Do you run a grocery chain, manage multiple pharmacies, or spearhead local specialty stores? There’s a technology that can make your retail business more fruitful by using visual data and protecting your locations from stockouts due to poor planning. This technology flaunts its best features with image recognition software in retail, and here’s how it works.
Image recognition technology explained
Is that a monkey or just a cat in a monkey costume? When you see an image anywhere, you instantly recognize what’s in it — that’s something very basic for humans. You don’t have to break it down into smaller pieces to identify what you see.
Machines can’t do that. They are inferior to the human brain when identifying visual data. To make up for this inferiority, machines follow a multi-step process to decompose an image and analyze pixels and patterns before they can accurately name an object in the image.
That’s how image recognition software works, in simple terms. More technically, the image detection process is performed within a convolutional neural network (CNN) using machine learning (ML) and computer vision technologies.
When a CNN comes across an image, it analyzes it step by step. It may first detect the colors and edges before identifying more complex elements like the shape and dimensions of an object in the image. This process is carried out within CNN layers with extensive visual data filtering and validation in between.
To visualize what image recognition software would do to recognize one, you can think of these five steps:
- Image type detection: To identify an image type and whether it’s relevant to the visual data analyzed for a specific use case.
- Data classification: To classify the patterns of visual data like colors, dimensions, and shapes.
- Feature detection: To compare image features with pre-labeled data and identify the feature in question.
- Data extraction: To distinguish visual data and objects in an image.
- Image classification: To recognize an image by classifying and tagging everything depicted in it.
In retail, image recognition software is perfect for identifying and grouping visual data coming from product displays, shopping aisles, and in-store shelves. Keep reading to find out why it’s a big deal for your business.
How can you use image recognition software in retail?
Image recognition technology can help you grow your income, one way or another. Visual data taken across your retail stores is awash with insights you can use as pristine as they are or combine with predictive analytics to make better business decisions. Here’s when these insights are the most effective in the retail industry.
Ever tried to put a price tag on out-of-stock events? It might have too many zeros, as retailers get $1 trillion less than they could every year because of stockouts. This gives grounds for a proven use of image recognition software in retail to check facings and product displays for out-of-stocks in real-time. It can analyze images of shelves within seconds to alert your employees of the goods that need to be replenished.
Discounts, promos, and frequent repricing are often the culprit of mispricing products. If you operate dozens of locations with thousands of SKUs, the mispricing risk increases with every manual process your staff performs. With image recognition technology, however, you can rely on your software to monitor current product prices and identify inconsistencies at each store.
Foot traffic tracking
Image recognition software can detect what’s going on on your shelves just as accurately as how many shoppers visit your retail locations daily. Foot traffic numbers unlock great insights into managing your stores so that you can see the busiest areas, come up with the best product placement ideas, and avoid overstaffing/understaffing issues.
If you cooperate with many manufacturers and brands, it may be difficult to use your retail space according to all their planograms. And what if you have your own planograms for your own products? That’s when image detection enters the scene for easier merchandising and planogram compliance. Your software can spot inaccuracies across your stores, so you can plan immediate action and make the most of store layouts.
Even though barcode scanners are fine for most SKUs and are easy to use by shoppers, image recognition technology can improve your customers’ self-checkout experience. Based on this technology, your system can tell apart products of the same type, like fruits, by identifying their distinguishing features without barcodes. This will simplify the self-service, non-assisted checkout process.
Why is this huge for your retail business?
Looking ahead: you will unlikely build the perfect store to outperform Walmart with image recognition software alone. But you can improve the customer experience and rake in more profits with it. Depending on which use cases you roll it out for, image recognition technology can transform the way you:
- Sell. Using image recognition software in retail is closely linked to increased sales. These can result from more accurate pricing, optimized on-shelf availability, smarter planogram execution, or all at once. There’s an untapped sales growth opportunity by simply eliminating lost sales due to stockouts, which take 46% away from retailers’ profits.
- Serve. In retail, the customer experience is the next touchstone of success. Image recognition software enables you to excel at the major aspects of the great customer experience: product availability and lightning-fast checkout. Today’s shoppers often complain about this, so minimized out-of-stocks and optimized self-service checkouts are the best ways to respond to their complaints.
- Audit. Whether you audit your locations on your own or hire third parties, image recognition software can save you a great deal of money. With it, you no longer need to schedule checks in advance, send teams to faraway locations, and take notes manually. Real-time object detection technology speeds up data collection, reducing in-store audit costs and making the necessary improvements faster to implement.
