By

Martin Hitch

|

November 20, 2018

Retail 4.0 - IoT & Mapping Technologies

Mapping technologies have allowed us to become intrepid explorers, granting access to the most remote corners of the globe. They’ve minimized the time it takes to get from Point A to Point B through step-by-step directions, which in turn has greatly reduced the anxiety of getting lost. More recently, these technologies have helped consumers discover new and exciting places, from restaurants to monuments, along the way.

Apply the same mapping technologies to a store environment and you’ll greatly increase the efficiency of a customer’s visit. Moreover, these technologies offer brands a simple and effective advertising platform, and even the ability to place their merchandise in the highest trafficked areas of the store.

As we’ve mentioned, the customer now controls the brand engagement before the retailer does. The customer can maintain a very high bar for their expectations, and retailers must rise to meet it.

The consumer expects the goods at the cheapest price, delivered at the quickest pace, whether in the store or to their front door.

This is where last mile comes in - and why it’s so important for retailers to focus on winning that part of the shopping experience. The product must be abundantly available and accessible for the customer, effectively making brick and mortar stores into distributors. This method remains to be perfected because a brick and mortar store still comes with humans, increasing the likelihood of error (e.g. misplaced product, mispriced items, damaged goods).

The way to become more like a distribution center then lies in separating the roles of humans and machines.

Through technology like that from Bossa Nova, we can map every store, every product, every day - removing the margin of error and providing real-time updates regarding a product’s location.

First, we map the store’s floor plan and aisles. Next, we identify the fixture layout, followed by the label locations (e.g. where product labels are on the shelf) and product facings (what the product packaging looks like on the shelf). From there, the AI and computer vision technology recognizes three key data points: out-of-stocks (missing product facings), misplaced items (mismatched product facings and labels), and promotional stacks (xx xx).

Together, all of these elements create an actionable inventory ecosystem. As the robot follows the store map, it scans for missing or misplaced products, and provides a command to the store associates to replace or replenish the stock. Beyond providing constantly available product to consumers, this information is key for retail brands that need to better understand the sales velocity of their products, and for retailers that want to see the highest traffic areas of their shopping environment.