eLeader Shelf Recognition AI
Auditing a store display poses significant challenges. First, the task involves identifying an exceptionally of different SKUs, (up to several hundred large stores). Secondly, each FMCG producer has their own vision of stacking goods on shelves and measuring display parameters. The volume of sales depends on the attractiveness of the shelf and the availability of products to the consumer.
Monitoring this area is an important business process. The eLeader Shelf Recognition AI application cooperating with SFA / FFM systems is a modern tool supporting the implementation of these tasks. Its main functionality is counting and measuring key parameters of product display. It is all based on a photo of the shelf taken in the store. It replaces the tedious and error-prone manual operation.
Your display, the silent seller
Research shows that as many as 75% of purchasing decisions are made in the store shelf. The optimal shelf is one at eye level (although, of course, the display strategy covers the entire shelf from bottom to top).
We know from research and life experience that visual impressions are crucial for purchasing decisions made by customers, therefore special attention should be paid to such aspects of visual product presentation, i.e. KPI, as shelf share, display height, number of perceived products (facing) and the corresponding parameters of your competitors’ products.
Thanks to eLeader Shelf Recognition AI, a sales representative will recognize products on a store shelf using photos, this way reducing the shelf research time from a dozen or even several dozen minutes to just a few. In short, image recognition technology helps retailers and manufacturers understand the market and react quickly to changes in the business environment.
We know that you care about the best display of your products, so you need to be sure that your people will arrange the shelf in accordance with the applicable standard.
Providing consumers with free access to our products requires constant analysis and maintaining high display standards in stores. The image recognition technology in the eLeader Shelf Recognition AI application effectively supports our sales representatives in these activities. Thanks to it, they report incomparably more detailed information on store shelves compared to the period before the system implementation.
Paweł Kaczyński
Business Systems Analyst
DANONE
Comprehensive analyses
Accumulation of data in the form of reports provides information that allows for multi-faceted analysis, verification of assumptions and the subsequent planning, i.e. Category Management. The eLeader Shelf Recognition AI solution guarantees information better quality and more objective information than the declarative display status of products, with carries a high risk of error.
The data is irrefutable – we have almost 100% recognition accuracy. You can reuse data are for secondary analysis and new reports. Data can be easily fed into any report – from Excel to Microsoft Power BI, which you can receive with eLeader Shelf Recognition AI.
Do you wish to know what competitive advantage you gain with AI-assisted store shelf analysis and what you can learn about your competitors thanks to this analysis? Or maybe you would like to know what problems can be solved through the automation of a store display audit? Download the ebook to find out more about our eLeader Shelf Recognition AI?