- Grow. Visualizing retail operations gives you insightful clues about sales trends and market opportunities. What is hard to detect using quarterly reports is now visible with real-time image data taken across your locations, including high-demand SKUs and shifting shopper behaviors. This comprehensive coverage lets you quickly adapt to any changes in retail to grow your stores.
- Retain. The understaffing problem sets alarm bells ringing in retail. To boost retention, 39% of retailers are pumped to make routine tasks easier for their employees with technology. Doing so with image recognition is a timely move to take the complexity of in-store audits and inventory management off your employees and improve job satisfaction at your stores.
These benefits of image recognition software in retail are quite universal. They apply to grocery stores, specialty stores, pharmacies, and other locations if the technology is properly implemented and you act smart with visual data insights.
Cost of implementing image recognition software in retail
A lot goes into developing image recognition software. Whether the cost of your project is going to be in the area of $10,000 or $100,000 is determined by:
- Availability of datasets
- Hardware costs
- CNN development costs
- Software type
- How many locations you run
In retail, image recognition software is often implemented via an API to reduce development costs and get an image detection system up and running faster. It can be deployed within 1-2 months for small to medium retail businesses but requires ongoing data storage and image capturing investments. Still, a custom API can accurately match the capabilities of your other software and retail operations — something third-party APIs are bad at.
The cost of developing a custom, cross-platform image recognition system with unique deep learning algorithms from scratch may be dramatically higher. If you want your software to have extras like predictive or prescriptive analytics and handle real-time visual data across a multitude of retail locations, you’ll likely need to invest hundreds of thousands of dollars. The development time will also increase.
Check out our blog post on image recognition app development costs for a more detailed cost breakdown.
Challenges of implementing image recognition software in retail
Creating image recognition software starts with images. But it isn’t easy to capture them for real-time object detection and classification. There should be tons of images taken with high-end cameras or digital sensors. How good your hardware is and how well it’s calibrated can affect the quality of images, which should always be high for your software to recognize what it sees.
The image quality issue isn’t the only image-related challenge. The more images you capture and the higher-resolution they are, the more space they will take up in your storage system. This may become an ever-worsening problem as you add more stores to your software to analyze shelf data. That’s why developing your software with cloud storage is a smart move to ensure that physical storage capacity isn’t a limiting factor for scalability.
Another challenge may arise when building a CNN. You don’t need to create every element of an object detection system from scratch — even for a custom project. Building a unique CNN and training your software with unique datasets may take months and thousands of dollars. On the other hand, using pre-trained network models, like VGG-16 or ResNet-50, and easy-to-access computer vision libraries, like OpenCV or VXL, is an efficient way to deploy your software quickly.
It wouldn’t be a piece about challenges if it failed to mention data security. Just like other data types, visual data may jeopardize shoppers’ privacy if it:
- Is improperly captured
- Recognizes human faces
- Is stored without stringent security standards
There must be comprehensive scene understanding and careful reasoning behind every shelf or shopping aisle image to prevent the unintentional disclosure of sensitive data. Additionally, you’ll need to invest in computational and hardware security, whether you use cloud or on-premises storage. This is harder to do on-premises than with Google Cloud Platform or other time-tested, robust cloud storage systems.
Unicsoft has been around for 15 years and has earned explicit recognition from Gartner, GoodFirms, and the Clutch community since we arrived on the technological scene.
Retail is one of the industries we focus on to empower business owners with technologies they consider too costly or hard to implement. Getting your image recognition software developed and deployed with Unicsoft is a fully guided experience based on our cross-domain expertise and full-cycle services.
Your image recognition software isn’t going to be the first ML and computer vision project for us. Explore some of the latest implementations by Unicsoft:
- Image recognition app for pharmacy shelf monitoring and real-time data grouping. Here’s how we created it.
- Product detection and recognition tool for shelf management at supermarkets. Go here to learn more about this case study.
We can help bring computer vision into your retail locations and have everything business owners need to embrace this technology.
The bottom line
Is image recognition software worth it in the retail industry? If you care about your out-of-stock rate, sales, in-store audit costs, and the customer experience you deliver, this software can be more rewarding for your business than you might think.
Is it going to be easy to amass images across your stores and build a neural network with computer vision to implement image recognition software in retail? Probably not. Many challenges must be overcome along the way to ensure the accuracy of visual data insights, reasonable technology adoption costs, and consumer privacy.
The great news is that no challenge is too tough with Unicsoft. Let’s talk about the issues your retail business is facing and how we can implement image recognition technology to solve them.