Tracking shoppers in-store

Tracking shoppers in-store

A growing band of bricks-and-mortar retailers are using technology to track their customers in-store and generate more revenue.

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Women shopping in shop

When a customer walks into a store and thinks one of the mannequins is watching their every movement, they might well be right. Armed with technology that tracks customers’ movements, and recognizes their gender and race, mannequins are being used to produce data that helps retailers better understand customers. With footfall under pressure – affected by an array of factors, including weather, location and consumer choice – retailers believe this knowledge can be used to increase conversion rates, the average value of transactions and the profitability of stores.

Analyzing shopper behavior can yield instant dividends. For example, one major department store studied traffic flow and found that less than 10 percent of customers visiting its shoe department engaged with the self-service wall display where merchandise was stacked. Some benches were found to be limiting access. Sounds obvious, but it might not have been spotted without the traffic-flow analysis. Relocating the benches prompted a double-digit boost in the department’s sales.

Mining the data with mannequins

using real time heat maps to increase sales

Retailers are using a host of technologies to follow where customers go inside their stores and how they behave. Information can be generated from any or all of the following: aisles and door sensors, beacons (which may require users to install compatible apps), mannequins, video cameras, Wi-Fi- and Bluetooth-based location triangulation.

Data can be presented in easy-to-read formats, such as heat maps, in real time and has helped retailers reposition sales staff, identify the real prime locations in-store and track whether local promotions attract new shoppers.

Even if the customer has switched off their smartphone and walked past a store, their movements can still be tracked. Using cameras and sensors, it’s possible to analyze how many shoppers walk by (and how this varies across any particular period), how many enter, how long they stay and how many buy products. Such data can be used to adjust opening times, staffing levels, sales techniques and store layout to boost revenues.

Italian mannequin maker Almax caused a stir two years ago with its Eye See mannequins, which use facial recognition technology. In one store, Almax’s mannequins alerted managers to a regular spike in Asian customers coming through a particular entrance after 5pm. When management moved two Asian shop assistants to that location at that time, sales rose 12 percent. Elsewhere, Almax data noted unusual numbers of youngsters using the store in the afternoons – unusual because the shop didn’t sell any products to children. The store changed that and kids’ products now account for 11 percent of turnover.

If customers have Bluetooth or Wi-Fi activated on their smartphones, retailers can tap into a much richer stream of behavioral data generated by customers travelling through stores. If shoppers have downloaded an in-store app, they have usually shared their personal details with the retailer. Even if they haven’t, their behavior can still generate valuable insights. By aggregating data from other shoppers with smartphones, companies can learn what percentages make repeat visits or go to other branches even when they didn’t buy anything.

The allure of apps

creating customized experiences

Using in-store data to maximize the sales potential of store layouts and service levels is valuable but some bricks-and-mortar retailers are more ambitious, believing they need to transform the shopping environment so dramatically that people visit because they enjoy the experience. Technology can play a part here too: apps can be immensely useful in attracting shoppers. According to the US Mobile App Report 2014, the use of apps occupies seven out of every eight minutes spent on mobile devices.

“Consumer expectations will be that products, services and experiences should be shaped passively by their data in real time and personalized to them. If you’re not doing it, you’ll be seen as less relevant and exciting than those who are,” says David Mattin of trendwatching.com, who cites the Chune app as an example. Through Near Field Communication, Chune takes music playlists from cell phones over a small area, so customers’ favorites can be broadcast in store. Mattin calls it “crowd shaping through aggregating consumer data”. To others, it just sounds like something that makes shoppers feel good.

Shop apps can sort through product wish lists, personalize special offers, minimize waiting times at checkouts and construct the quickest, most productive route round a store. As customers approach products, they can provide key information. Timberland found discounts offered via in-store apps were twice as effective in generating sales as emailed discounts. Giving deeper discounts to customers loyal enough to download a store app – allowing retailers to capture their data – can make these apps even more attractive.

At supermarkets, the check-out experience is crucial. Russian startup Synqera’s Simplate platform scans and reads customers’ facial expressions at the checkout, combines the data with shoppers’ purchase histories (obtained via a loyalty card), and creates custom promotions that can be offered to consumers at the counter, or through SMS, email or mobile apps. If the software suggests customers are in a good mood, it could invite them to complete a survey. Ulybka Radugi, one of Russia’s largest cosmetics chains – with 2.5 million customers and 280 locations – began piloting the platform in July 2013.

