This article was first published on Business Reporter.
Retailers are looking towards artificial intelligence (AI) such as image recognition technologies to help enhance sales staff productivity as well as make them be more competitive against their peers.
Alexander Laugomer, project manager digital merchandising at consumer and industrial goods firm Henkel, says: “The major benefit of the AI technology is that it not only provides us with information on our own and our competitors’ products, but it also gives us an actionable report straight to our mobile devices.
“This allows our sales reps to improve our brands’ situation in-store there and then, without the time-consuming task of manually compiling data.”
Henkel outsources this function to retail image-recognition firm Trax. The technology works by being able to recognise more than eight million images on a shelf. After recognising the products, the artificial intelligence system gives the sales staff real-time recommendations on what needs to be done to give them a competitive advantage in the marketplace.
The technology is designed to help improve productivity and reduce the time an employee needs to spend checking inventory on store shelves, as well as gathering analysis about things such as shelf location and different types of promotions.
Laugomer says: “The software provides an electronic list that is entirely objective and significantly more accurate than previous manual processes, which are obviously prone to human error.”
Research has shown that retailers were investing in smarter analytics and technologies to gain a competitive advantage and improve the experience of the customer.
A survey by KPMG International and The Consumer Goods Forum showed the usage of techniques such as predictive analytics, customer path-to-purchase analytics, and artificial intelligence were expected to double over the next two years, to 59 per cent, 54 per cent and 43 per cent, respectively.
The research also found 29 per cent of firms surveyed currently use data analytics, with this proportion expected to double to 58 per cent in the next two years.
Willy Kruh (inset, below), global chair of consumer markets at KPMG International, says: “Companies need to gather and analyse as much circumstantial, situational and demonstrated behaviour data as possible so they can start to understand the motivation for why, when and how a consumer makes a purchase decision at any given time.”
Companies in the drinks industry have been using Trax AI to help make them more productive. In 2014 Coca-Cola gained 1.3 per cent in market share within five months and was listed in Australia’s BRW Magazine’s 50 Most Innovative Companies after using the technology. The soft drinks giant was able to get real-time images of its products in store, giving sales staff insights into any performance gaps, so that they could apply corrective actions in the store as soon as problems were found.
Elsewhere, beer manufacturers have been using it to better manage their stocks, gain greater visibility into trends across markets and improve their ability to predict and respond to competitor behaviours. It has also helped beer brands make sure their products have been placed on the shelf during peak periods.
According to Joel Bar-El, CEO of Trax, fast-moving consumer goods (FMCG) companies spend about $70billion on shelf merchandising standards, buying shelf space and marketing materials, promotions and exhibitions.
Companies positioning their products in-store can get the maximum number of people seeing their products, thus potentially improving sales. And through using AI image-recognition technology, they can use real-time analysis of how their products are doing on shelves, giving them the best sales potential.
Dror Feldheim, co-founder and chief commercial officer at Trax, says: “Retailers turn our data and insights into broader market intelligence and highly accurate trend predictions that shine a light on new ways to improve their customer experiences in-store.”
The technology is also being used by companies in conjunction with their loyalty programmes, so consumers can look at the shelf digitally and make smarter choices. They can use it to filter specific products on shelves, such as gluten-free or low-fat, for example.
