Catalog Analysis: Taking Squinch a Step Further

Last month we began our discussion of the merchandising functions of “squinch,” or square-inch analysis, which helps the merchants and the creative team determine what is selling based on how much catalog space you have allocated to the products. We looked at squinch both by page and by profitability — two essential components of this type of analysis.

This month’s column takes square-inch analysis a step further. The square-inch analysis spreadsheet is a great format because you can use it to re-sort the same information again and again, by a variety of criteria, to learn more and make better merchandising decisions. We will first sort the square-inch data by product category, and then by price point, gleaning information from each analysis.

By product category

The chart below shows the same type of square-inch analysis that we performed in last month’s column (“Determining Your Product Winners — and Losers”). But this time instead of sorting the data by page, we have sorted the data by product category.

Analyzing performance by product category enables you to compare the relative strength of each category, whereas page analysis of merchandise or a ranking of all products by contribution shows only how well the creative is working and identifies the winners and losers. Good merchants must constantly test new categories and try to expand those categories that show strength, and drop those that don’t sell.

Since product categories vary in terms of the merchandise assortment and number of items, categories are never equal in their responsiveness and contribution. But you can begin to gauge whether to expand, contract, maintain, or discontinue categories by looking at the overall profitability of each: In other words, did a category make money, or didn’t it?

To figure out a category’s profitability, you want to compare its percentage of sales and percentage of profit contribution to the percentage of space it took up in the catalog. If the percentage of sales and profit it generates is greater than the percentage of space, it’s a winner. Conversely, if the percentage of sales and profit it generates is less than the percentage of space, it’s a loser.

In the spreadsheet below, we see that category A (books) generates 43.6% of the catalog’s total sales and 56.8% of its profits while taking up just 30.7% of the space. The conclusion: We’ve got a winner.

Category B (outdoor accessories), however, generates only 22.8% of the sales and 2.9% of the profits while using 34.3% of the space. Conclusion: This category needs help — and fast.

As for category C (garden items), it is relatively balanced, generating 33.7% of sales and 40.3% of the profit, while taking up 35% of the space.

Delving deeper within each category, in the strongest categories of a successful catalog, typically at least 70% of its products are winners (again, generating a higher percentage of sales and profit than the the percentage of space it takes up in the catalog). This is often referred to as a 70% or more success rate.

You should evaluate product categories in which only 50%-70% of the items are winners. By analyzing the product subcategories you may notice some consistent winners or losers. The relative performance of various price points may also give you a clue as to what is working.

Product categories with a success rate of 30%-50% need to be studied even more closely. Since the losers are outperforming the winners, you need to decide whether you should be carrying different products within the category, or whether the category should be cut back dramatically.

Categories in which fewer than 30% of the products are winners should be dropped, unless there is an overriding reason to retain them. For example, if you sell licensed products, the manufacturer may require you to carry the entire line. In this case, you could reduce the space allocated to the loser items, move the products to the back of the order form, or resort to a line listing of the products without the benefit of photography.

Looking again at the spread sheet on page 163, we can draw some conclusions about which categories to maintain, contract, or expand. For instance, within product category A, three of the seven items were strong winners, showing a positive profit contribution. In other words, 43% of the products in this category were winners.

The cataloger would likely want to modestly expand this category by seeking more products similar to the three winners. One product, the stamp book, was particularly strong — in fact, it was the only item among all three product categories that contributed more than \$1,000 to profits. The cataloger would do well to add more products like this one.

By the way, if you are prospecting heavily, here’s a word of advice: Conduct separate product category analyses for prospects and for customers. Typically first-time buyers select different products than do multibuyers. Also, prospects normally have a lower average order value than do customers.

By price point

A second, closely related way to sort squinch is by price point. This type of analysis helps you determine whether various price points offered in the catalog are paying for themselves and which price points are the most popular. This analysis is also used to find new items similar to the winners, rather than to establish or change prices of existing items. As with product category analysis, you may want to look at a price-point squinch for first-time buyers vs. repeat customers.

In the spreadsheet below, we have three categories of merchandise: those selling for \$9.99 or less; those selling for \$10-\$19.99; and those selling for \$20-\$29.99. Looking at the percentage of sales and percentage of contribution vs. the percentage of space, we find a much better balance than we did in the product category analysis.

The \$0-\$9.99 category has a positive overall contribution. Of the 11 items offered in this price range, six are winners, for a 55% success rate. But this price range uses 34.2% of the catalog’s space while generating only 26.7% of the sales and even less (18.3%) of the profit. This price range is underperforming. Clearly, the cataloger should find more winners or reduce the space allotted to this price range.

One item, T-shirt A, dominates the \$10-\$19.99 price range. That shirt contributes an impressive \$1,848.86 to profit. Aside from that product, though, the price group basically breaks even. The category has only a 43% success ratio (three of the seven items are winners), but it has a good balance of sales and profits to space (36.1% sales; 36.5% profit contribution; 33.3% space.)

The \$20-\$29.99 price point category has the greatest net contribution of the three ranges, with five out of eight winners, or a 63% success rate. Two strong items, the planter A and the stamp book, produce most of the profit contribution. For the category overall, sales percentage and profit contribution percentage are greater than the percentage of space used (37.2% sales; 45.2% profits; 32.5% space). This category is performing well, especially with contribution to profit.

Price-point analysis gives you an added dimension in looking at the overall product contribution of a catalog. When combined with product category analysis, a catalog’s overall merchandise strategy should become abundantly clear.

Next month, this column will look at premailing merchandise analysis — the product category and price-point grid, a planning tool designed to ascertain whether there is adequate balance in a proposed catalog merchandise offering.

Jack Schmid is president of J. Schmid & Associates, a Shawnee Mission, KS-based catalog consulting firm.