How to ensure sales strategy execution in stores, deliver value to your customers and drive sales?

Articles

After hours put into developing, producing, optimising supply chain and marketing the product it all comes down to how the product performs at the point of sale. Controlling execution for a large number of stores is one of the many challenges manufacturers and retailers are facing today.

The latest “McKinsey on Consumer & Retail” 2022 statistics show that 75% of customers have adapted a new shopping behaviour, 40% have tried new private brands, 32% have switched brands and 27% have switched the retailers they previously shopped at.

Taking this into account and the many other changes consumer behaviour has gone through in the past years, one thing remains constant – for consumers every shopping experience counts. Have you ever gone to a supermarket and thought, “It is very likely that X product is missing.” Never, right? Expectations will never be negative when going to a retailer or wholesaler, unless we have already had a bad experience.

An essential component in keeping your customer happy is the on-shelf availability (OSA) of the product at the time of purchase. Both manufacturers and retailers are battling the difficulties in assortment planning, organising and controlling compliance with sales strategies in stores. With that said, the quality, volume and time-sensitivity of the data collected from stores is priceless.
Relying on insufficient data and outdated manual methods in OSA calculations results in lost sales and frustrated customers.
Luckily, this can be avoided with leveraging correct tools, adapted to the market and current technology.

Undoubtedly, coupling Artificial Intelligence and Image Recognition technologies brings a valuable support system to retrieve data from the stores in high volume and quality, as well as process data automatically, quickly and effectively. One of the main advantages of implementing this technology is the management’s ability to react to the changes in stores in a timely manner, given the fact that it takes much less time to process the shelf data and gather insights when compared to manual, or semi-manual methods.

Recent IHL group studies show that shoppers encounter out-of-stocks as often as one in three shopping trips.

Reasons for missing products on the shelf may vary from human errors, inadequate forecasting, inaccurate reporting to ghost inventory and inefficient stock replenishment. By having the right store data at hand, you will be able to evaluate the products profitability plans and increase the ROI for each product line.


So how can Image Recognition benefit your inventory process and decrease operational costs?

Leveraging Ailet Image Recognition solution in store audit, allows to automatically collect and analyse store data, with 97% of product recognition accuracy in real-time. With Ailet Mobile App each field-team member has a set of tasks to perform at each point of sale, while carrying out inventory. Automatic calculation of OSA metrics and recommendations in real-time allows the sales representatives to perform corrective actions right at the shelf, and 10-20 seconds later the results and analytics on the assortment performance in stores will be available to the management.

As a result, empowered, agile and responsive field teams are covering more stores in less time, execution errors are corrected faster and more effectively, correspondingly followed by boosted sales, undamaged brand reputation and great customer experience.
Based on our ongoing projects with global manufacturers, the growth of OSA through the Modern Trade channel is 5-10%, while reduction in audit costs can go up to 60%. At the same time, delivering a 1% increase in sales for every 3% increase in OSA.

Adapting Ailet’s artificial intelligence in store audits encourages collaboration between all the business units involved, giving grounds for timely strategic decisions based on transparent store analytics like OSA metrics execution by category or product segment, store, retailer, which retailer contributes the most to overall OSA measurements, its dynamics and progression range.

As witnesses of the unpredictability of today’s market it is safe to say that the recent purchasing behaviour may not necessarily be the indicator for the future. And given the enormous volume of product performance data that is generated daily, it is not just a question of obtaining it constantly, but a matter of processing and analysing it correctly.

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