When Less is More: Fewer Reports, More Business Intelligence

A business-focused report will tell you at least the following:

• What drives your customers', employees', or members' overall satisfaction and intention to continue the relationship
• How participant segments differ
• What actions will have the greatest impact on your business objectives

Don't shortchange your analysis.

Without appropriate levels of analysis, the true value of your survey may remain undiscovered. To help you determine the level that is most appropriate for your needs, we provide a quick overview of the most common types of survey analysis and reporting.

Three levels of insight into your survey results

Level 1 - Basic tables, charts and cross-tabulations

Basic tables, charts and cross-tabulations describe your data, using means and percentages. Basic tables and charts are the most common formats for reporting survey results. Basic charts summarize your data in an accessible, visual format. Charts can be used effectively to compare results for two or more groups, or to rank order responses from most to least positive. are adequate for many purposes, such as a quick survey of satisfaction for a one-time event.

Tables and charts are adequate for many purposes, such as a quick survey of satisfaction for a one-time event. These tools alone, however, do not tell the whole story, and they can be misleading.

A frequent misconception about survey results is that the lowest-scoring items merit the most immediate attention. Reports based on this typically report "strengths" and "areas for improvement." Reports of this type usually include charts or tables that rank items based on averages or top-box percentages.

Frequently, this inference is incomplete or even misleading. A fundamental problem is that some low-scoring items may not be particularly important to respondents. Also problematic: differences that appear large on a chart may not be statistically significant - that is, they may represent random fluctuations in your data, not real differences between groups.

Level 2 - Statistical Analysis

Statistical analysis enables you to distinguish the random "noise" in your data from meaningful changes over time or differences between groups. Correlations, comparison of means, and statistical testing of cross-tabulations fall into this category of analysis. These methods, often referred to as "descriptive statistics," give you a more exact understanding of your survey results. Descriptive statistics are powerful because they allow you to confirm or disregard differences that show up in charts, tables and graphs. Knowing whether apparent differences are truly meaningful or chance occurrences can save you large sums of money when it comes time to allocate resources to one plan of action or another.

Level 3 - Mapping Key Drivers

Interpretive Analysis and Mapping Key Drivers of business outcomes addresses this limitations of more basic descriptive methods. At this level, the analyst looks at responses to individual items or clusters of items to understand how they work in relationship to each other.

Interpretative statistics reveals the elements of your products, services, or culture that most influence overall satisfaction, renewal intentions, and willingness to recommend your products or services to others. These elements are often called "key drivers." The chart below illustrates results of a key drivers analysis.

A glance at this chart immediately communicates customer priorities. Actions the company might consider based on this analysis might be to:

• Service: Improve service by increasing customer focus and responsiveness (upper left quadrant - high importance, low satisfaction).
• Marketing: In marketing, build brand by capitalizing on important strengths such as expertise, innovation, trustworthiness and partnership (upper right quadrant - high importance, high satisfaction).
• Customer Communication: Continue communication practices and policies to maintain strengths evident in the lower right quadrant - not necessary to invest more resources here at this time.
• Efficiencies: Monitor customer concerns and competitor offerings with respect to efficiency, cost, and ease of making changes (lower left). These are weak areas of moderate importance to customers; they could quickly become a source of vulnerability.

Mapping key drivers enables you to determine priorities for improving the customer experience or increasing employee retention. Analysis of key drivers also reveals strengths most likely to foster satisfaction or loyalty so that these strengths can be continued and highlighted in recruiting or marketing.

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