Shelfie
Shelfie :- Reimagining Success through One-Stop Cloud Service

I magine walking into a store, excited to buy yourself a dress that you had eyed for so long, just to find out that it is out of stock! Struck by disappointment, would you even consider going back to the store to buy something else in the future?

A study by The Harvard Business Review in 2004 reported that nearly a third of consumers opt to buy an outof-stock product elsewhere. And this has become a common scenario for most retailers these days. Often store owners ignore gaps in their inventory, figuring the fix is more expensive than the problem. Surveys reveal retailers, due to faulty in-store ordering and replenishing practices, put themselves in dire situations by ordering too little or too late by depending on inaccurate demand forecasts or otherwise mismanaging inventory.

This is where companies like Shelfie are playing an active role in changing the narrative. With images and data crowdsourced from shoppers, Shelfie is giving marketers better store visibility so that they can reduce stock-outs and boost their customer experience. Headquartered in Boston, Shelfie eradicates the need for manual processes and provides the latest app to tackle image processing and crowdsourcing. This enables the customer to take pictures of empty supermarket shelves and let stores know what items are out of stock.

With deep learning technology embedded in them, the Shelfie cameras are transforming retail by bridging the gaps between shelves and retail owners.

In fact, the open APIs assure shop owners of a universal integration with existing point of sale systems. Through a data-driven approach, the company turns the status of shelf stock into real-time insights that are immediately available both at the store and head-office level. This allows retailers to take knowledge-based operational decisions and maintain onshelf-availability (OSA) round the clock.

At the outset, Shelfie ensures a smooth flow of sales from the warehouse to the customer by eliminating chances of loss and effective stock replenishment activity. The company, through its robust cameras, is playing a pivotal role in the automation of menial stock monitoring tasks and liberates floor staff to focus on serving customers towards increased average basket sizes.

In essence, the Shelfie cameras can be mounted on top of any mounted shelf and capture images of retail items, which can then be transferred to the cloud. As a next step, the cloud-based advanced machine learning and image processing algorithm is used to analyze shelf images. Upon detecting an event, the data is further sent to the concerned dashboard and mobile app, informing floor staff to re-stock specific items. The instant analysis of the gap ensures that stock is readily tracked and issues pertaining to the non-availability of items are solved at the very moment. Also, by minimizing chances of stock-outs, Shelfie is optimizing sales revenue growth and subsequently improving consumer propensity to purchase.

Backed by many accomplishments and contributions to the retail industry, Shelfie is introducing the unparalleled benefits of digitalization to the new generation of retailers. The company is committed to break the chains of inefficient, traditional practices and introduce a greater level of in-store productivity. By choosing Shelfie, retailers will undoubtedly pave the way to enhanced service speed, streamlined business processes, and greater consumer engagement.