for. With the emergence of software-assisted page planning, graphic design and page layout techniques, obtaining square-inch measurements has become at least partially automated. Software systems which store dimensional data related to sales offers as shown on page layouts should be capable of delivering the necessary area measurements for each item offered on each page in tabular form. Obtaining Sales Data The minimum data required for square-inch analysis consists of page number, unit sales volume, gross revenue, and gross profit for each item offered. Additional insights can be obtained from including unit return volume, unit of sale, merchandise category, style information or other descriptors in the sales data inputs to square-inch analysis. One common challenge for the business systems which record item sales data is relating it to the exact catalog page on which an item appeared. Another common challenge for business systems is identifying which sales were motivated specifically by a catalog offer. Reporting The fundamental quotient of square-inch analysis is item profit per square inch according to the formula item gross profit (dollars) / offer area (square inches) = item profit per square inch. Secondary calculations include unit volume per square inch, item revenue per square inch, gross profit and revenue per offer and per page. The elementary mathematical formulas involved in deriving the results of square-inch analysis can be easy modeled by formulas in a software spreadsheet. Support for page planning decisions requires that these results be numerically sortable. Businesses who utilize direct marketing can take this reporting a step further by applying design of experiments methodology. The direct marketer can create "look alike" control groups (selected from the qualified mail population using random sampling techniques) to calculate the incremental revenue per square inch. This is important because the marketer can understand the influence the direct marketing had on the customer's purchase decision. The challenge is the business must allocate a significant quantity of customers to the holdout control group to ensure results are statistically significant and the insights can be expected in future direct mail campaigns. Automation With the emergence of sophisticated software-assisted catalog publishing systems, square-inch analysis has become at least partially automated. As of 2012, at least six publishing systems claim to provide some form of square-inch analysis capability, and at least two are known to have been created primarily for this purpose. References Marketing analytics