Motions and emotions

Tracking data beyond demographics

Snack food giant Mondelēz plans to roll out facial type recognition technology in ‘smart shelves’ where its products are stacked during 2015. The shelves could use weight sensors and motion tracking to calculate what kind of person is buying which product and in what size.

Proctor and Gamble (P&G) is focusing on emotions, not motions. Using software developed by Californian firm Emotient, the FMCG giant can detect seven main emotions – sadness, anger, fear, disgust, contempt, surprise and joy – generating data for its product focus groups. By measuring the level of emotion across a store, the software could help retailers identify and placate irate customers by putting more employees on the floor or giving out samples.

When P&G tested three fragrances for its Tide detergent, there was a correlation between the product participants chose in an at-home survey, and the one that provoked the least negative reaction in shops.

When collecting personal data, retailers and brands using in-store customer tracking technology need to carefully consider privacy. This is particularly relevant to apps, which can be vulnerable to hacking. For instance, the app for a recent live event organized by one IT security firm leaked the details for thousands of attendees. And some customers may just not like the idea of stores using their personal details or tracking their movements. “Retailers should communicate openly with customers about tracking, and always offer a way to opt out,” says Mark Larson, KPMG’s Global Head of Retail. “This is particularly important in the EU, where new privacy regulations have been recently introduced.”

Brad Lawless, vice-president for Collective Bias, a social start-up linking customers and retailers, says: “Some people balk at retailers knowing too much about them, but we've seen shoppers parting with personal information when signing up for store loyalty programs if they receive additional convenience or savings in trade," says Lawless. "Imagine walking into a store with a shopping list stored on your device. You get in and out more efficiently with less frustration and possibly experience a moment of delight as well."

“The key to getting shoppers in-store – and converting more of those into customers – is to deliver an experience people can’t get online,” adds Larson. “Delving into their movements, emotions and thoughts is coming up with some answers, and could boost revenues. There will be winners and losers among the competing technologies, but that needn’t stop retailers experimenting. One US retailer tracked 29,000 shoppers over three weeks and using the findings to tweak layouts at 90 stores increased conversion rates by 3 percent.”

Tracking the benefits

How sensors, beacons and Wi-Fi can help retailers

  1. Discover which stores are most popular with customers.
  2. Identify which products attract the most attention.
  3. Evaluate conversion rates of shoppers passing, entering or buying.
  4. Highlight necessary changes to store layout.
  5. Influence where products are best sited.
  6. Determine where staff need to be positioned, especially to tackle customer-service issues such as long queue times.
  7. Measure whether various factors affect the likelihood of purchase (such as music or in-store temperature).
  8. Enhance the shopping experience by offering personalized discounts, location-based loyalty programs and suggesting new products customers might like.
  9. Help shoppers find their most useful path through stores.
  10. Increase overall sales and revenue.

Tracking the benefits



Using technologies such as sensors, beacons, and Wi-Fi networks can help retailers:



  1. Discover which stores are most popular with customers.
  2. Identify which products attract the most attention.
  3. Evaluate conversion rates of shoppers passing, entering or buying.
  4. Highlight necessary changes to store layout.
  5. Influence where products are best sited.
  6. Determine where staff need to be positioned, especially to tackle customer-service issues such as long queue times.
  7. Measure whether various factors affect the likelihood of purchase (such as music or in-store temperature).
  8. Enhance the shopping experience by offering personalized discounts, location-based loyalty programs and suggesting new products customers might like.
  9. Help shoppers find their most useful path through stores.
  10. Increase overall sales and revenue.

Tracking the benefits



Using technologies such as sensors, beacons, and Wi-Fi networks can help retailers:



  1. Discover which stores are most popular with customers.
  2. Identify which products attract the most attention.
  3. Evaluate conversion rates of shoppers passing, entering or buying.
  4. Highlight necessary changes to store layout.
  5. Influence where products are best sited.
  6. Determine where staff need to be positioned, especially to tackle customer-service issues such as long queue times.
  7. Measure whether various factors affect the likelihood of purchase (such as music or in-store temperature).
  8. Enhance the shopping experience by offering personalized discounts, location-based loyalty programs and suggesting new products customers might like.
  9. Help shoppers find their most useful path through stores.
  10. Increase overall sales and revenue.

© 2016 KPMG International Cooperative (“KPMG International”), a Swiss entity. Member firms of the KPMG network of independent firms are affiliated with KPMG International. KPMG International provides no client services. No member firm has any authority to obligate or bind KPMG International or any other member firm vis-à-vis third parties, nor does KPMG International have any such authority to obligate or bind any member firm. All rights reserved.

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