Ok, here's a query for you. We take all customers and segment them based on life-to-date purchases. Then I select customers who place "average" average order values. Finally, I segment customers based on percentage of historical demand spent on items at/above the historical average price point of the item. Within the cells of the resultant query table, I measured the percentage of future (next 12 months) sales from items selling at/above their historical average.
Tell me what you observe.
The table illustrates key findings:
- Once you train a customer to bargain hunt, the customer bargain hunts.
- When you train a customer to pay full price, the customer is more likely to pay full price in the future.
- 70.4% of future sales are from items at/above their historical average.
- 82.4% of future sales are from items at/above their historical average.