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Shopper Tracking: You Can't Improve What You Can't Measure


Stores used to be a black hole of accurate and meaningful shopper metrics, but thanks to major advancements in in-store tracking technology, stores are now a treasure trove of shopper data and insight.

In fact, tracking shoppers in stores has emerged as one of the top investment strategies in retail, according to RIS’ “29th Annual Retail Technology Study.” But what features and capabilities should tech-savvy retailers considers when looking to deploy next-gen, in-store tracking?

To uncover how retailers can best leverage in-store tracking to gain actionable insight on ever-changing demand, Sensormatic Solutions’ senior director of its ShopperTrak retail consulting practice, Brian Field, sat down with RIS for an exclusive Q&A on the topic.

RIS: Why is it important for retailers to collect data about the in-store movement of shoppers and merchandise?

Field: The short answer is to ensure that their customers have an optimal shopping experience. Tracking shoppers helps retailers understand which pathways are working and which are not engaging shoppers. It also helps determine the effectiveness of staffing and scheduling practices. And tracking merchandise helps improve inventory accuracy and turn.

RIS: Where are retailers seeing the biggest return on investment from collecting and using this data?

Field: From an inventory perspective, the easiest and most significant ROI is in improved inventory accuracy, so that stores are more properly replenished and false out-of-stocks do not result in lost sales opportunities.

For traffic, the easiest and most significant ROI is in labor optimization – ensuring that the right people are scheduled at the right times to engage with shoppers and to ensure that restocking and cashiering take place at the right times.

RIS: Why is it important to anonymize shopper data?

Field: Individuals, organizations and governments have made it clear that some areas of personal data collection should be off limits to businesses. There are laws like GDPR in the European Union and similar legislation in California that address the specifics of what is permissible and what is not. For example, the in-store traffic data that we collect via WiFi tags does not include shopper identification information ― just a unique, anonymized, indexed number.

RIS: How can retailers leverage in-store data to make better use of their workforce?

Field: Using in-store data does an even better job of identifying labor coverage opportunities than perimeter traffic. For example, let’s say that the perimeter traffic counts indicate that a shift is needed between 3 pm and 7 pm on a Friday. This would represent a need for the overall store. But there may be zones or departments inside the store that experience a very different shopping behavior pattern. In-store traffic provides further insight into that, and allows for even better coverage where it is most needed at the appropriate day and time.

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