We had the chance to write a column on millefeuille.ai!
In this article, we dive into the fascinating world of tech and AI in retail, and reveal how these tools are transforming the customer experience.
We’re sharing the article here 👉
By working closely with retailers and brands to enhance the customer experience in categories requiring a high level of advice, we’ve discovered the many challenges, stakes, and opportunities related to integrating tech and AI in the retail sector.
I. The needs of retailers and brands in 2024
II. How does AI come into play?
III. How do our clients and their consumers welcome AI solutions?
The needs of retailers and brands in 2024
Personalisation and omnichannel customer experience:
Faced with an abundance of choices, millennials and Gen Z can be less loyal to brands. They prefer personalised shopping experiences that meet their expectations and won’t hesitate to look elsewhere if the experience doesn’t satisfy them.
A non-intuitive, impersonal user experience leads to high abandonment rates. Consumers seek seamless, tailored interactions where they are at the center of the shopping journey, whether online or in-store. To stay competitive, retailers must meet the omnichannel challenge and offer a coherent, unified customer experience.
Simplifying the customer journey:
In a fast-paced world, consumers are looking for smooth, intuitive experiences. Efficiency and speed have become top priorities, especially online. Optimising usability and reducing delays are essential to ensure a frictionless experience at every stage.

Sources : Forrester’s North American Consumer Technographics Brand Compass Survey, Q3 ‘15 ; McKinsey & Company Next in Personalization 2021 Report
Increasingly saturated markets, where capturing attention is crucial:
Consumers are becoming more demanding and seeking expert advice. Take wine, for example, where it all started for Matcha: customers often ask for recommendations related to very specific needs or desires (an aperitif with friends, a gift for a loved one, a bottle for a specific dish, etc.). Nowadays, selling wine is no longer enough; you need to tell a story, enrich the experience with accessible content, and offer a selection that is understandable to the consumer. The same goes for other alcoholic beverages, as well as coffee, where the offering is continuously expanding, especially with the rise of the whole-bean coffee segment, or cosmetics with increasingly varied formulas and effects.
A few key figures illustrating the need for guidance:

Sources: SOWINE/Dynata 2024 Barometer; IFOP study for Craft Beers & Co (Nicolas Group), 2022; IFOP study for Lemeilleurcafé.fr, October 2022
How does AI come into play?
AI to recommend the right product at the right time:
To offer personalised recommendations on our personal shopper, Matcha first needs to build a precise profile of the products, translate user needs into criteria, and then match this data using various technologies. Classification algorithms and automatic language analysis, strengthened by LLMs, help identify detailed product categories and extract unstructured data from labels and descriptions. Finally, Matcha uses optimisation models to analyse complex data, anticipate customer expectations, and predict trends.
AI to help customers express their needs:
Generative AI can interpret user requests made in natural, unstructured language, to predict and suggest terms or phrases that match their desires and needs. This technology helps users express themselves freely on our interface, making it easier for them to find the perfect product, leaving no questions unanswered.
An assistant for sales teams:
By using generative AI as a 'data steward' and a powerful tool to connect key details from product sheets together (e.g. linking a product to its category, profile, producer, etc.), we can ensure high-quality product data, which is essential in demanding sectors like travel retail, where premium products attract consumers who expect clear and detailed information about their purchases. As an intelligent assistant, Matcha Advisor is a valuable asset for teams, who can use it (directly on kiosks or tablets) as both a training and sales assistance tool.
How do our clients and their consumers welcome AI solutions?
Adoption challenges for clients:
Adopting a shopper-led strategy requires retailers to place the consumer at the heart of their commercial strategy and recognise the benefits offered by AI. Indeed, there may still be some distrust about AI's ability to provide reliable and relevant advice. Moreover, integrating AI may seem complex and expensive, and clients might fear it requires technical and educational support, but in reality, these are often turnkey solutions, as is the case with Matcha! Additionally, some clients might consider developing their own AI solutions, underestimating the costs and time involved, whereas it’s often wiser to adopt proven and optimised solutions.
Adoption challenges for consumers:
Shopping habits can pose challenges. For instance, users of our personal shopper might not immediately notice our solution because they tend to scroll quickly. It’s therefore crucial to work on the UX/UI to ensure the solution is visible from the start of the shopping experience. Consumers also need to easily understand how to use the solution, which requires an intuitive interface and clear instructions. Ultimately, we need to effectively adapt to consumers' shopping habits, both online and in-store, and build their trust in the reliability of our recommendations by maintaining high data quality. To reinforce trust, it’s also important to retain a human dimension by integrating experts’ knowledge, avoiding an overly impersonal and dehumanized relationship.
In conclusion...
AI can create value for consumers, retailers, and brands by simplifying and optimising the shopping journey with personalised assistance and instant recommendations. This enhances the customer experience and boosts sales throughout the year.
The uses of AI in retail are endless: stock management optimisation, personalised promotions, better store layouts, and much more. Every sector and every stage of the shopping journey can benefit from these technologies, making the experience more efficient and secure while driving sales and overall performance!
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