Five Ways Retailers Can Improve Store Execution

Computer vision creates new possibilities and profits

Massive change is poised to accelerate in one of the last areas of the retail industry affected by digital transformation. The area in question is store execution and the transformation is being driven by increased visibility from computer vision and powerful analytics capabilities utilizing artificial intelligence. Retailers at the forefront of this movement are tapping into significant new sources of efficiency, revenue and competitive advantage.

This isn’t a claim based on unfounded hype, because even world class operators would admit they have ample opportunities to improve store execution. It’s a perennial challenge made more difficult in recent years by the industry’s increased complexity and labor issues, but retailers now have an opportunity to address challenges in ways that weren’t possible just a few years ago, and achieve rapid ROI.

Computer vision enables stores to be digitized and AI combined with optical character recognition (OCR) makes it possible to analyze data from captured images. To make digitization a reality and achieve the benefits that come from increased visibility of in-store conditions a few things have to happen first. They include:

  1. Images must be captured. This is best achieved with fixed location cameras that can either be shelf-edge or ceiling mounted. Other effective image capture techniques include the use of mobile devices such as smart phones and tablets and dedicated or multi-use robots.
  2. AI must be deployed. Stores equipped with computer vision generate large amounts of data. Extracting value from that data means AI is needed to uncover insights and recommend actions across multiple use cases.
  3. OCR is essential. Computer vision that is OCR-capable lets retailers take full advantage of AI because text on packaging and pricing labels can be turned instantly into data usable by AI.

With these fundamentals in place, retailers gain 24/7 visibility of in-store conditions to see what they have been missing and identify lapses in execution.

Why Now and What’s Different?

Technology has advanced considerably in terms of both the image capture hardware and the AI solutions needed to enhance the value of data. Retail has changed too, in ways that create urgency to improve visibility and performance because existing operational challenges are more difficult and new challenges have emerged.

For example, shopper behavior is more dynamic than ever and that puts new pressure on planograms and inventory levels. The growth of e-commerce and usage of stores as fulfillment centers creates new inventory challenges and on-shelf availability issues. Meanwhile, store sizes are changing, and store specific planograms add operational complexity and the risk of uneven execution. In addition, there are challenges related to labor such as availability, turnover, increased wages and training.

These reasons and others explain why computer vision and AI are gaining traction to address key execution challenges such as:

Planogram Compliance: This is huge issue for retailers and suppliers of fast-moving consumer goods, but one that can be fixed with computer vision. Companies spend countless hours and invest considerable resources to develop planograms based on shoppers insights that are finely tuned for specific store sizes, category trends and demand patterns that vary by geography. When planograms aren’t properly executed, the data science and merchandising expertise that went into their creation is wasted and sales and margin opportunities are lost. This use case alone can justifies the ROI of computer vision.

On-Shelf Availability: Retailers know the importance of being in stock and have struggled with the issue of on-shelf availability for years. Computer vision goes a long way toward fixing the issue because when inventory isn’t on the shelf it can be detected instantly, alerting store employees to remedy the situation, often by locating inventory in the store. This also benefits online order fulfillment because if e-commerce systems are integrated orders can be picked faster and with fewer refunds and substitutions.

Promotion Compliance and Pricing Accuracy: Improperly executed promotions and incorrect pricing are another source of lost revenue and shopper frustration. Increased visibility enabled by computer vision lets retailers know whether carefully designed promotional plans are being properly executed, whether items on shelf are priced correctly. In addition, alerts can be created to direct store associates to take action.

Labor Optimization: Labor is expensive and scarce, so it is essential employee efforts are deployed against high value activities. Computer vision helps target those activities, such as remedying out-of-stocks, while also eliminating tasks that can better be performed by technology. For example, manual daily scans can be eliminated to deploy labor to higher value task.

One Version of the Truth: Computer vision and AI enable retailers to provide a common view of the business to suppliers and service providers. The data and insights found within it are extremely valuable to trading partners who recognize increased visibility of store execution is a rich source of opportunity to increase sales, improve promotional effectiveness and quickly identify lapses in execution.

A New Beginning for Productivity Improvement

Excellence in store executions is a nut retailers have been trying to crack for a long time, especially in the fast-moving consumer goods space. Until now, solutions were largely low tech, required human intervention and physical observation, followed by time consuming and costly corrective actions.

Now, due to the maturity of computer vision and AI, store execution has gained the type of visibility common to other parts of the business. For example, shopper loyalty programs, especially those with high penetration rates, provide retailers with near perfect visibility into purchase behavior. The growth of E-commerce provides even more granularity into behavior and has given rise to retail media networks with precise targeting capabilities. Supply chain visibility also has improved dramatically over the years thanks to technology to track and optimize the movement of goods.

What each of these areas have in common is they digitize retail and generate large volumes of data which can be leveraged with AI-powered solutions. The same can now be said of the store environment where computer vision and AI are helping retailers see what they have been missing to take action and improve productivity.

Retailers focused on improving productivity in 2023 are making bold moves with computer vision and AI.  See how your organization can benefit, connect with a store intelligence expert today!

 

Want to learn more about computer vision and AI?  Check out these other resources:

 

Shelf Intelligence: What it is, How to Get it, and Why You Need it to Win

Category Planning and the New Age of Automation

A New Version of the Truth for Category Managers

 

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