December 14, 2021, under the roof of a cozy steak house at the very heart of Kyiv, Competera gathered key figures of Ukrainian retail. The guest list included top managers and retail professionals from Epicentr K, Eva, Intertop, MHP, as well as industry experts Alexey Chorniy from Suntown Ukraine, and Nikolay Brilenko, ex-Director of Development at Rozetka.business meeting in Kyiv
The discussion pivoted to the latest trends in retail tech space, the biggest players' moves towards technological optimization of offline stores, storage spaces, and items allocation. On top of this, the community also discussed the key obstacles holding retailers back from AI solutions adoption and the main requirements for a successful technology landing within an organization. Let's dive into the insights!

It's All About Trends

Store as the new entertainment and recreation place. Just as Apple stores have become a popular spot for teens and youth to hang out in, Ulta Beauty strives to create a thus-like experience for shoppers by creating a beauty space where women can learn, recreate and  interact with each other. Overwhelmingly, offline stores are growing out of the "shopping point" status to lure new customers in, engage with, and, most probably, sell more. 

eCommerce personalization. With the growing share of online orders, retailers face the importance of personalizing online offers for each shopper by suggesting personalized discounts and prices and coming up with custom items complementing the shopper's cart. That’s why the strategies that would bring retailers closer to shoppers' hearts are top of mind for the industry movers.
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Cashier-less fad rules the stores in Ukraine. Ukrainian retailers have eagerly jumped on the bandwagon of self-checkouts in-store. Nonetheless,there is no single opinion when it comes to evaluating the effectiveness of the self-checkouts. Thus, Alexandr Galkin insisted on "skipping the self-checkout stage and moving towards cart-free cash-less shopping." The statement brought up another hot subject - the adoption issue and, particularly, effective means of motivating shoppers to scan QR-codes which is necessary to make the idea of such cashless payments work.

Technology is Taking Over Retail Worldwide

Here are only some of the brightest cases of AI-based technology implementation in retail that were touched upon during the morning business session: 

Sephora, a French multinational retailer of personal care and beauty products, applies AI for its inclusive foundation matching service to make color matching easier and smarter for shoppers. 

Balsam Brands, a US-based retailer of artificial Christmas trees and seasonal decor, implements an AI-based pricing solution for managing seasonal sellout and growing gross margin.

Sainsbury's, following Amazon's practice, opens its first SmartShop Pick&Go store in London, offering customers the best of contactless, checkout-free shopping.

Vimos, a Russian DIY retailer, entrusted more than 80% of its assortment to an AI-based price optimization solution to maximize revenue without traffic losses and save profit during the low season.

Going way beyond the subject, the participants also discussed the main challenges and obstacles to successful technology implementation.
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Key Сhallenges for Retail Technology Adoption

According to the latest statistics, 80% of retail executives expect their companies to adopt AI-powered intelligent automation by 2027. In addition, 79% of retail leaders believe that AI will make their jobs simple and more efficient. So what is standing in the way of general adoption and whopping success stories? Here are the top 3 reasons outlined by our experts during the business breakfast:

#1 Data Quality

When it goes to an advanced solution implementation by a retail organization, both the retailer's and vendor's teams face a significant problem - the improperly stored data. 

"The scope often lacks some crucial data points like historical sales, price lists by date (what price drove/lagged sales), promo calendars, and stocks by date," comments Vladimir Kuhkanov, Product Manager at Competera. 

The problem's solution lies in creating a unified MBM/data lake in a retail organization, which is nurtured by data inputs made by teams from marketing to logistics and supplies.

"Once created, the data lake project is a never-ending story. Therefore, retailers should train and dedicate teams to maintain its viability and proper functioning," Vitalii Gots, Head of Analytics Systems Development at Epicentr K.

#2 Human Factor and Lack of Trust

Retail teams have been doing a lot of manual jobs since the very dawn of the industry: assortment planning, supply chain optimization, delivery routes mapping, pricing, replenishment, and allocation. The technological advancement in machine learning and artificial intelligence can ease their woes. Nonetheless, the end-users, i.e., pricing and category managers, store operation pros, inventory control specialists, are not that fast to let go of the dozens of years of their experience and entrusting their routine tasks to machines.

For example, the lack of trust often leads to a meager adoption rate of price recommendations by pricing managers, deviations from delivery routes mapped out by intelligent algorithms, etc. The challenge can be resolved by educating small groups and growing the early adopters of the technology within the organization. Later on, these people will educate their peers and lead the technological transformation.
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#3 Lack of Process Optimization

No doubt, retail teams who have been in the industry for over ten or even twenty years know their jobs best. But why wouldn't one invest time and knowledge into more meaningful tasks like strategic planning and execution instead of routine tasks? Advanced technologies make the whole company's life easier by streamlining regular processes, reducing labor, and saving time. And that means a comprehensive increase of efficiency.

"According to Juniper Research, retailers will spend $7.3 billion on AI technology in 2022. As we see, the future of retail is technology-powered. Regardless of whether retail executives plan the major tech revolution tomorrow or in 10 years, they should emphasize the role of proper data storing and support the organizational transformation together with processes’ optimization," -  Alexandr Galkin, CEO at Competera.

More Questions Discussed

  • What are the main business growth levers in retail?
  • Shopping season deals: how to make sure that Black Friday sellouts don't hurt the prime sales in December?
  • How to convince the team that data storing is essential and what data points should be kept wisely?
  • What data parameters are necessary for a neural network to process and work with a product category properly?

 

With this event, Competera has relaunched its tradition of business breakfasts for the retail community. Stay tuned for updates on future events!
 

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