Pricing for Lifetime Value

How do you price to maximize the lifetime value of a customer? What an interesting question.  In its simplest form, the issue comes down to customer capture and customer retention.

What does it take to capture a new customer?  Of course when we price a product we only have a probability of winning each deal.  The lower we price the product the higher the probability that we win.  If this is a one-time purchase, meaning that selling this one doesn’t make it more likely to sell the next one to the same customer, then we would simply choose the profit maximizing price using the models as we always do.

However, if we believe that capturing a customer makes it more likely to sell another unit later to the same customer, then it is in our benefit to lower our price so we can win more customers up front.  We often see special rates to new subscribers for satellite TV service, or cellular phone service.  These are services where they can determine if you are a new customer or not.  And once they have you, they really lock you in (for 2 years).  We also see prices as low as free to capture new customers.  For example, free samples of products or free trial periods of software.  The more likely you are to sell another unit to the same customer, the lower you will set your customer capture price.

Our customer retention price works the same way, only it is slightly higher.  We are assuming now that we have some “loyalty”, meaning the customer is predisposed to purchase our product over our competitors.  That is why we gave the discount on the customer capture price.  This means that we could get away with charging a higher price than we would if the customer were making a first-time decision.  After all, we should be able to capture some of that loyalty.   When we set this customer retention price, some customers will buy and some won’t.  We may be tempted to select the profit maximizing price for this decision.  But note that we are in a similar position as we were when setting the customer capture price.  If we win a customer, we have a higher probability of winning him again.  This gives us extra incentive to lose fewer customers, motivating us to price lower than our profit maximizing price.  This price of course is going to be higher than the customer capture price, but not as high as it would be if we knew this is the last this customer will purchase from us (or give us loyalty).

What if you could segment loyal customers from those that make stand-alone decisions every time?  The above logic implies that you may want to give your loyal customers lower prices, because that keeps them coming back.  Restaurants like Subway that offer a buy 10 get 1 free card are doing exactly that.  They offer their loyal customers a 10% discount (actually 9% but who’s counting?) while the non-loyal customers pay full price.

The real answer though is it depends.  It is very possible that the loyalty is so high that you may be able to charge an exorbitant price to most of your repeat customers while losing only a few.  In this case you would charge them more than a non-loyal customer if possible. Yet I can only think of three conditions where you could get away with this:  1.  the customer is ignorant of other rates and just keeps on writing the check;  2. the customer is somehow locked into the deal, like a cell phone contract;  and 3. the customer faces some very high switching costs (similar to 2).  In the absence of one of those three conditions, you should set your loyal customer price lower than (or equal to) your non-loyal customer price.

Summary – Without going through any complex math, our logic produced the following generalizations.  For customers who are more likely to make a repeat purchase, charge a lower price to capture more of them initially.  For their repeat purchases, charge more than the capture price, but less than what you would charge a non-loyal customer.