3 min read
Article originally posted by IronYun CEO, Paul Sun, for the Forbes Technology Council: https://bit.ly/3biw68O
Now more than ever, many consumers are choosing to shop online. Brick-and-mortar retailers need to respond. Enabling technologies can help retailers motivate buyers to choose physical stores over shopping online.
Retailers need solutions that offer valuable information about their customers’ behaviors in the store environment to enhance their experience, whether they’re exploring products in-store or buying items, and AI video analytics can provide those solutions.
What Is AI Video Analytics?
AI video analytics is computer-vision powered by machine learning algorithms. AI video analytics can monitor and analyze visual data from security cameras to improve business processes.
What Can Retailers Do With AI Video Analytics?
In multiple ways, AI video analytics can help brick-and-mortar retailers: it can give shoppers more personalized experiences, provide information to improve stocking levels, streamline floor plans into more efficient traffic patterns, improve inventory management and identify repeat customers for special promotions or services that only loyal buyers will receive. It can also reduce theft and loss and improve stocking levels.
In addition, AI video analytics can deliver real-time information so stores can better serve their customers in a variety of thoughtful ways.
Create The Ideal In-Person Customer Experience
AI video analytics can provide real-time and historic data on shopper behavior. This data can inform store layouts, product placement and the anticipation of customer needs. AI video surveillance monitoring can also reduce theft and loss and improve incident response time to create a safer shopping environment.
In addition, video data can be used to differentiate the store experience from other brick-and-mortar alternatives. Smoother, better and differentiated experiences will encourage more frequent visits and increase loyalty.
Many retailers have already begun to grasp this concept. As a result, research shows that the number of retailers investing in AI will double over the three years as they look for new ways to compete with e-commerce stores.
Optimize Product Placement
Product placement is an important part of customer experience. If visible products are out of stock, you can lose the sale.
With AI video analytics, retailers can monitor product levels dynamically and take immediate action by alerting staff so they can restock accordingly.
Additionally, if a retailer is nationwide or in multiple locations, store owners can test product placement by monitoring and comparing customer behavior between different locations.
Information based on real-world video data takes the guesswork out of product placement and saves valuable time and resources that need to be spent on other important areas of the store.
Create Personalized Shopping Experiences
Retailers can combine AI-driven data insights, shopper-approved AI-based facial recognition and shopping history to provide truly personalized shopping experiences.
AI video data can help improve traffic flow and increase sales conversions. AI-driven video data can link to store maps and shopping applications to help shoppers map out their visits ahead of time or send alerts or promotions during their visits. New shopping apps could deliver personalized suggestions based on interest, history, and current promotions.
For example, a shopper’s face and history could trigger a coupon to buy toothpaste. Or a shopper could be notified when the store becomes less crowded. These new AI-driven applications can make the physical shopping experience feel closer to online convenience, but with all the advantages that in-person shopping conveys.
Optimize The Checkout Line
The checkout line is one of the most important aspects of the in-person shopping experience. A self-checkout line is not always the answer. Most people with full carts would much prefer checkout assistance.
The intelligence behind AI video analytics is always on. It can be tuned not just to count the number of people in line but to understand dwell times, heatmaps and traffic patterns and drive optimal staff response at the checkout line. Retailers can take action by sending additional staff members into the line, opening up new lines or modifying store layouts to improve checkout flow.
AI data can also help the aforementioned shopping applications to suggest additional items to help process customers and get them out of the store quickly. You can also send targeted offers to shoppers in line that encourage them to purchase more items so they don’t lose their place while waiting.
The Amazon Go Store is a first-generation example of AI-powered retail. These stores use AI to monitor video and track items from the shelf to the basket and out the door. Advanced AI-vision solutions can enable similar functionality for other brick-and-mortar retailers to allow their shoppers to potentially skip the checkout line entirely. Or, they could suggest “missing” items to customers using the traditional line.
Revolutionize The In-Store Shopping Experience
AI video analytics provides a plethora of ways for brick-and-mortar retailers to engage with their customers by providing differentiated shopping experiences that can compete with and, in many ways, surpass that of online shopping.
Retailers that evolve alongside consumer expectations will gain a competitive edge against those that don’t.
Technologies like AI video analytics enable brick-and-mortar retailers to differentiate and compete in today’s shopping environment. AI video analytics is only one of many tools available for online retailers, but it’s already redefining how brick-and-mortar stores compete with online businesses moving forward.
How To Choose The Right AI Video Analytics Partner?
As you consider a potential AI video analytics solution for your business or organization, there are a few important things to keep in mind as you make a decision.
1. What are your specific goals for using AI video analytics?
2. How will you use the data collected?
3. How easy will it be to integrate with current systems?
4. How will data be kept secure?
5. What is the user experience like?
In the end, it’s important to find a solution that meets your specific goals and fits well into your existing processes. The right AI video analytics solution can help you revolutionize the in-store shopping experience for your customers.