A ‘Squinch’ Primer for Catalogers

This is part one of a two-part article.

Square inch analysis – evaluating the performance of selling space in a catalog – can be an immensely valuable exercise, if not an elementary one. It’s the process of determining the overall effectiveness of your page count, product mix and overall use of selling space.

Many catalogers who run the square inch analysis, also known as a “squinch,” don’t take as comprehensive a view of the data as they could or, more importantly, should. The fundamental techniques work for $1 million companies just the same as they do for $100 million companies.

Have an analyst do it, or at least put on your analytical hat if you do it yourself. The squinch is a data-driven analysis of how customers interact with your catalog and merchandise assortment at the transactional level. It’s a tool for your creative team and a tool for your merchandising team. But unless they are good with Excel, leave them to interpreting and applying the findings and let your number crunchers crunch the numbers.

There are always several items that must be evaluated. They include: product strength, price-point strength, category strength and page efficiency.

You also may look at sub-categories or design components or roll data up to give a broader picture of performance. But generally, an analysis of the above-mentioned four points provides vast insights into your merchandise mix and opportunities to maximize it. A thorough squinch analysis helps answer important merchandise questions, including:

• What is the optimal page count for this offering?

• What are the strongest and weakest products/categories in the catalog?

• How many items should I offer overall/within category?

• If growth opportunities exist, at what price points and within which categories should I grow?

• If the product count should be cut, which products and categories should go?

There’s a short list of data points you need to have ready to conduct the squinch. Put your data together and work from one raw data source. This will make things easier when you find that a handful of data needs updating and one change can affect several pieces of analysis. In terms of data points, you’ll need these for each item in the catalog you’re analyzing:

• Item number (i.e., SKU).

• Item description.

• Page number on which the item is sold.

• Category for the item (you may have several categories with which you can describe products depending on the business you’re in; no harm in assigning Category 1, Category 2 and so on for analysis).

• Retail price from catalog.

• Item cost (or gross margin; both will get you to the same place).

• Units sold (gross unit demand).

• Gross sales.

• Total square inches used to sell the item (including image and copy used to sell; be as precise as you think you need to be, but I rarely measure to the 0.01 of an inch).

• The price point range for the item (based on retail price; i.e., $0-$10, $10.01-$25, etc.).

You’ll also need the following from your P&L:

• Overall marketing cost for the catalog (paper, printing, postage, name rental, creative expenses, etc.).

• Your catalog’s net contribution margin, defined as your gross margin minus net fulfillment expenses. Net fulfillment expenses are your fulfillment expenses minus shipping and handling charges collected. If your gross margin is 60 percent and your net fulfillment expenses come to 15 percent of sales, your net contribution margin is 45 percent.

Everything else you need for the analysis can be calculated from the above data.

Next month: measuring winners.

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