Computer vision is revolutionizing foot traffic retail analytics. See how CV affects data on dwell time, time-in-store, hot spots, and more.
Retail Analytics: 5 Big Data Points to Track Through Computer Vision
If you’re not leveraging advanced data in your pursuit to grow your retail business, then you’ll have a challenging time seeing the results you hope for.
Data is now the make-or-break element that can set up a business for success. It can help you understand your customers, know who they are, how they act, and how to offer them products and services in a way in which they’d most likely respond.
Gathering this data falls to customer analytics, and retailers should take a closer look at how they are collecting this information and what they are doing with it, especially if you’re not already leveraging Computer Vision.
How Does Computer Vision Work in This Context of Retail?
Computer vision (CV) is an AI-enabled technology that helps digital systems recognize and understand the content of images, similar to how people use their eyes and brains to make sense of the world around them. When you add a photo to your Facebook and the network recognizes one of your friends and asks you if you want to tag them, that's computer vision in full action. But, there's more to CV than just tagging people on social media. This AI-driven technology can translate an image’s content into actionable data that identifies significant trends, outliers, and patterns that can impact a business.
With CV, you can utilize your pre-existing cameras and sensors to gather real-time information. Retailers now can gain deeper insights into customer behavior and act on that information to boost revenue faster than ever before.
Retail analytics is essential to helping you understand how to improve your operations to directly encourage customers to buy more and return to your store. Without data, all the measures you employ are essentially educated guesses.
Computer vision is the most comprehensive and accurate method of gathering data. It represents a potentially 24/7, real-time approach to data aggregation that is not subject to human error or bias like surveys and secret shoppers. The technology also allows you to drill down into a broader range of details than through your POS system.
What Are the 5 Important Data Points to Begin Collecting with Computer-Vision-Powered Retail Analytics?
Here's an interesting fact:
90% of the shoppers who don't get the help they need leave empty-handed. But, when their needs are met and their questions answered, 86% of them will buy more than planned.
You may think that the solution is to simply hire more staff, but what if there was a smarter way that did not cut into your profit margin and add overhead? A better strategy would involve deploying computer vision to solve business challenges like in-store conversion rate and time-in-store. Here are five powerful ways retailers are leveraging CV in their stores as we speak.
1. Shop Times
Through Computer Vision, your store can gather essential customer behavior analytics regarding when they like to shop:
- Average shop times, even across a particular time of year, or time of day
- The shop time for an individual customer
Yes, CV gets you the scoop on customer shop times but can also help you understand macro-shopping moments and the level of service your shoppers are receiving. Decreasing time-in-store could be attributed to a corresponding decrease in the level of service and attentiveness from employees, for example.
Tracking shop times with Computer Vision can help you increase the number of people buying something, the number of products they buy, and how much they spend in your store. It can also help you discover a few patterns that might not be working in your favor. For instance, if you notice you have a lower average shop time at a particular time of day because your customers seem to be in a rush, it might not be the right time to come out with your best offers during this specific window.
2. Where Your Customers Go (or Don’t Go)
Consider the potential of these retail metrics:
- What sections are visited most or least often
- Various hot spots and dead zones
You can then use this data to learn how your customers' shop. Let’s assume you have 100 people who look at a particular shelf, but nobody picked up any products from it. Maybe the actual products aren’t what the customer expected, or their placement needs a bit of work to allow shoppers to see the offers better.
3. Dwell Time
Dwell time refers to the length of time a potential shopper spends looking at your display. It's an essential metric as the longer the time a person spends looking at your display, the higher the chances they will buy something.
But do you have data on this behavior?
Customers pass by your store, but they don’t come in. How many come in? How many stop to look at featured in-store displays, or do they just pass by? Might some of them leave but then come back?
They are all impossible to answer accurately without the use of computer vision. Suppose you have a camera that captures the front of a store looking at those passing by. And when you spot potential customers dwelling, you get that data to your dashboard, which can reveal specific changes you could be making to convince dwellers to cross the threshold.
4. Cut Down Time-in-Line
No person on this Earth likes waiting in line, and they greatly appreciate any effort retailers make to smooth out the process as much as possible.
Through CV, you can see the average time your customers spend waiting in line in real-time. You get notified when the time frame increases, in which case you can send more staff to the checkout point to resolve this issue.
It could also reveal certain personnel issues by comparing average checkout times between cashiers. The data could reveal that between two cashiers, one had a 10 minute longer average waiting time. If you look at the register, you can also see there was less revenue as a result. This cashier might require extra support or training to perform their tasks efficiently.
5. Pick Up and Put Backs
A customer picks up an item, and instead of putting it in their carts, they put it back on the shelf. By itself, it’s not such a big deal, but through CV, you could see this is not an isolated event.
Instead, it’s a pattern. Multiple of your consumers end up acting the same way. It could be an issue with the actual product or an offer that’s not enticing enough to make them spend money.
By identifying the pattern and the problem, you can make the necessary adjustments and increase your conversion rates - the number of people who buy something rather than just browse.
Increase Your Store Revenue with AlwaysAI
Computer Vision and big data analytics aren’t trends that retailers can afford to skip. They have a genuine impact on your operations, and with the right approach, the customer behavior analytics you track can help you grow your business.
alwaysAI makes it easy to build, deploy, and analyze the results of advanced CV initiatives.
You don’t have to have a team of data scientists and top-flight machine learning developers on board to truly leverage CV. alwaysAI’s team of world-class machine learning experts is here to support your deployments, model development, and application-specific needs to ensure your project meets multiple business objectives.
Choose a pre-trained computer vision model from the alwaysAI catalog that fits your goals, or upload your own model; then train it locally or in the cloud using our model training features. Finally, customize your app with alwaysAI’s powerful Python APIs.
Simple, scalable deployment
Deploy your application easily and quickly to your existing edge infrastructure on a wide variety of devices. (ARM-32, ARM-64, or X86)
Completely custom CV solutions
Design, train and improve applications tailored to your business needs. Expand the scope of your applications with custom analytics solutions for use with 3rd party BI tools or internal systems.
Learn more about retail analytics in our video series: The Business of Computer Vision: Customer Analytics.
alwaysAI provides developers and enterprises a comprehensive platform for building, deploying and managing computer vision applications on IoT devices. We make computer vision come alive on the edge - where work and life happens. The alwaysAI platform offers a catalog of pre-trained models, a low-code model training toolkit, and a powerful set of APIs to help developers at all levels build and customize CV apps. alwaysAI has an easy deployment process and a state-of-the-art run-time engine to accelerate computer vision apps into production quickly, securely, and affordably.
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