Pivot Tables Qualify Excel as a Serious Market Research Tool... Almost!

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1 SOFTWARE REVIEWS By Barry de Ville Pivot Tables Qualify Excel as a Serious Market Research Tool... Almost! BECAUSE OF ITS PREVALENT POSItion on many desktops, Microsoft's Excel.spreadsheet software is tasked daily with the extraction of trends, patterns, and relationships that cbaracterize tbe marketing hot spots of a wide variety of businesses. The release earlier this year of version 5, which included a new Pivot Table feature, represented a major leap forward for spreadsheet packages as generalized market research tools. Cross-tabulations are the foot soldiers of data description and data analysis in a wide variety of market research and other empirical data-analysis tasks. Tables are a simple, direct, and intuitive way to display relationships effectively. They are probably the most common form of data analysis Barrj' de Ville is a data and technology analy.st and architect with a consulting practice in Ottawa. Oniario. He can be reached un the tnternet at B ;u hookup.net. and display in use in business today and are almost universal in their application in any number of data-analysis situations. Because researchers need no special training to use and understand tables and to benefit from the results produced their continued popularity as data analysis and display tools is assured. PIVOT TABLES The combined popularity of Excel and cross-tabulations presents a strong opportunity for the introduction of new software functionality in business and market research. Pivot Tables Cro ss - tab ulations are the foot soldiers of data description and data analysis in a wide variety of market research tasks. dehver this new functionality in an extremely effective and convincing fashion because they allow researchers to assemble and reassemble the tables across various dimensions of analysis and at various aggregations of data. They are called Pivot Tables because the focus of the analysis can pivot around either row or column headings. The analogy of the pivot is both interesting and imaginative: Two-way and multi-way factors, clustered along dimensions of rows or columns, can be seen to be pivotal in describing or explaining a given relationship. A relationship might change direction, going from positive to negative, as it pivots around the values of one or more influencing factors. With Pivot Tables. Excel offers a form of direct manipulation or visual programming that comes close to offering the same ease of use in the area of tabular data analysis as spreadsheets historically have offered in the area of financial planning and analysis. Pivot Tables in Action To illustrate, let's look at the original table PRODUCTS.XES taken from the EXCEECBT computer-based training sub-directory in the workbook (see Exhibit I). Invoking the Pivot Table operation calls up the Pivot Table Wizard, which quickly guides you through the operations necessary to produce a summary table. In this case, we assembled a table that displayed sales by region for the two sales agents in the data table for each of the product cate- 5 0 Vol. 7 No. 1 MARKETING RESEARCH;

2 Exhibit 1 Exhibit 2 Original table from ExceVs computer-based training directory Year J Month Dec' SalespBrs Region 983iBuchananlSouth 3833;Bucbanan!North 3216IBuch)anan:Easl B150 bavofio TSouth 1993]Dec [ ^_2733; _ 279OiDavoiio JWest 450j ' Easf 797i uchanan]north 1933jMat; t993tmar PioducU 1773 Bu h_a_nan [West B290jOavolio Summary pivot table produced after a few Pivot Table Wizard operations? S_ J Buchanan Oavolio South I West ] 23819j ^ : ! gories (and all products rolled together). The refined table that resulted is presented in Exhibit 2. The floating Query and Pivot Tool Bar allows you to produce multiple pages for each product category, a type of drill down. Drill-down and zoom-up (or aggregation) operations are familiar and useful features of tabular data analysis that have emergedfromthe EIS (Executive Information Systems) and DSS (Decision Support Systems) applications areas of enterprise computing. Another type of drill down is offered by double clicking on a given cell to see the underlying worksheet data. Double clicking on Davolio's South sales, for example, displays the underlying data shown in Exhibit 3 on page 52. Summaries and groupings also are possible. For example, Buchanan's sales can be singled out rapidly for special treatment, sorted by amounts, and grouped by quarters (see Exhibit 4 on page 52). The floating Query and Pivot tool bar provides a number of "instant access'" tabular operations, including the grouping and ungrouping operations that are displayed in the screen shot. The software also supports multiplepage displays to show higher dimensional tabular relationships, re-calculations, and row-column control field swap operations. The Function Wizards and floating Tool Bars provide a wealth of direct manipulation and visual programming functionality that makes the Pivot Table capability within Excel both powerful and easy to use. So far the results have been somewhat cryptie only numerical results are shown. Modern analysis tools should present a graphic face both to facilitate understanding and. later, to assist in communicating the results. Excel 5's Graphics Wizards change numeric data into a graphic display so managers can quickly summon up a chart in Excel (see Exhibit 5 on page 53). Pivot Table Weaknesses The kinds of tables we've been looking at are useful for standard business analysis MARKETING RESEARCH: Vol. 7 No. 1 51

