Here are the results of a regression model ... I sum last year demand by price point, and the regression model predicts how much the customer will spend next year (in total) with the brand. The "p" variables represent different price points that customers spent money in last year ... p020 = items $10.00 to $19.99 etc.
We're looking down the "B" column ... those are the coefficients. If a customer spent $100 on items between $0.01 to $9.99, we multiply $100 by the coefficient for "p010" ... by 0.461. 100*0.461 = $46.10.
Now look at P100 ... these are items between $75 and $99.99. The coefficient is just 0.247 ... if a customer spent $100 on items between $75 and $99.99 (which isn't possible of course, but we're here to create an example), then the customer will spend 100*0.247 = $24.70 in the next year.
Which customer would you prefer?
- The customer who will spend $46.10 next year.
- The customer who will spend $24.70 next year.
It's not a difficult choice, is it?
Every one of you offers items at different price points. Some of those price points yield high-value customers. Some don't. You'd probably want to know which ones lead to low-value customers before offering next year's assortment, correct? (click here for more details).