of a customer. Roughly defined, LTV is the projected revenue that a customer will generate during their lifetime. In this graphic we’ll briefly cover how to calculate LTV and how to use LTV to help solidify your marketing budget. Special thanks to @avinash.

Click on the image below to view an enlarged version of this infographic.

## Want to display this infographic on your site?

Simply copy and paste the code below into the html of your website to display the infographic presented above:

20 years as average customer lifetime is a lot! now I can see with numbers why Starbucks is a very successful company. Very interesting! Thanks for sharing.

Hi Judit:

Great point – Starbucks does have an amazing customer retention rate. Just goes to show – focusing on customer satisfaction goes a long way!

It’s great that you give a practical case of LTV calculation in addition to explaining how and why it is useful for marketers and businesses, but your conclusion seems bogus to me.

You calculate 3 types of customer lifetime value:

- Lifetime revenue

- Future Value of Lifetime profit (no discount applied)

- Present Value of lifetime profit (discount applied)

Then you average them to $14,099 and conclude:

“Starbucks must spend less than $14,099 to acquire a customer”

Well if you were concerned about acquisition cost, you should have kept the profit calculation. Assuming Staburcks makes $5000 profit out its $25,000 lifetime revenue, they incur a cost (cost of goods sold if you like, all the costs except marketing) of $20,000 to which you will add the customer acquisition cost and this should not exceed $25,000 to break even. Thus, acquisition cost It should be below $5000, not 14099. You cannot average revenue and profit, profit is a share of revenue.

Same goes for profit and discounted profit. If you’re taking the Present Value of future profit, it’s just a weighted representation of profit, which you cannot average with profit, which is again, a part of this equation.

I’m no maths or finance teacher, so I don’t know if I made my point clear… basically what I see here is:

(The size of a forest + the size of a tree today + the size of a tree when he will be fully grown) / 3 = the maximum size of a leaf

Clearer? maybe not =D

Hi Briac:

Thanks so much for the comment – definitely appreciate your pointers! I think your math is very insightful – certainly helps to clear the waters a bit.

There’s lots of little ancillary factors that go into calculating LTV – too many to include in a small infographic. Additionally, the purpose of the infographic was not so much to give a precise LTV to an average Starbucks customer as it was to simply illustrate a (simplified) method of calculating LTV – and how LTV can be useful when putting together a marketing budget.

From our research, we estimated that the LTV of an average Starbucks customer was roughly between $5,400 and $25,000, as illustrated in the infographic. Consequently, the break-even range for Starbucks’ marketing budget per customer lifespan had to be less than $25,000 (high estimate). Any number less than $5,000 is less than $25,000, so a marketing budget of less than $5,000, as you mentioned, would probably be more accurate.

Again, we’re working with rough estimates. :)

I would probably not average all 3 LTVs and just pick the lower figure to keep my calculations on the conservative side.

I suppose the downside to that is you might not be throwing enough money at customer acquisition as you should, but I figure when you’re starting out you might want to start conservative until you have a better feel of what’s working and what’s not.

The wide range of results from the different formulas, small sample size, and some of your assumptions about customer retention rate, profit margins, etc. were questionable. Briac, above, has some good points as well. Nevertheless, it was a fun exercise, and the variables are things that all new ventures should consider as they talk with investors.

FWIW, I used a different set of values for r (60%), c (2) and t (10) and ended up with an average LTV of $3,046.

I 100% agree with Briac. Averaging the LTVs makes absolutely no sense. Those metrics are measured in different ways for different purposes. Would it make sense to average daily unique visitors with monthlies? Each represents something distict and aren’t meant to average together.You should pick the ONE LTV that suits your particular business need.

Great work, very useful information!

Calculations here are flawed: in addition to the mixing of revenue and profit (mentioned above), there are 2 other issues I see at a glance:

1) There’s a functional relationship between customer retention rate and life time of a customer. You can’t assume 75% retention and 20 year relationship. That’s what the (r/(1-r)) term in the third LTV equation is: the expected number of periods that a customer sticks around, given that they drop out at the rate of (1-r) per period. So, the expected number of years for 75% retention is (.75 / (1-.75)) =4.

2) Since the third equation is (correctly) accounting for the expected number of years and then multiplies that by the profit, it should be profit *per year* not *per “lifetime”*. In the example above, that means the final value will be about 1/20th of what you calculated. (assuming the 75% retention rate, avg annual spend, and discount rate given).

Steven is right. As soon as you average the revenue and the profit, this methodology implodes. Nice graphic though, you should adjust and republish.

We use the following

Churn = (Current + New – Previous customers)/Previous

Lifetime = 1/Churn

ARPU = Revenue/Current Customers

Referrals per customer = k

kLTV = 1/(1-k)*Lifetime*ARPU

Note that s*c ~ a so the difference between simplified and custom is one is total revenue and one is profit.

I have noticed that smart real estate agents all around you are starting to warm up to FSBO Promotion. They are acknowledging that it’s more than merely placing a sign in the front property. It’s really about building associations with these dealers who sooner or later will become buyers. So, whenever you give your time and effort to aiding these vendors go it alone — the “Law involving Reciprocity” kicks in. Interesting blog post.

I really appreciate the effort that went into producing this infographic. I assume that in order to determine what the average lifetime span of a customer is, it really comes to basic business knowledge and market intelligence?

Amazing Info graphics. Will have to pore over it once again to get the grasp of it!!!

Hy

Excellent post man!

Thanks for sharing,keep on posting.

Its really easy to understand the LTV through your post.its really helpful for every one.

Thanks

I am sorry to write this, but at least one of the LT methods above is bullshit. I’d say the first and the third, because they don’t take the margin into account but use only the revenue. In fact, second method is the same calculus as the first, just multiplying with p.

Actually, Starbucks shouldn’t spend more than $588 to acquire each customer. Based on the numbers provided in the infographic the LTV is $588. The three formulas used are partially right and partially wrong. This is how I got the $588 as the LTV for Starbucks:

(52 x s x c x p) x [ r / (1 + i - r)]

(52 x 5.90 x 4.2 x 0.213) x [ 0.75 / (1 + 0.1 - 0.75)] = $588.12

What’s wrong with the formulas/calcs in the infographic?

1) It’s not including any cost….it should be profit (excluding marketing).

2) It’s not taking into account the value of money along the time….the formula should discount anual profits ($274.45) for 20 years.

3) The “m” used is incorrectly including the profits of 20 years. The “m” should be the profit of one year (in average if you prefer). The other bit of the formula is called the multiplier factor, and it basically discount perpetuity profits (m) at 10% discount rate plus taking into account the churn effect.

Hope this is helpful. If you believe I’m missing something, please, let me know.

I think a great follow up post would be host to calculate the “constants.” I would like to hear the rational behind how they calculate customer retention and average life span.