St. Patrick’s Day, Uber, and LTV

St. Patrick’s Day

This past St. Patrick’s Day, I was enjoying a pint at a South Boston drinking establishment when a couple of patrons began passing out Uber promotion cards. The card offered a free ride of up to $25 by downloading the Uber app and signing up for the car service. I struck up a conversation with one of the Uber reps. He indicated that with every successful sign-up and redemption he received $25. This all got me thinking about how Uber views its customer lifetime value (LTV) and whether this marketing campaign generate positive cash flow.

Uber

For those that are unfamiliar with Uber, it is a venture-funded startup mobile app that allows users to schedule black car pickups based on the user’s current location. Uber stores the user’s credit card payment information, which eliminates the cash payments for the ride. For this service, Uber takes roughly 20% of transportation fees.

Uber is still a young company, but it is proving to be disruptive to the taxi industry and is garnering a valuation of $3.5 billion as of August 2013. Its December 2013 revenue information was leaked.  These leaked numbers gave me the fodder to predict how much expected cash the St. Patrick’s Day marketing campaign could generate through LTV analysis.

LTV

LTV is the expected net cash generated over a customer’s lifetime. LTV is comprised of several factors: revenue per average purchase, number of purchases during a given period, the gross margin percentage, the customer retention rate, the discount rate used in the time value of money, and the cost to acquire a customer. In order to determine the LTV for Uber, I will be making assumptions based on the leaked revenue document. So let’s start!

The sheet above is data from the leaked revenue document.

First, we must determine how much money an average Uber customer generates. Based on the data, the average trip revenue is $26 (revenue divided by the number of completed trips) and the average number of trips per customer is about 2 (revenue divided by [average trip revenue times active clients]). As a result, the total cash generated over this 4 week time frame is $52 per average customer.

The next step is applying the gross margin to determine the remaining cash Uber will receive from the service. Based on Uber CEO’s conversation with Bloomberg the gross margin is 20%.

Next we calculate the rate of customer retention. This is where I took some liberties with my assumptions. I assume that the beginning clients is first period Active Clients and the ending clients is the Active Clients in period 5. I also assume 75% of Signups turn to Active Clients, which increases ending clients. With these values I apply the retention formula of Ending Clients minus Starting Clients divided by Ending Clients. The resulting the retention rate is 54%.

Now, we apply a discount rate to account for the time value of money and the risk of a venture-funded startup. In this case, we are using a 40% discount rate, as the company is a later stage start up.

The final input is the cost of acquiring the customer, which is the $25 less the gross margin for the ride, plus $25 for the sales rep’s commission.

With all of the inputs determined, we see that over a 5 year customer life, an average customer is expected to generate $137 from this marketing campaign. Not bad if they can do this million times, especially if Uber’s retention rate stays above 15%. But if the retention rate falls below 15%, Uber loses money on this marketing campaign.

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