The overwhelming theme from your feedback over the past day is this:
- Please show me how to calculate Merchandise Productivity.
Here, then, are the specific instructions for how to calculate Merchandise Productivity for April 2016.
Step 1 = Select all customers who bought exactly two times between April 1, 2015 and March 31, 2016.
Step 2 = Calculate the average amount spent by this audience between April 1, 2016 and April 30, 2016 (include all of those who did not buy from 4/1 to 4/30 in your calculation). Pretend this amount is $11.00.
Step 3 = Select all customers who bought exactly two times between April 1, 2014 and March 31, 2015.
Step 4 = Calculate the average amount spent by this audience between April 1, 2015 and April 30, 2015 (include all of those who did not buy from 4/1 to 4/30 in your calculation). Pretend this amount is $10.00.
Step 5 = Your comp segment measure is ((Step 2 / Step 4) – 1) = ((11.00 / 10.00) – 1) = 10%. This means that in April 2016, your merchandise productivity is 10% better than in April 2015.
Step 6 = Repeat Step 1/2/3/4/5 for each month you wish to measure merchandise productivity, sliding the window back a month for March, then back another month for February, and continue back as far as you like.
I like to run these analyses with "numerous dependent variables". Instead of total sales, as outlined above, I will modify Step 2 and Step 4 (not Step 1 and Step 3) for the following:
- Phone Transactions.
- Paid Search.
- Organic Search.
- Comparison Shopping Engines.
- Mobile Phones.
- Social Media.
- Email Marketing.
- Specific Stores (i.e. Bellevue Square).
- New Items.
- Existing Items.
- Each Product Category.
- Low Priced Items.
- Average Priced Items.
- Expensive Items.
- Items Purchased Via Free Shipping.
- Items Purchased Via Discounts/Promotions.
- Items Purchased Via Liquidations/Clearance.
- Fashion Items.
- Basic Items.
Ok, what questions do you have? About a third of my consulting projects surround the methodology above. 80% of the time, I am able to identify a merchandising issue that is holding the business back, so the methodology works well.
I also like to run the analysis, going back about four years, allowing me to create comp segment metrics for the past three years (on a year-over-year basis). The trends allow me to see when specific issues arise ... it is very common for issues to arise at the start of a new season when a new merchandise assortment is introduced.