3 Exhibit 3 Detailed data underneath Davolio's southern region sales but normally would not be acceptable for tnore academic researeh tasks. For example, because the cell entries are presented in raw form, the interpretation of tbe table is subject to distortions caused by the preponderance of high-valued raw data entries in a particular cell or row. To address this "base of comparison" problem, it is necessary to express all exhibits in a cotnmon or norrnalized form. Tbe favored method of presenting normalized results in tabular analysis is by expressing cell entries as percentages. Although percentages are not provided by default, they ean be easily computed and displayed in Pivot Tables, as can a wide range of other cell entries such as average, minimum, maximum, cell entry variance, standard deviation, and so on. Moreover, percentages can be computed for rows, columns, or totals. A row-wise percentage calculation is presented in Exhibit 6. This is one area where the Function Wizard assistance breaks down; no matter Exhibit 4 Example summary results produced for Buchanan's sales figures MARKETING RESEARCH:

4 Exhibit 5 Graphic display of sales results produced hy the Graphics Wizard in Excel 35.00% 30.00% 25.00% 20.00% 15.00% 10.00% 5.00% 0.00% Sales performance by region East North South Region Buchanan Davolio West how intuitive tabular displays and analyses are. virtually all novice analysts encounter difficulties in deciding whether to express percentages as a function of row summaries or column summaries. The triedand-true solution is to run the percentages according to the "cause and effect rule"- i.e.. compute the percentages in the direction of the causal factor. This rule states tbat one of the two factors being tabulated is considered as the cause of the marginal distribution of the other factor. (Strictly-speaking, it is not a question of which factor is the "cause" of the other one, but which factor we wish to consider as affecting the percentage distribution of the "dependent" factor.) In this case, we consider that differences in sales agent practices with respect to customers in different regions ean be assumed to influence the percentage outcome of sales in the various regions. The other thing missing in Pivot Tables is some routine indication of the statistical Exhibit 6 Cell entries expressed as percentages of row totals 25.48% 27.91% 16.78% 20.27% 21.34% 32. 3% 26.25% Grand Total 22.58%: 24.25%! 26.22% 26.95% % significance of the resulting table. The utility of significance tests has been hotly debated in academic circles, but this is no reason to leave them out of a tabular display. Like the sight on a rifle, a slgnifi- cance test is no guarantee that you will hit your mark, but it certainly gets you into the target zone faster. These drawbacks are unfortunate because they divorce this "street smart," MARKETING RESEARCH: Vol. 7 No

5 Exhibit 7 Relationships change with the introduction of new tabulation fields The strengths of Pivot Tables offset their deficiencies in the area of scientific rigor. -il-avoiio rand Total powerful, and effective business analysis tool from advances in statistical theory and philosophy of science that have occurred over the last few (jecades of empirical social research. (Notice, however, that once the entries in the cells are expresse(i as percentages, the exceptional performance of Davolio in the South region becomes obvious, with sales almost double those of Buchanan in this area.) Like the sight on a rifle, a significance test is no guarantee that you will hit your mark, but it certainly gets you into the target zone faster %! % 23.27%i 21,18% 14,35% 1 24,39% I 32.29% i 28,96% 19.63%! 26.71%i 23.21%! 25.44% 100,00% Yod.ob% % Another deficiency of the Pivot Table feature lies in its limited support for the construction of well-specified higher dimensional tables. Accurate research requires tables that can display controlling and specifying factors that fundamentally affect the relationships characterized in the table. Multidimensional tabular analysis theory and practice teaches us that an accurate description of the form of a given relationship can only be obtained by including all the relevant factors that influence the relationship. This is common knowledge among recent graduates of even elementary university-level research methods courses but it's quickly forgotten in the rough-and-ready world of bottom-line business results. For example. Exhibit 7 shows that the relative performance of Buchanan and Davolio is influenced, or specified, by the type of product being sold. When all products are considered, Buchanan out-performs Davolio in all regions, except the South. However, in the '"Produce" product category the results are more balanced, with Davolio outperforming Buchanan in two regions. A powerful facility like the Pivot Table tool should provide advice in isolating these kinds of well-specified, high-dimensional relationships (possible through Wizards) and should provide automatic search engines to assist in identifying them. A number of products all belonging to the CHAID/AID/CART family are available to earry out automatic higher-level dimensional factor searches for controlling and specifying relationships. Two product category leaders are SPSS's CHAID and ANGOSS" s KnowledgeSEEKER (see the Summer 1994 issue for reviews). THE BOTTOM LINE The strengths of Pivot Tables offset their deficiencies in the area of scientific rigor. Because Pivot tables are so easy to set up and use, the analyst can quickly explore many, many business and market scenarios in a given session. The access to data and the insight this offers contribute major value in an area where decisions often are made without the benefit of empirical data analysis. This is an exceptionally positive development because it promises to produce more marketing decisions based on a balanced approach that includes both empirical data analysis and experienee-based intuition. IM3 54 Vol, 7 No, 1 MARKETING RESEARCH:

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