How To Specifically Calculate Merchandise Productivity

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.
• Affiliates.
• Comparison Shopping Engines.
• Mobile Phones.
• Tablets.
• Social Media.
• Email Marketing.
• Stores.
• Specific Stores (i.e. Bellevue Square).
• Outlets.
• 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.

E-Commerce And Catalog Management Case Study: Comp Segment Performance

Please click on the image to enlarge it.

We recently discussed how business leaders can improve business performance by focusing on key metrics like Final Fulfillment, Return Rate, Gross Margin, and Pick/Pack/Ship expense.

The catalog/e-commerce CEO sets objectives designed to drive improvements in these metrics.

Next, the business leader focuses on understanding if customers are truly spending more, or have curtailed spend over the past several years.

"Comp Segment Performance", something I learned about at Eddie Bauer back in 1996, is one of the better ways to analyze this issue. And there are an infinite number of ways to look at comp segment performance.

The process generally involves finding a segment of good customers, those in the top 25% to 35% of your customer file. Once you identify the segment, compare metrics like repurchase rate, spend per repurchaser, total revenue, and total profit on an annual basis, over the past five years.

Conversely, look at campaign-based catalog metrics like response rate, average order size, dollar per book, and demand per thousand pages circulated across a comp catalog over the past five years. In e-mail marketing, review open rates, click-through rates and conversion rates in comparable campaigns over the past five years.

In our example, management chose to look at annual metrics. Here is what total revenue looked like (indexed so that 1.00 is average):

• Five Years Ago = 1.00
  
• Four Years Ago = 0.90
  
• Three Years Ago = 0.97
  
• Two Years Ago = 1.05
  
• One Year Ago = 1.00
  

Notice that comp segment performance was roughly "average" last year. In other words, even though the brand experienced a terrible year, actual customer productivity is "average".

This suggests that the CEO does not have a serious merchandise issue to address. The CEO needs to focus on key operational issues, or needs to carefully review the marketing/advertising investment strategy.

Comp Segment Performance is an important component in the catalog/e-commerce CEO toolkit. All business leaders should have comp segment performance metrics readily available, produced on a monthly basis.


Homework Assignment: Review the following series of metrics. Which metric seems to have a disproportionate influence on the profitability of our brand?

	Demand to	Comp	Marketing	Profit /
	Profit	Segment	Expense	EBT
5 Years Ago	0.269	1.000	$3,000,000	$660,529
4 Years Ago	0.235	0.900	$3,150,000	($315,375)
3 Years Ago	0.219	0.970	$2,235,797	$63,008
2 Years Ago	0.235	1.050	$2,013,020	$550,175
1 Year Ago	0.244	1.000	$3,780,004	($258,027)