Computer Vision led Digital Transformation for Grocery Retail Stores
The Covid-19 pandemic has accelerated a wide shift in the way consumers shop today. They are looking for convenience and discounts while buying grocery. However, by 2026, it is expected that up to $700 billion in revenue will have shifted from traditional grocery to other formats and channels.
It is clear that grocers who are capable of changing their business models by capturing value from new technologies will thrive. In recent years, technologies that are driven by Computer Vision and AI have rapidly emerged and are reshaping the grocery retail industry.
The History of Computer Vision
It is no longer enough to just monitor transactional data and expect your grocery business to grow. There’s a real, great need for capturing millions of daily events and interactions – shoppers pathways inside the store, traffic count, and conversion – and analyzing this data to optimize the customer experience.
Grocery retailers can easily capture data from their existing video camera infrastructure and convert it into actionable insights. Using video analytics software, retailers can take data intelligence to the next level.
For instance, Deep North, with its video analytics solutions, provides real-time predictions into the store traffic and occupancy in a retail store based on historical footfall data. This information can be used to further prescribe the optimal staff deployment to provide adequate customer assistance. The inability to offer a personalized shopping experience due to a lack of information on customer profile and journey largely affects grocery revenue.
Let’s look at how the use of video analytics solutions, driven by Computer Vision and AI, can help improve decisions to optimize cost, enhance shoppers’ experience, and increase operational efficiency.
Important Use-Case of Computer Vision in Grocery Business
In-store ROI Driven AI Insights
Footfall analytics refers to measuring the number of people entering a store. This KPI is particularly important as it helps retailers understand the impact of marketing on driving footfall into the stores.
By analyzing patterns such as day-of-week and hour-of-day footfall, retailers can predict live store occupancy. Real-time alerts can be triggered to control people counts in store. This is critical in the wake of the global health crisis, where the number of persons permitted in space is limited.
Deep North’s footfall analytics solution enables retailers to gather information about customer demographics, including gender and age range. Marketing and merchandising teams can use this data to plan promotional campaigns and ensure the store offers items of interest for each demographic.
A study revealed that 75% of retailers lose customers due to long wait times. Crowded queue lines decrease consumers’ shopping motivation and result in a high queue abandonment rate.
Queue management solution is about measuring how many customers line up at any given hour of the day and how much time they spend waiting. These insights can help predict queue length at any time of the day and send out real-time notifications to assign new cashiers.
Thus, store managers can optimize service quality and enhance customer experience while lowering employee costs.
When sales associates perform optimally, the store operates smoothly, and customers enjoy a good in-store experience. This results in high customer satisfaction levels, leading to increased sales, more revenue, and a higher profit margin.
By tracking store traffic, store managers can predict the optimal number of staff required at any given hour of the day. In fact, Deep North’s video analytics platforms can send out real-time alerts if a store associate is missing from a particular zone or a department.
Good in-store management means there should be enough attendants on the sales floor to cater to the needs of every visitor.
“Deep North helped one of its clients connect associates to customer needs.’ The company saw a whopping 10% increase in its revenue growth and almost $1.5M incremental revenue just from one store.”
Shopper Journey and Engagement
Grocery retailers can track visitors’ interactions with objects using video analytics – and understand how much time consumers spend in certain areas of a store. Grocery managers can also track the paths that customers take when navigating inside the store.
This navigational and dwell time data enable grocery managers to observe trends of customer activity and optimize store layout based on deep insights. They can use the same data to predict crowds and manage queues proactively.
In addition, retail managers can enable strategic deployment of store associates based on traffic hotspots where consumers tend to dwell more.
Navigational trends, in particular, also help identify underutilized spaces in-store, which can further be used in improving traffic flows, optimizing floor planning, and better merchandising. These factors are critical in influencing and increasing in-store conversion.
End Cap Analysis
Video analytics help analyze shopper’s behavior and identify which end caps are most visited, which needs to be improved, and how they interact with the products and brands that are placed there.
This information can be useful for operational managers to enhance each of the end caps within the store and optimize them for better results. They can determine the attractiveness of the merchandising, improve its store layout, and drive impulse sales to the maximum.
With all relevant data in one place, marketers can devise more adaptive sales strategies and make smart decisions to further increase product visibility and revenue.
Calculating retail conversion tells you the percentage of people walking to the store and converting into actual sales. This KPI helps you understand how well your store is performing. Based on this metric, store managers can strategize the type of products to stock, staffing, and service – and drive conversions and basket size improvements.
When store managers also track the number of people walking to a specific zone from another zone, known as capture rate, they can use this information to strategically display products to maximize product visibility. For instance, it would be good to position low-priced, impulse buys near the red zone (most visited area of the store).
And, if stores are trying out a new advertising approach, the conversion rate will tell if it is helping or hindering their bottom line.
ROI Driven AI Insights – Back of the House
The Bureau of Labor Statistics (BLS) shows that workplace injuries cost the U.S. economy roughly $52 billion to $60 billion per year collectively — that’s at least $1 billion per week. Simply put, accidents and injuries can land retailers in financial and legal hot water.
Implementing video analytics solutions in the grocery industry can help prevent a variety of injuries and accidents. It can detect any spillage of colored liquids or fluids that may result in accidents, compromising the occupants’ safety and leading to hefty lawsuits at times.
Fall detection solution can also generate a real-time alert whenever a human being falls inside a store. It enables store operators to provide quick assistance for the safety of customers and employees. This also results in an enhanced customer experience.
Amid the backdrop of a pandemic wave, it’s crucial for grocery stores to maintain adherence to mask-wearing, social distancing guidelines, and workplace hygiene.
By integrating Deep North solutions with video cameras, retailers can contain the coronavirus transmission and prioritize employees’ safety at work. With mask detection capability, conveniently monitor large crowds throughout the day and get alerted in case of a breach.
Store managers can also monitor the schedule and coverage of sanitization measures and the total time taken for each cleaning activity. Video analytics can further enhance customer experience by ensuring that staff members are wearing appropriate uniforms at all times, such as hair nets in the Deli section or complying with handwashing guidelines in the bathrooms.
A video analytics platform can also be used to configure a mobile-based alert for unattended objects within a store. It can raise intrusion alerts whenever someone is being seen trespassing or loitering around a restricted zone for quite some time. Extended dwell in areas with restricted facilities or having entrance to a valuable inventory store can indicate an intent to commit a crime.
An average of 1.44% of the revenue of retail stores is lost due to shrinkage – theft, employee and customer malpractices, and inefficient business practices. These real-time alerts can help detect suspicious behavior and safeguard the warehouse valuables while ensuring your employees’ personal safety.
The competitive nature of the grocery retail industry has led to the evolution of innovative technology for tracking customer behavior and journeys and providing a superior shopping experience. Grocery businesses need to act on opportunities faster than their competition to gain a real strategic advantage.
AI-led Computer Vision enables grocery businesses to personalize customer offerings, make informed decisions about marketing and layout strategies, and make long-term plans to ensure that shoppers keep coming back again.