From keywords to key context: this is how brands adapt to the new era of conversational eCommerce

Rarely, when we enter a physical store, does the purchasing process begin with a keyword. We explain what we need, whether it is for ourselves or if it happens to be a gift, for which occasion, which features are important, or how much we wish to spend.

Depending on these requirements, the sales associate understands the need and offers us specific recommendations. The new conversational experiences in eCommerce seek to bring this dynamic into the digital environment.

Within this context arises the AI Assistant by Doofinder, designed so that the search experience in an online store more closely resembles a conversation with a sales associate in a physical store. Rather than simply interpreting keywords, the assistant interprets the user’s need and connects it with the merchant’s catalogue.

For the shopper, this translates into a more guided experience, with recommendations and support in various languages. For eCommerce, it means more data about purchase intent and improved decision-making regarding catalogue management, merchandising, and conversion.

Searching for products in an online store using natural language

Keywords such as “running shoes”, “black handbag”, or “waterproof jacket” have formed the basis of interaction between a consumer and the online store. Nonetheless, this model is beginning to fall short compared to the way we actually search for a product today, thanks to artificial intelligence.

It is now common to find searches such as: “I want women’s shoes for walking around the city that are comfortable and lightweight” or “looking for a waterproof backpack to travel with”. More than just a product, we are searching for a solution to a specific situation.

This change is especially visible in sectors such as fashion: 72% of consumers purchase fashion online, according to Doofinder’s 2025 Profile of the Online Consumer in Spain.

In a sector where product discovery is key, how we search within an online store directly influences the shopping experience.

Munich Sports business case: when conversation guides the purchase

A clear example of this evolution can be seen with Munich Sports, a Spanish brand known for footwear and sports fashion, recognized for its iconic “X,” and which already has this technology implemented in its shopping experience.

Within the online store of Munich Sports, users can interact with the AI-powered assistant developed by Doofinder, which analyzes the user’s context and intent.

Taking into consideration factors such as urban use of the product, the need for comfort and lightness, or the female category, it presents products that match the user’s search needs.

However, the conversation is not limited to product discovery. It also allows for commonly asked questions to be resolved before making a purchase, such as when an order will arrive or what the shipping terms are. The assistant can answer such queries directly by accessing shipping or delivery information from the eCommerce. This accelerates purchasing decisions and reduces the operational load on the customer service team.

From search tool to strategic resource for eCommerce

The competitive advantage no longer lies solely in bringing more visits, but in gaining a better understanding of the customers who are already inside the store and accompanying them during their decision-making process in order to improve conversion rates, increase average order value, and foster loyalty.

Each conversation reflects a genuine intent to purchase and reveals patterns that previously remained hidden within traditional searches, providing a new layer of information for eCommerce teams.

Images: Doofinder