It Takes Two; a Customer Experience Measurement Strategy

World class multi-location brands leverage several measures to understand individual store performance. This is true across numerous industries, from restaurants to supermarkets to petro and convenience retailers to drug stores to department stores to hotels to banking and financial services organizations. However, not all stores are created equally. There are many factors that go into measuring how an individual location delivers on the brand promise. Financial metrics are an obvious metric—but tend to be in the rear view mirror. In Market Force’s modeling work, we have found that both delivery to brand standards (assessed through mystery shopping and audits) and customer experience metrics (surveys and call center data) can be lead metrics of financial performance. So how?

Location-level customer experience derives from two components:

  1. Operational execution—how well did the location deliver on the brand standard?
  2. The experiential factor—how did a customer feel about his or her experience?

Both operational and experiential measures tell a brand how its locations are delivering on the brand promise.

Operational Measures: Most brands leverage mystery shopping to understand their operational execution. This measure is a black and white, objective evaluation of exactly what happens at the store when a customer comes in. Were they acknowledged and greeted? Were they served properly? How quickly did they receive service? How long did it take them to check out? Were they thanked for their business? These are simple questions, answered with ‘yes’ or ‘no’ responses. In addition, shoppers can assess the sales process—did associates ask needs based questions, provide recommendations, and interact in a way that positively represents the brand. Mystery shopping enables a business to ‘inspect what they expect’. This feedback helps brands know where they are executing and where there are performance gaps.

Experiential Measures: Just as many businesses deploy customer experience surveys. This measure is more of a ‘shades of gray’ perspective; a subjective read on how a customer felt about their visit. Overall, how satisfied were they with their experience? How likely are they to return? How likely are they to recommend the store to a friend, family member or colleague? How do they feel about the value for the price paid? These questions are answered using both quantitative scales and open-ended text data. Leveraging both numeric and open-ended data will provide operators with the information they need to coach their teams to delight each and every customer.

With both measures in place, an organization has a truly holistic view of their location level CX, and change becomes a matter of acting on very specific behaviors. In our research across hundreds of multi-location businesses, we find that better performance on brand standards (as assessed by mystery shopping) has a high impact on the actual customer experience—customer satisfaction increases as locations deliver better on standards. In addition, our sophisticated financial models show that the actual behaviors of store staff and operational attributes of a store can predict financial metrics like same store sales, transaction counts and average transaction value. And these are the metrics that really matter.

For additional insight into this integrated approach, please see our “Better Together: Integrating Direct Customer Feedback and Mystery Shopping Data” white paper.

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Brad Christian is a Managing Director at Market Force and consults with retail and restaurant executives to design cost-effective customer experience measurement programs that help them protect their brand's reputation, delight guests and drive greater unit economics.

Making Sense of Sensors and Beacons

Many companies have invested in camera and beacon technology to track customers within brand locations. That data is very rich. How can you make sense of the plethora of information? We recommend tying behavioral data from these sensors to the subjective data supplied by customers.

For example, a Market Force partner uses sensor data to track cars and people at a gas station and convenience store. Data includes unique visitors, first time visitors, dwell time at certain stations (like the pump) and number of visitors entering the convenience store. This rich behavioral data can be combined with subjective survey data, contact center data, or mystery shopping data. Brands can examine:

  1. Relationship between dwell time and cashier service in the convenience store, and sales. Modeling can relate actual physical time spent in the convenience store to basket size and sales. It can extend to test hypotheses—like whether dwell time is related to cashier friendliness collected on your customer survey. And if that relationship exists, analytics can help determine what a cashier could do to ensure that a longer time spent in the store or at the register, ensures a higher number of items purchased.
  2. Bounced visitors. Real estate is an expensive investment. The number of bounced visitors who spend very little time at your location is a great indicator of abandonment. This information can be related to your mystery shop data to indicate whether the attractiveness, security, and cleanliness of your site discourages or draws in traffic.
  3. Average days between visits. This frequency metric will help you determine whether you have a steady clientele or new customers entering every day. That’s an implicit measure of loyalty and can be related to both customer satisfaction and loyalty card data.
  4. As a last example the number of people in a particular zone can be related to conversion rate. For example, three people might visit a zone that has a live sales person and only one purchases. Conversion rate could be related to the time spent with the sales person or the effectiveness of the sales person in positioning products. The latter would be measured through customer satisfaction surveys

With the use of GPS tracking in smart phones and the nearly ubiquitous implementation of cameras and sensors, your brand has the opportunity to link highly complex behavioral data with subjective perceptions and operational metrics like mystery shopping. A wealth of insights that your analytics team can mine to manage your business more effectively. To learn more about our location based services offering and/or analytics, schedule a briefing with us and we’ll be glad to have a conversation. 

 

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As Chief Strategy Officer, Cheryl aligns Market Force's strategic direction with our clients' strategic objectives. She oversees the North American client base, Analytics and Insights, Winnipeg Operations and Marketing. She has a Ph.D. in social psychology and broad business experience in both private and public companies.​

 

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To discuss your needs for improving performance for your multi-location brand, give us a call. We’d be happy to discuss best practices for measuring the customer experience and compliance to brand standards, using analytics to understand what matters most and the ROI for change, and technology solutions that integrate large quantities of data on one single platform. We look forward to a great discussion!

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