So this is kind of fun!
If you can run a regression equation for one year, why not run one for each of the past four years? This allows us to compare how customer spend in one price band is impacted over time.
In this comparison, I evaluate a customer spending $200 last year on items only in the $0.01 to $9.99 price band. Over time, customers are becoming less valuable:
- 2016 Customers = $113.83 next year.
- 2017 Customers = $106.99 next year.
- 2018 Customers = $109.50 next year.
- 2019 Customers = $103.86 next year.
You're seeing the impact of merchandise productivity ... and it's not pretty, is it?
We can run a comparable table for other price points ... how about $50.00 to $74.99?
The relationship is different, isn't it? There are productivity gains in each of the past two years at this price point.
Granted, the customer is less valuable. But the customer is becoming more valuable.
So the key, I suppose, is this:
- Is the company shifting toward higher price points over time?
- If so, is the mix away from lower price point items into higher price point items good for customer loyalty?
We'll answer that question tomorrow.