Measuring Customer Engagement in Retail Stores

Measuring customer engagement in retail stores is common practice. Many stores monitor foot traffic and use visitor counts to help determine store performance. While this information can be helpful, it doesn’t tell the whole story.

Foot Traffic Data Can be Manipulated

A recent article on RetailWire delves into the specifics of why foot traffic data isn’t enough, and helps illustrate why it is important to collect data that is qualifiable. For instance:

What’s important about traffic — especially for stores — is not the raw number, but the conversion rate, or basically dividing the number of transactions by the number of visitors. But companies face complications with the metric as store managers with bonuses on the line seek ways to make their conversion rates look better. –RetailWire

Due to varying store locales, conversion rates don’t always work as an apples-to-apples comparison between stores. Shopper styles vary, and certain areas – such as those with young shoppers or high tourism rates, might have a demographic more accustomed to browsing without an intent to buy. Further, conversion rates can be manipulated by moving sensor locations to different areas of the store.


Foot Traffic

Quality of Data Matters

With the abundance of analytics that are available to us today, not all data is valuable. You can count the number of people entering a store, but if that is the only information you have it doesn’t give you much to work with. The article goes on to state:

One thing traffic does not do, though, is measure the quality of the engagement. Did consumers stay a long time on the site or hang out at the store or did they bounce right back out? Measures of bounce rates and dwell times are sometimes needed to get to “quality of traffic.” –RetailWire

Foot traffic data alone just doesn’t offer the level of insight needed to understand in-store customer behavior and it’s effect on the purchasing decision.

Best Data Practices for Measuring Customer Engagement in Retail Stores

The best data you can collect for retail stores are the ones that tell the full story and the most valuable interaction your customers are having with your products is in the fitting room. Insight into that process is invaluable because it is the biggest sales conversion area of the store. With our fitting room solution data can be collected on:

  • Number of Fitting Room Visits
  • Number of Calls for Entry
  • Length of Occupancy
  • Calls for Service
  • Time Waiting for Associate to Answer Service Calls
  • Number of Calls Unanswered

This not only gives you valuable data for measuring store performance, but it also equips store associates and managers with the tools they need to ensure each customer is being serviced on their timing. Contact us to get started!

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“Fashion Is Your Business” Podcast Featuring Stuart Silverman, Co-Hosted by Alert Tech

Earlier this year at NRF Retail’s Big Show we co-hosted a podcast for “Fashion is Your Business”. Brian Laney (VP of Sales at Alert Tech) and Stuart Silverman (founder and CEO of RaterBee) discuss how to provide improved customer service through innovative customer feedback. They also address some of the obstacles surrounding the collection and analysis of customer feedback, and how to get store associates more motivated and involved. Click here to listen.

Why Benchmarks and Standards Are Stagnating Retail Stores

Knowing how a consumer thinks and feels about a given brand and its products is important. Understanding how loyal they feel toward the company and how likely they are to recommend it to their friends is also critical intel every business can benefit from. This is why retailers across the globe reach out for tools such as the Net Promoter Score (NPS) survey and Applied Predictive Technologies (APT). These products are designed to address any gaps that are causing customer dissatisfaction so that a brand can better understand what consumers want from them, but should these benchmarks be the “be all, end all” solution for retailers?

What NPS and APT Are Designed to Address

Both products are specifically designed to uncover what a customer is and is not satisfied with. The products use different algorithms to measure the customer experience.


NPS is designed to discover how satisfied a customer was with a given product and/or service. It also gauges whether customers like the brand and if they would recommend the company to a friend or family member by filtering survey respondents into three sections:

  • Detractors
  • Passives
  • Promoters


APT uses cross-functional Big Data-driven algorithms to help brands measure the effectiveness of their merchandising, marketing, operations, capital initiative, and ultimately, their profits. This program can take several factors into account, including the weather and local economic conditions.

NPS, APT, and other similar technologies create standards which retail executives are lead to believe are the new benchmarks in the industry. Executives feel comforted by the fact that they have “black box” metrics on hand, as they feel that this enables them to make safer business decisions.

The Benchmark Scoring Pitfall Retailers Fail to See

Analytical data is important in retail, but these systems are often not specific enough to deliver information a brand can really sink its teeth into. For example, the NPS survey does not specifically identify why a customer may be scored as a “Detractor,” or what made another customer a “Promoter.”

Another problem is that a business may not have any idea how to proceed with the results of these tests and surveys. Without having a plan in place to act on the results, this information is not going to help the business get very far.

Making a Mark with a Strong Brand Identity

Creating a strong brand identity doesn’t come from staring down pages of click-through rates and web traffic analytics; however, as the leading retailers in this industry know, technology does play a key role in standing out and rising above.

Technology gives retailers the opportunity to orchestrate the ultimate customer experience. Customers can now call a store associate for a different size, color, or style of garment with a tap of a button, and that information can be saved and stored. Associates can quickly address customer calls with a simple, easy to use iOS device and retrieve a customer’s past purchase history, allowing them to make better and more insightful purchase recommendations. Best of all, everything can connect to one central point where real-time data can be pulled upon request.

There is no question that data and analytics are critical for retailers. But brands must go beyond relying on stagnant benchmarks and questionable survey results by investing in intuitive technologies in order to excel in this competitive marketplace.

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