How Computer Vision Helps Improve your Retail Stores

How Computer Vision Helps Improve your Retail Stores

What is Computer Vision?

Computer vision is a technology that lets software acquire, process, and analyze images. In the very beginning, this technology was only adequate for basic object recognition. However, modern computer vision systems have proven they can do much more, such as facial recognition and other complex visual analysis.

When artificial intelligence (AI) is paired with computer vision, you end up with software that can perform much more demanding tasks. For example, you can write software that can analyze and classify thousands of images and video feeds in real time. This category of software relies on convolutional neural networks to process and categorize visual data very quickly. This process delivers highly accurate results and allows for advanced computer vision machine learning.

Thanks to more efficient algorithms and easily accessible computing power, modern computer vision analytics software can run on inexpensive computing devices.

Computer Vision use in retail

Retailers and brand owners have an abundance of options for optimizing store sales, testing new promotions, and monitoring employee performance. For years, computer software tools have empowered retail managers so they could make better decisions.

These software solutions relied mainly on financial data analysis and various other sources of business information.

Computer vision goes beyond simple business data analysis. It captures a true snapshot of what’s currently happening in real time. It lets managers visualize accurate information about any store, or area within each individual store.

This explains why computer vision has become an essential component in the retailer and brand owner’s tool set.

Store management benefits

Computer vision lets store managers track the performance of different areas within their store.

They can also:

  • Assess and compare the performance of different products sold in-store.
  • They can test the performance of various product mixes, and the performance of various promotions within their store.
  • They can optimize staffing levels in real-time and respond to customer traffic as it ebbs and flows during the day.

Senior management benefits

Senior managers working at the corporate office can start with an overview of the entire retail chain’s results. They can also drill down to individual stores or specific areas within each store.

Senior managers can:

  • Gain useful insights into customer shopping patterns so they can better plan store remodels and next-generation store layouts.
  • Make decisions based on factual data that is constantly updated and analyzed.
  • Respond to new trends and styles faster than when using traditional business analysis tools.
Attention span

Computer Vision Examples

Retail analytics software

Computer vision software applications produce meaningful and accurate data for retail store owners and operators. The software delivers actionable insights that management can use for retail sales forecasting and analysis. For example, retail buyers can rely on retail analytics reports to plan their purchases based on real data from each store.

Retail data falls under the following categories:

  • Footfall and customer counts: Computer vision can distinguish between new and returning customers. The technology can also recognize store staff and exclude them from footfall reports. Vehicles can also be detected and counted using this technology making it great for store pick-up data.
  • Demographic data: Computer vision can detect a person’s age and gender to produce highly accurate attendance reports.
  • Length of stay: Find out how long shoppers stay in your store, or in any department to determine “hot” and “cold” areas. This is a great sales floor planning tool for any location.
  • Customer wait times: Measure the time waiting for service to identify problem locations. Excessive wait times can indicate store staffing or planning issues.
  • Shopper’s attention span: The time spent looking at a store display or digital screen is a great indicator of the viewer’s interest.

Since retail analytics data is very useful to brands, retailers can share this data with vendors and brand owners. This way, they can work together to improve their product labeling, packaging design, and product features.

Digital Content Optimization

Digital signage has evolved beyond traditional advertising and promotional mediums. The digital signage screens deliver programmed content that is specific to each venue. The programming can be adapted based on the time of day or day of the week. This is the usual model that most retail organizations rely on to deliver content on their store’s digital screens.

Retailers have invested massively in in-store digital screens to inform, entertain, and motivate. They use digital signage to promote their merchandise and loyalty programs, help people navigate their stores, and provide useful information that shoppers want.

One issue facing many large retail operations is the manpower required to manually update and program content. This is especially difficult for national and international retail chains that extend across multiple time zones, provinces/states, and where languages differ.

In these situations, computer vision can take over each digital signage screen’s programming. It will ensure the best content is shown to each viewer without any manual intervention.

Here’s what happens when you interface your company’s digital signage network with computer vision.  You get a powerful content delivery system that adapts to the audience in real time.

Counting more than people

Computer vision can do more than just count people. The technology can be adapted to recognize vehicle types. This is extremely useful for any retail business that offers drive-through services or monitors outdoor signage effectiveness. It’s increasingly important for brick-and-mortar businesses to track and understand vehicle traffic patterns so they can make better business decisions.

Privacy Implications of Computer Vision

People have been worried about their privacy due to the increasing use of digital cameras in public spaces. They are concerned about being identified or tracked without their consent.

However, these worries are unnecessary because professional computer vision analytics software doesn’t keep any personal information. It scans and understands images but doesn’t save or store them in the system.

It’s important to distinguish between surveillance and analytics software, as both use computer vision technology.

Surveillance software is used to identify and track individuals in monitored areas, like for controlling access or preventing theft.

On the other hand, computer vision-based analytics software has a different purpose. It counts people or analyzes the characteristics of people looking at a screen. The data generated by this type of analytics software is anonymous and respects everyone’s right to privacy.

About Aquaji Computer Vision Software

Navori Labs’ Aquaji software combines Artificial Intelligence and Computer Vision to generate real-time, meaningful, and actionable data. The software utilizes a network of digital cameras to gather information, and a supported endpoint device analyzes the data.

Each endpoint collects and sends the gathered information to a backend server responsible for organizing and presenting the data in a user-friendly manner. Aquaji users can easily access the data through the software’s secure dashboard. The user interface is designed to be intuitive, requiring minimal training. Users can quickly generate valuable reports within minutes.

Importantly, Aquaji’s features can easily adjust to comply with local privacy laws, ensuring data protection.

Aquaji supports various popular hardware devices, including Navori’s own StiX 5700, Windows PCs, and Philips Integrated Displays.