Few market research tools objectively measure the countless number of attributes that make up a customer experience like mystery shopping, but collecting this data is only the beginning. The value of this data lies in a company’s ability to communicate and use the data in a way that drives significant performance improvement. In 2009, that means performance dashboards and analytics.

Mystery Shopping Dashboards

Effective mystery shopping dashboards are both information-rich and visually appealing. They summarize critical, real-time performance information that allows leadership to stay on the pulse of what the customer is experiencing on the front lines and to respond to shifts as they occur within the business.

Five Characteristics of Great Mystery Shopping Dashboards

1. Customized Design: To those outside the industry, it may be surprising to learn that there are rarely two mystery shopping programs that are alike. Even two seemingly identical competitors often approach their mystery shopping programs in very different ways. As a result, business intelligence and reporting requirements also differ significantly.

This makes it critical for mystery shopping companies to possess the technical capability to rapidly customize dashboards and reporting solutions that speak to a company’s unique needs and identified priorities.

Sample Standard Dashboard Components

• Program Snapshot / Gauge (Year-to-Date, Prior Year-to-Date, Score Change)
• Category Performance Snapshot (Year-to-Date, Prior Year-to-Date, Score Change)
• Total & Category Scores by Month (typically two series; one for current year, one for prior year)
• Distribution of Scores (% of scores 100%+, 90-99.9%, 80-89.9%, etc.) compared to a prior time period
• Highest / Lowest Performing Regions, Districts, Locations
• Highest / Lowest Scoring Attributes / Questions
• High Improvement / High Decline Regions, Districts, Locations (i.e. Change vs. Last Year)
• High Improvement / High Decline Attribute / Question Scores (i.e. Change vs. Last Year)
• Spotlight Attribute / Question Performance (focuses on a specific question identified as important through prior analysis).

2. Dynamically Deployed: In leading customer-centric organizations, everyone from the CEO to the cashier takes responsibility for delivering a differentiated customer experience, but each level of the organization requires slightly different information to drive performance. Effective dashboards must be deployed dynamically, meaning that when a district manager logs in, he or she sees a different dashboard than that of a corporate leader or a location manager. Each type of user receives the specific information needed to make informed decisions and drive improvement in his or her specific role.

3. Context, Context, Context: A score is meaningless unless it can be put into context. If I tell you I’m 210 pounds and ask you if I’m healthy, you need more information. What’s my height? How often do I exercise? How much body fat do I have? The same is true with all dashboards. Numbers and scores need to be put in context using complementary metrics to tell the story.

Example 1: Is a company year-to-date loyalty score of 95% good? You need to see the number next to last year’s score, a predefined target score and/or an industry score to begin answering the question.

Example 2: Is location #1234’s year-over-year loyalty score change of -8.0% cause for a review? To answer this question, you need to know where the location ranks amongst peers or how this compares to the company’s performance. If the company required stores to cut their floor staff in half and as a result, national scores are down 12%, the location may actually be performing well given the environment.

At the company level, putting scores into context on the dashboard typically involves a comparison to scores from a prior time period, a pre-defined target score set using analytics or competitor performance data if available. In addition to these methods, other organizational level dashboards (e.g. Districts, Locations) often use ranking or comparison to top peers to achieve context.

4. Interactive / Drill-Down Capability: At a single glance, the dashboard should tell you a lot about what’s going on, but more can be understood with the ability to “drill-down” into more minute pieces of information. The overall score has dropped significantly this year compared to last, but why? Interactive-drill down functionality allows a user to quickly investigate and pinpoint the source of aggregate score changes.

Standard Dashboard Drill-Down Dimensions

• Organizational Hierarchy Drilldown (e.g. Company → Region → District → Location → Department)
• Survey Level Drilldowns (e.g. Survey → Category → Attributes / Question)
• Time Dimension Drilldowns (e.g. Year-to-Date → Quarter → Month → Week)

5. Display Sophisticated Alerts: Sophisticated alerts bring the information previously available only through time consuming analysis to the attention of those who need to know about it via the dashboard, emails or text messages. Some alerts are simply “FYIs” for users to keep an eye on, while others are used for immediate action plans or talking points. At BestMark, designing alerts begins by asking the question, “If we had all day to look through data, what things would we be looking for, and if we found it, what would we say?” For example, our system is taught to create an alert anytime an entity (i.e. company, region, district, location) has a very high or low month. This is achieved by ranking monthly scores for each entity against itself. An alert that is automatically created may look like this:

Top Score Alert: The Scottsdale, AZ location (#1234) achieved its highest score in the 34 months of the program, posting an April 2009 score of 98.6%.

The sentence above is automatically compiled by the system and displayed on the dashboard when it finds the score, and becomes an immediate positive talking point for the district manager’s next conversation with the location.

Mystery Shopping Analytics

In our next article, we’ll examine analytics in mystery shopping, including how to identify and bring focus to the experience attributes that most significantly influence customer loyalty, advocacy and profitability.