The offline retail industry is increasingly adopting IT technologies to optimize internal operations. By reducing the impact of human factor in routine processes, retail companies are significantly boosting their stores’ basic performance indicators and improving customer service, which can be clearly demonstrated by stores that are already digitalized. Invest Foresight explores the inevitable transformation of conventional retail sales thanks to high technology and Artificial Intelligence.
One of the most important aspects of the offline retail industry is its omni-channel approach, or integrating diverse customer communications channels to create a single system. The majority of retail chains have their own online versions, delivery services, etc. However, many customers do not seem to be ready to take full advantage of these tools.
And we know why: Russia is huge and distances are enormous. Building a fast and fault-free delivery is a serious challenge not only for major cities like Moscow, St Petersburg and Nizhny Novgorod but for smaller cities and towns as well.
Still, attempts have been made and some useful experience has been gained. All we need is a little patience until it becomes a common practice for stores and customers to use different channels extensively and simultaneously.
The same is true about marketing via mobile devices. A person’s everyday life seems inseparable from their smart phone at this point. I believe that smartphones will soon become an efficient tool to create a price offer for clients through recommendations.
What is hindering the progress? Offline retail needs a significant improvement of its IT infrastructure: video analytics and all services based on machine vision and technologies to analyze consumer behavior require enormous computational capacities.
There are still only a few cases that show that such technologies help cut costs and increase sales. All innovations are still at the pilot stage and being tested. For instance, machine analytics of consumer behavior in stores puts a heavy load on their network structure, and this problem will not be solved anytime soon.
The use of artificial intelligence based on big data — for example, machine vision to recognize events and analyze them for the segmentation of consumer traffic — is not far off, although it is unlikely to happen next year.
The curse of coupons
Traditional stores attract customers using special offers and discounted goods. Promotional campaigns are used by retail chains mostly to compete with each other. I believe they are not happy about the share of discounted products on their shelves. It is obviously wrong and something needs to be done about it.
Naturally, one can simply put away the discounted goods, but since it is impossible to predict the result, it would be a risky move.
There is another, more ‘elegant’ solution: introducing a personal price offer which is based on a number of specific customer parameters and evokes interest to goods outside the scope of the consumer basket. A customer’s profile may often be inaccurate as they may purchase goods of higher or a lower price segment within the same group for whatever reasons.
Personalized pricing allows for developing consumer taste while boosting a customer’s loyalty to the retail chain that helped him make the right choice. In case a customer likes the offer he will remain loyal to the chain and recommend it to his family and friends. There is also Net Promoter Score, an index to gauge the customer’s attitude to a company and loyalty to the brand.
I foresee that we will soon witness a boom in the personalized price offers in the market — which will affect, among others, the way retailers will handle discount sale items as well as the concept of discount in general, which may be abandoned at all, with price options available both as to consumer basket and the product itself.
IT technologies, which are being actively employed for human benefit in various spheres, will facilitate this process in the retail industry. Those include machine learning, which will primarily be used for working with big data to segment customer traffic and serve as a basis for developing models for teaching AI.
Today, retailers are actively embracing the functions provided by the electronic shelf label (ESL) system. We should understand that this system is not only useful for promptly updating information on the current product price but also serves as a tool to make an accurate analysis to see a specific price for a particular product offered to customer. The ESL system makes any purchase a mindful act, with a customer being aware of the price.
According to retailers, currently up to 15% of customers’ complaints received by hotlines relate to price changing from shelf to cash register. ESL eliminates this issue by excluding the human factor.
Traffic as a source of monetization
Generating traffic through managing consumer behavior and attention is another relevant area in the work of the offline retail industry, with AI technologies to provide assistance in the foreseeable future.
It is commonly known that any company that can generate additional traffic to its website will make a significantly greater amount of money than solely through selling products. Offline stores should also learn to monetize their traffic through methods other than sale of goods.
The use of AI based on big data analytics will help various chain store departments determine reference consumer groups and take efforts to plan and execute marketing events more efficiently to target specific costumer segments depending on their consumer preferences through actively utilizing media content to boost loyalty to the brand.
I recall a very successful experience by a retail chain, where digital screens were placed in fresh fish outlets to show fish cooking videos.
While using advanced IT developments, chain stores have to be aware of their ultimate goal — creating the most favorable and positive environment for customers though offering personalized service. We should remember that for many people across the globe — and Russia is no different — shopping is not just a trip to the store to buy food and other products, but a form of recreational activity.
By Mikhail Lantsov, CEO, Digital Retail Technologies