3 NEW INNOVATIVE SOLUTIONS TO OVERCOME RETAIL CHALLENGES
Offers, holidays, and much more: what truly drives consumers?
Over 6 in 10 Consumers Are Willing to Switch Supermarkets for Better Deals. Retailers have long emphasized the need to "put the consumer at the center."
This refers to the need to address customer needs through targeted offers. Easier said than done, but in a market where 62% of consumers are willing to switch supermarkets for better deals (Retail Insider, February 2025), it’s critical for Italian retailers to remain competitive. Given this tremendous volatility, it's essential to focus on the consumer, who is influenced by various factors that can drive purchasing behavior in unpredictable and seemingly untraceable ways. Take, for instance, Father’s Day sales, which fluctuate in ways that never replicate the previous year. Tuidi, through internal data analysis, found that in 2024, sales in Italy of products like flour and cake mixes declined by 7% compared to the previous year, when March 19 typically saw a sales increase of up to 35%. Why? The proximity of Father’s Day to Easter was a significant factor in this cannibalization of sales.
As Andrea Paparella, Sales Manager, explains, “This highlights the central importance for retailers of understanding the consumer and constantly ‘putting them at the center’ of their analyses to craft a consistent and attractive offer, without compromising the distributor's financial stability.”
The Approach of Personalized Predictive Models
The key to achieving this goal lies in adopting personalized predictive models developed through machine learning technology. The solution involves predicting consumer responses to the offers presented, in other words, accurately forecasting demand.
And this is where Delphi, the platform developed by Tuidi, comes into play. For years, Delphi has helped retailers strategically forecast demand by analyzing both internal variables (receipt analysis, promotions) and external factors (weather, events, holidays), adjusting predictions to each store's specific characteristics. This enables better inventory management and operational efficiency. Tuidi has demonstrated that through machine learning, it can increase sales by up to 2.2% thanks to the precise demand forecast that helps prevent stockouts. But an accurate demand forecast isn’t just about optimizing stock levels - it is the foundation upon which a more solid and profitable sales model is built.
The next step, based on demand data, is to ensure competitive pricing: attracting customers, raising the average transaction value without compromising economic sustainability. For instance, on Father’s Day, where consumption estimates cannot be standardized, a strategy might be to put a key product like eggs, essential for baking, on promotion. Internal analyses suggest that this could lead to a 116% increase in sales, with an 18% margin erosion.
A necessary evil for the distributor? Not necessarily, because customers drawn by the lower price will also purchase other ingredients needed for baking, amplifying the positive effect on overall sales. In particular, milk is one of these products, with related references showing a significant 34% increase due to the introduction of new variants like plant-based and lactose-free options. However, this change has led to a decline in sales of traditional references, such as cow’s milk.
Delphi’s Impact on Operational Strategies
The conclusion: creating a satisfying shopping experience for a customer is not only about ensuring product availability through supply management but also, and perhaps most importantly, about addressing pricing, assortment variety, and workforce management simultaneously. And this is where Delphi makes its mark again. By collecting and analyzing data, the software now enables action on these additional levels:
- Workforce Management, to define staffing needs by automatically allocating tasks throughout the day, ensuring operations are carried out correctly in the store while reducing the cost of excess staff by up to 10%. It also helps optimize workforce management by predicting peak traffic periods and efficiently distributing staff across departments.
- Smart Pricing, to optimize pricing strategies by leveraging over 20,000 hidden correlations between products, aiming to recover margins by up to 15%.
- Smart Category, to make the product assortment more dynamic based on predicted demand, enabling more frequent rotations of products and increasing references by up to 25%.
“These new features of Delphi,” says Andrea Paparella, “allow retailers to transition from a reactive to a proactive management style, differentiating themselves from the competition and consolidating their position in an increasingly competitive market”.
