Using human faces as a lever, facial recognition in retail creates new growth avenues, while helping offer next-gen customer experience. As a new paradigm in retail data economics, its application offers retailers endless possibilities to improve operationally as well strategically.
Face value matters a lot, and businesses are always keeping an eye on it. Wait! Wait! Are we talking of the stock and investment market? Well, it is true that the term “face value” has its implications on a business’s finance, but here, we are talking about the real value of a “human face”.
Each human face is valuable and is uniquely important to make profits and enhance ROI. At least, in the retail domain this is becoming largely evident.
Every single day, hundreds and thousands of people visit retail stores. But with their visit, they create an opportunity for retailers to build seamless campaigns, better product positioning, decrease the shelf life of non-sellable goods, and craft customer-specific strategies.
With facial recognition at their disposal, retailers can convert their retail stores into experience hubs, understand customer sentiments rightly, and build a long-term strategy to improve the bottom line. Retailers can link the technology, virtually to any initiative that improves customers’ in-store journey.
Apart from such primary benefits, facial recognition-based behavioural analytics offers several other benefits. For instance, FaceFirst analysis revealed that the use of the technology can reduce the occurrence of in-store violent incidences by an astounding 91%.
Facial recognition in retail thus comes with many overwhelming benefits. Before we take a deep dive into understanding the potential use cases of the technology and its underlying benefits, let’s understand how it works.
How facial recognition in retail works
Facial recognition in retail works as a three-step process, viz. face detection, face expression detection, and expression assignment to a certain state of emotion.
In face detection, facial recognition exploits all nodal points on a human face to form input metrics like the length of the jawline, cheekbone pattern, depth of the eye socket, nose width, distance between eyes, lips etc. The mathematical function then develops a faceprint and stores it in the database. During the person’s second visit, it tries to find the faceprint in the database. If the match is found, then the system initiates the required action.
Facial emotion recognition (FER), which is the subset of facial detection, drives facial expression detection. It maps and categorizes expressions into different categories - joy, anger, surprise, unhappy etc. Unlike facial detection, facial emotion recognition doesn’t just restrict itself to person identification but offers a next-level identification, and, thus, is more sensible in retail facial recognition.
Potential use cases of facial recognition in retail
Retailers by gleaning insightful information from facial recognition technologies can improve the entire retail function. Discussed below are some important applications areas in retail for the application of facial recognition.
Stakeholder identification
Who enters retail stores matters, because of the implications each enterer has. Right from customers to employees, each stakeholder who enters a retail shop consumes the system’s time to authenticate and categorize identity. Facial recognition improves the efficiency of entry points by making identification not only quicker but also secure.
In retail, employee honesty is as important as customer honesty. As per NRSS’s 2017 study, employee dishonesty accounts for 33 percent of losses. Overcoming the limitations of traditional approaches, facial recognition serves as a powerful monitoring mechanism to identify guilty individuals.
Mask Detection
Unprecedented times often require great and innovative aspects to see through. Facial recognition has been a true blessing to the retail landscape in the pandemic situation. The majority of retail chains have installed high-end facial mask detection systems at their stores.
Earlier, the technology was restricted to detecting masks for employees, but with the situation intensifying, retailers began mulling the wider implementation of the system to check for the visitors who are not wearing masks. Indeed, mask detection is one area where facial recognition can do wonders.
Self Service Checkouts
In the UK, retail outlets are already working with tech companies like Optimum Data Analytics to integrate facial recognition at self-checkouts. Apart from optimizing operator efforts at checkouts, the application comes in handy to streamlining activities like age authentication for alcohol purchases.
Retailers are increasingly sensing the opportunity for digital checkouts, and thus facial recognition in retail is getting traction. Preventing customers from the hassles of using credit cards or even smartphones, point-of-sale terminals enabled with the ability to scan faces, revolutionizes the entire transaction pipeline at checkouts.
Theft Monitoring
On top of real-time scan and track alerts, the face recognition-enabled cameras use machine learning to develop context-aware alert systems. These could involve detecting and flagging anything from shoplifting, aggression to threatening body language.
In fact, theft monitoring is the foremost area that strongly prompts retailers to leverage facial recognition. Retail giants like Walmart have experimented with facial recognition to prevent thefts in their stores. Walmart had even used the technology to analyse and understand if a customer’s mood is inclined toward committing theft.
Conclusion
Image recognition for retail execution works as a profit enhancer for retail businesses. In the entire spectrum of biometric solutions, it is one component that carries immense long-term benefits.
Being used to smooth buying funnels of online stores, today’s customers demand a similar experience even in the brick-and-mortar model. Since stores’ physical presence will continue to dominate, the adoption of facial recognition holds the key to refining customer journeys.
Successful facial recognition in retail, however, calls for careful consideration of contextual factors. In the absence of an expert AI team, complexities may go unaddressed. So, encountering obstacles in in-house implementation don’t waste time in experimenting with options. Partner with ODA and be the first and the best mover in face recognition technology for your retail setting.