May 01, 2011 9:30 PM  By

While some of us love diving into the minutia of square-inch analysis, others may find this an unenviable yet necessary task of mathematical gymnastics. Once completed, however, the analysis provides insights for marketers and merchants — from reallocating page space allotted to products to identifying which colors or price points are most appealing. The findings help shape the next catalog.

The square-inch analysis template always requires modification. For instance, a greeting card company needs to have visibility to price point, format of card, and sentiment, whereas an industrial supply company tallies space allocated to instructional information, in-use product photography and bundled/kit pricing.

Sometimes there isn’t time to do a square-inch analysis, however, and reviewing performance by merchandise category is better than doing nothing.

### No time like the present

To understand merchandise category performance, run the data for the products in the catalog for a specific time period. Divide total sales by page count to yield average sales per page. Then parse the data by merchandise category, and count how many pages (rounding is acceptable) each category is occupying.

Now you can see the performance compared to the average of the catalog.

The next step is to look a little closer at underperforming categories. Review the items within each category to find the lowest performers.

What is causing the less than stellar performance? It is due to space allocation, creative treatment, price point, or other variables? The simplest way to answer the question is to compare the worst performers to the best performers.

You’ll want to look at placement on the page, space devoted to selling the product, copy block, price point and visual treatment of the item. It’s not unusual to find that the item isn’t given enough space to tell the whole story — from the lack of product insets to communicate benefits to the spatial relationship of the item to the copy block.

Once you have identified the potential reasons for lower than average performance, decide which changes are best to implement. Whether mimicking the best creative treatment or deciding to increase the photograph by 15%, you now have a course of action because of simple category analysis.

### Directional data

Since you have already run the report for the catalog during a specific timeframe, and you know the average revenue per page, you can now figure out revenue per product. Quickly count how many products are shown on a page — shown (what customers see) and not line listed.

Divide the number of products shown into the average revenue per page. If the average revenue per page is \$5,000 and there are five items shown on a page, then each item generates \$1,000 on average (\$5,000/5).

The \$1,000 is the threshold: If you want to add a product, it needs to generate \$1,000.

If you need to omit products, start by finding items that fall short of \$1,000 in sales. Determine the relevance of omitting those, because some might be part of a bundled product offering, or perhaps a low-dollar add-on item. And remember, just because the product is omitted from the catalog or a particular effort doesn’t mean you remove it from the website.

### Determining merchandise attributes

Your specific merchandise attributes will directly influence which data elements you will include with square-inch analysis. While most companies will use customary column headings, such as new item vs. repeat item or type of image shown (silhouette vs. environment), you may want to isolate other influential characteristics.

Some ideas include products shown in-use, on-figure vs. off-figure, inset of product shown in the packaging, featuring the company’s brand/logo, product theme, import vs. domestic merchandise showing the “Made in the USA” symbol, and items that have a ratings and review treatment.

One of the more recent considerations has to do with the space for ratings and reviews. If the rating/review is specific to a product, the space should be attributed to the product. But if the rating/review is more general, you should divide the space equally among the benefiting products (usually on the page or page spread).

A similar issue pertains to recipes, testimonials, ring sizers or shoe sizers, embroidery or personalization options, and how-to instructions. No matter the space allocation methodology you choose, the most important advice is to be consistent.

### More than a number

A square-inch analysis will reveal the popular price points. One advantage of price-point analysis is that you can sort the spreadsheet by category and then price point. You’ll see very quickly if particular price points are under-represented in the catalog.

The chart “Holiday 2010: Retail Under \$100” to the right isolates products shown in the catalog whose retail price is under \$100. The red bar indicates the percent of products offered below \$100 (e.g., 20.3% of products are \$9 and under), and the green line indicates the percent of products sold for less than \$100 (e.g., 30.7% of products sell for \$9 and under).

The under \$9 price point is clearly appealing to customers. The chart also reveals that 14.4% of the products are offered in the \$29 price point (\$20 to \$29 range), but only 11.2% of items are sold at that price point. This means that too many products are potentially offered at this price point.

You’ll want to look at the individual products as well as the product categories to determine why this is happening. Sometimes the answer is over-assortment (too many choices at this price point), and sometimes it’s because customers are choosing a product at a lower price point.

If the latter occurs, revisit the creative to ensure that there is proper upselling on the page, and that the creative treatment is guiding customers appropriately.