In an earlier post, I described some of the sessions at the recent EMEA Retail Executive Summit in London, where an energized and interactive group of retail executives sharing ideas and innovations to survive – and thrive – in today’s challenging environment. Today I’ll share recaps of the other discussions at the event.
A highlight for me was hearing views from Planet Retail Global Research Director Robert Gregory on “The Future of the European Retail Landscape.” Robert noted that, while the landscape is indeed evolving at an incredibly rapid pace, price remains absolutely critical to shoppers. – if anything even more critical as more shoppers gain more insight into prices across channels.
The value chain is fragmenting, technology is enabling huge advances in fulfillment and shopper experience, and mobile is massive, with 80% of Europeans using mobile devices to check online reviews, compare prices, etc.
But in all this change, price remains absolutely critical, whether shoppers are purchasing online or in-store. In an increasingly fragmented, complex landscape with always-on shoppers, AI to drive pricing and promotions can help retailers understand changing shoppers and offer customer-focused solutions.
In Europe, big box channels are seeing slow growth, particularly hypermarkets and superstores, as online grows. The fastest-growing physical outlets are convenience and discount stores. Online grocery is seeing the fastest growth of all even though it is still the smallest sector in absolute terms.
Store growth continues to slow and stores get smaller – the sales area of the average store is declining by about 7% in a 10-year period.
Robert says we’ll see a significant shift from static pricing to dynamic pricing, from one-size-fits-all to more focus on flexibility through diversification and localization.
Online access is increasing shoppers’ access to lowest pricing. Increasingly quarterly promotions across retailers are matched across the board by Amazon, creating a consistently low price across the market, in contrast with traditional high/low price variances. The result is downward price pressures in nearly every category.
Instead of a few products being competitively driven, nearly all will be. But leveraging new data streams and AI technology, retailers can employ dynamic pricing that is both responsive and targeted, Robert noted.
I always love hearing directly from retailers themselves about their individual price optimization journeys, so the panel moderated by Revionics Chief Marketing and Strategy Officer, Cheryl Sullivan, was informative and fascinating. The discussion featured Joachim Paulsen, Head of Pricing at Reitan Convenience, and Herman Tinga, Chief Commercial Officer at Lenta.
Reitan has moved from focusing on competition in its zone approach to focusing on customer behaviors, leveraging Revionics price optimization science to make that shift. Reitan stores are owned by franchisees, and franchisees were supportive of the initiative because it was intended to increase profitability. Nonetheless Joachim noted that some franchisees were surprised to see that price recommendations included some reductions as well as price increases. To help drive adoption, Joachim did a store tour to explain the machine learning science. Today the proof of value is in the business results – an increase in market share across all the banners.
At Lenta, which spans more than 80 cities across Russia, the teams are very regionalized for sourcing, category management and pricing, as well as lifecycles. Different formats also have different price strategies. Lenta conducts weekly competitive checks on more than 1000 items. They also do very granular customer segmentation and can make offers down to the personalized level. As Lenta continues to mature in its usage of Revionics’ science-based pricing recommendations, they may explore a more centralized approach to pricing.
Joachim described another tangible benefit of science-based pricing. On January 1 this year, the Norwegian government recently taxes on sugar – and buying behavior is very elastic on certain products with lots of sugar. Using Revionics they were able to increase cost on background products while staying the course with prices where the sugar-based items were very elastic. As of the end of the first quarter, Reitan had increased market share on Confectionary, which got the highest tax increases.
Herman discussed Lenta’s disciplined, data-driven culture. The company focused initially on data-driven customer insights and then turned to category management, which in turn was fed by the customer data. This led logically to price optimization.
When Reitan first implemented Revionics, they implemented a lot of business rules. Over time as they seek to unlock more value from machine learning, they have eliminated many business constraints in favor of more ML-based approaches. Herman explained that science in pricing is where you see the ultimate benefit of good sourcing, merchandising, etc. It enables Lenta to offer targeted pricing rather than taking a blunt one-size-fits-all approach.
Joachim sees agility in pricing key to responding to market factors like changes in weather, bank holidays, etc. Using Revionics, Reitan has implemented more localized pricing to be very targeted in deciding where to change prices. They use the science to follow customer behaviors and make more decisions driven by the customer’s preferences and behavior rather than vendor costs, and the confidence and accuracy of price recommendations continue to increase as the machine learning algorithms evolve.
Herman’s team focuses on the balance between providing fair prices to customers but also avoiding the waste of being mispriced or of promotions that are ineffective. Science can help drive good price perception while being cognizant of competitors’ high/low promotion patterns. The Revionics system lets Lenta offer more relevant prices while maintaining healthy margins.