Impact of a Loyalty Spoiler

When all things are equal, it's important to not focus marketing activities on Loyalty Spoilers.


Here's an example that I ran on a recent dataset:

• An item sold 400 units last year in Q4, at a price of $49.
• Customers who purchased comparable items repurchase at a 20% rate.
• Customers who purchased this item repurchase at a 15% rate, though equal in every other manner to customers buying other products.
• Each customer who repurchases is worth $150 in the next three months.

So, you earn $49 * 400 = $19,600 by selling the item.

Then the item spoils loyalty, costing you the following:

• 400 * (.15 - .20) * 150 = $3,000 of future demand.

The net productivity of the item, then, is not $19,600 ... but is $19,600 - $3,000 = $16,600.  You run a profit and loss statement on the current value of the item and the future value you either spoil or build.

Make sense?

Good!

Now go out there and run a Loyalty Spoiler analysis (hint --- email marketing is the best place to start, it is so easy and straightforward here).

If you don't have the resources to run your own Loyalty Spoiler analysis, contact me (click here)

Loyalty Builders and Loyalty Spoilers

If you can have a Loyalty Spoiler, you can have a Loyalty Builder.


Loyalty Builders are the opposite of Loyalty Spoilers.  Loyalty Builders cause a customer to continue to buy merchandise in the future.


Think about your inkjet printer.  When you buy the item from HP for $125, there's an inherent "Loyalty Builder" aspect built into the item ... you're supposed to come back, over and over and over again, and buy ink cartridges.  The inkjet printer is a Loyalty Builder.


Your iPhone is a Loyalty Builder, a tool that allows Verizon to keep making money on a monthly basis, a tool that allows Apple to sell apps.


Your Lexus Rx400h is a Loyalty Builder, a car that requires oil changes, transmission oil changes, differential trans axle oil changes, new tires, tune ups, wiper blades, you name it.


Conversely, some items are Loyalty Spoilers.  You'll routinely see how a new couch, purchased at Ikea, stymies subsequent purchases, and for good reason!  That couch completes a purchase cycle, the customer is done!


The secret, then, is to identify your Loyalty Builders and your Loyalty Spoilers.  In your email marketing campaigns, in your search marketing campaigns, on key landing pages, you give Loyalty Builders more priority than you give Loyalty Spoilers.


Oh, I know, merchants are going to howl over this one.  "If we don't tell the customer about an item, then the customer won't buy the item, blah blah blah."


But if you're reading this, you're most likely a marketer or an analyst.  This means you have a responsibility to increase loyalty, correct?


So, when all things are equal, advertise the Loyalty Builder.  Make the Loyalty Spoiler available and easy to find, but there's no need to feature an item that kills subsequent performance.

Loyalty Spoilers: Merchanics

Here's one approach to running a Loyalty Spoiler analysis.


Step 1:  Identify all items sold in 4th quarter of 2011.


Step 2:  Identify all customers who purchased merchandise in the 4th quarter of 2011.


Step 3:  At the end of the 4th quarter of 2011, calculate the future value of all customers who purchased in the 4th quarter.  Many folks will predict future value as the demand you expect this customer to generate in the 1st quarter of 2012.


Step 4:  Measure the repurchase rate (you can measure $/customer as well, it's just noisier) of all customers who purchased in the 4th quarter of 2011, measuring repurchase rate during the 1st quarter of 2012.


Step 5:  Create a spreadsheet, one row per customer/item combination, containing the following fields.

Step 6:  Aggregate the dataset to one row per item number.  Calculate the mean value of predicted customer future value.  Calculate the mean value of Q1 - 2012 repurchase rate.


Step 7:  Select all items that sold at least 50 units in Q4 - 2011.


Step 8:  Run a weighted least squares regression analysis.

• Independent Variable = Average Predicted Customer Value.
• Dependent Variable = Q1 - 2012 Average Repurchase Rate.
• Save the Predicted Value = Predicted Average Repurchase Rate.

Step 9:  Create an index (this step is important):

• Index = (Predicted Average Repurchase Rate) / (Average Repurchase Rate) - 1.

This index is a percentage.  It tells us how much an item spoils future customer loyalty.

For example, an item that has customers with an average predicted future value of $100 should yield an average repurchase rate of, say, 20%.

Now, let's say that an item instead yields customers with an average repurchase rate of 15%.  The index, then, is (15% / 20%) - 1 = -25%.  This item spoils future customer loyalty by 25%.

In the next post in this series, we'll address a practical outcome of the methodology.

Loyalty Spoiler

You are probably running your own Loyalty Spoiler analysis, right?


A Loyalty Spoiler is an item that sells well, but hurts the downstream loyalty of a customer.


You'll see this analysis in email marketing.  You want to prop-up the performance of an email marketing campaign, so you feature a half-dozen items that will sell well.


You read the results, you generate sales, and then you move on.


In a Loyalty Spoiler analysis, we measure the downstream loyalty of customers who purchased specific items.  If, after controlling for the quality of the customer purchasing an item, we find that equal customers perform worse after buying a certain item, then the item is a Loyalty Spoiler.


We'll talk about this topic in upcoming posts.