Tracking Mood: Are Your Customers’ Emotions the Key?
Online stores have a huge advantage with targeted marketing. From the moment you land on ASOS’ website, your path is monitored and analyzed. Click on a skirt or jumper, and you’re invited to “shop the look” or told “you might also like.” Leave the website to check the news on The Wall Street Journal or New York Times websites, and you might find a photo of that cable-knit jumper sandwiched in the middle of an article.
The Fifth Avenue Prada store doesn’t have this power. The subway may be lined with advertisements showing collection highlights, but these can’t be individually tailored. Brick-and-mortar retailers must explore other options.
Using Facial Recognition
One such option is to use facial recognition software to extract mood data from shoppers. This is already common in Russia, where if you’re an angry-looking man of 30, you’ve probably been offered whiskey on a Friday night.
Increasing numbers of British shops are following suit, with 59 percent of fashion retailers utilizing facial recognition software. Some use specialist cameras to monitor numbers passing through the door; others use CCTV.
It is, however, difficult to process large crowds, and there are obvious privacy concerns for the public. Nordstrom experimented with this approach, placing signs around its stores to warn shoppers of its use of facial recognition technology, but found the backlash was too great.
U.K. consumers agree, with a recent survey finding that 73 percent think facial recognition in stores is “creepy,” drawing frequent comparisons to George Orwell’s "Big Brother." By discarding facial data, stores can avoid this concern, but they also lose useful demographic data, such as gender and age.
Tracking Devices With Wi-Fi
Many people consider their faces to be more personal than their devices, despite the fact that their devices contain a great deal more information about their habits and values. Using data from Wi-Fi allows stores to adopt a more privacy-aware approach to tracking customer behavior. This is why Tesco offers free Wi-Fi to its Clubcard holders.
When customers log on, Tesco can track their path through the store and record shopping times. This data can be linked to purchase history to enhance Tesco’s targeted advertising. In larger stores, Tesco sees how long customers spend in each department, providing data that can then be used to build more accurate key performance indicators to compare performance between stores.
Combining this data with mood can further enrich a store’s understanding of its customers. Mood data can be matched with path data and ambient data (e.g., temperature and music) to see how people experience different areas of the store. Equipped with this data, managers may find that changing a store’s layout helps customers feel more at home, thereby pushing them to spend more time — and money — in-store.
Mood analysis doesn’t have to come from a camera, however. Well-trained staff with a clear understanding of a store’s user experience strategy can do this, too. When stores choose to use cameras, they need to use technology that won’t store facial data and implement a rigorous privacy policy. Implemented properly, however, customer behavioral data and mood analysis can bring customer satisfaction to a whole new level.
Roberto Ugo is co-founder and chief technology officer of Movvo, a platform that measures the flow of people in physical spaces and helps retailers enhance customers’ shopping experiences.
