## September 02, 2019

### Item Price

You have an item. You offer the item at \$100. There are several possible outcomes for the trajectory of the item.

• The item sells at full price, no promotions.
• Promotions (30% off, 40% off) impact the real price the customer pays for the item.
• The item doesn't sell well, and is systemically marked down until it is part of your clearance assortment, selling for \$40.
Now, there's lots of ways to analyze this item, so I'm not telling you what the "right" strategy is.

But at least consider this. Let's say that the item sold for the following amounts, after factoring in promotions.
• January = \$100.
• February = \$100.
• March = \$70 (30% off promo).
• April = \$80 (20% off promo).
• May = \$60 (40% off promo).
• June = \$50 (clearance).
• July = \$40 (clearance).
For the sake of simplicity, let's assume that the average selling price of this item is an average of each month ... (100 + 100 + 70 + 80 + 60 + 50 + 40)/7 = \$71.43.

Now let's look at our monthly distribution.
• January = Above Average.
• February = Above Average.
• March = Below Average.
• April = Above Average.
• May = Below Average.
• June = Below Average.
• July = Below Average.
If you create a new variable in your database called Above_Below ... where for each customer and each item you designate if the item purchased was sold at Above Average or Below Average the historical item price average ... well, then you've got something interesting!!!

More on the topic tomorrow.