Companies spend roughly 260 billion Euros per year on the battle for shelf space in stores. But even though shelf space is crucial for additional revenue, companies do not always have a great handle on this area. They don’t know:
What’s happening in each store that their products appear in
Their bought market share space
Their Planogram compliance
All of these numbers need to be known by a company in order to grow successfully, and that’s not always the case -- and the way that companies often try to track it, simply through a process involving sales rep visits to stores, is very prone to human error.
Here is how RedAI works
A sales rep can go to a store (point of sale, or POS) and scan shelves with their phone, and the photos of the shelves create data. If it’s a larger-format shelf, the app will guide the sales rep as to how to take a panoramic view and capture more information.
Once the photos are uploaded, the RedAI artificial intelligence neural network scans each of them for brand and packaging (skew), and provides you this information:
Essentially, you can see the position of your products, competitor products, and gain revenue intelligence from just snapping photos. You can also get intel on your competitors and their market shares and skew launches:
It’s data integration and detail analysis for every sales channel, and it can correlate with SAP, SalesForce, Oracle, IBM, and many more.
Consider this example in terms of AI and product recognition: What if one of your clients (a POS) has not ordered any product in the last week and a half, but two shelves are empty -- or, worse yet, contain the products of a competitor? Your sales rep has not gotten to that POS yet on his/her routes. Well, RedAI can instantly tell you that there’s an issue, and the sales rep can immediately pivot to focusing on where the issue is and making sure revenue is driving from that location.
It sounds very simple. We all snap photos all the time. It is the core of social media platforms and how we communicate with distant family members. But when you add the technologically-complex RedAI neural network layer (their “magic”), you can turn product recognition from sales reps taking pictures into a revenue growth opportunity.
In our next article, we’re going to look more at AI and ML in the enterprise -- the key issues and challenges, but also the key areas of potential growth.
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