AI-Based Shopping Advice in Retail

Whitepaper: Shopping Assistants - From Searching to Understanding and Finding

The right product may be only a few clicks away, yet it often remains overlooked. Large product ranges, insufficient product information, and long lists of search results make online purchase decisions difficult. AI-based shopping assistants provide guidance: They understand projects and requirements, offer advice through dialogue, and guide customers toward a more targeted selection. Our whitepaper explores how digital shopping advice benefits customers and retailers, how it changes customer journeys, and what retailers need to make it work.

The Gap Between Search and Purchase in Online Stores

A survey of 1,044 people in Germany, commissioned by Lufthansa Industry Solutions (LHIND), shows that 76 percent use online stores to research products at least once a week, but only 54 percent shop there that often. The online store therefore frequently serves as a source of guidance and a decision-making channel before a shopping cart is even created.

Fifty-six percent of respondents said they spend too much time searching for products, while 53 percent view the large selection as a barrier to decision-making. One-third even abandon purchases because the decision becomes too complicated. This gives retailers an opportunity to reconnect search and advice.

From Search Field to Digital Shopping Advisor

A shopping assistant does more than just match keywords. Customers describe their goal in natural language – for example a project, an event, or special requirements – and receive suitable recommendations. The assistant can ask follow-up questions, explain product details clearly, create shopping lists, and simplify checkout.

Creating a reliable shopping experience requires more than a powerful language model. Complete, machine-readable product data, a robust system architecture, and clear rules for data protection, transparency, and security are essential.

Brief insight into our whitepaper "Shopping Assistants - From Searching to Understanding and Finding"

 

Free Download of the Whitepaper “Shopping Assistants: From Searching to Understanding and Finding”

Learn how AI-based shopping assistants transform online product search into personalized advice, how retailers benefit, and what foundations are required.

Find These and Other Insights our Whitepaper “Shopping Assistants: From Searching to Understanding and Finding”
  • How customers and retailers benefit from digital shopping advice
  • How digital and brick-and-mortar touchpoints come together to create a seamless customer journey
  • How to Build Your Shopping Assistant in 10 Steps
  • The Role of Data Quality, Architecture, Data Protection, and Security
  • How OTTO, Germany’s largest online retailer, uses a shopping assistant
Bar chart showing the frequency of negative experiences when shopping online. Respondents most frequently report spending too much time searching for products (56% very often or somewhat often) and difficulty making decisions due to the large selection of products (53% very often or often). Thirty-three percent abandon a purchase because the decision-making process is too complicated, 31% consider product information insufficient, and 24% switch to a brick-and-mortar store instead.
Time-consuming product searches, too many choices, and complex decisions: AI-based shopping assistants can help customers when traditional search is no longer enough.
  • Guidance Shapes Purchase Decisions
    More than half of respondents spend too much time searching for products, and one-third abandon purchases when the decision becomes too complicated. Digital shopping assistants can address this barrier directly in the shopping process.
  • Dialogue Replaces Rigid Search Results
    Shopping assistants understand projects, ask follow-up questions, and take context into account. This helps customers find products that better match their needs.
  • Data Quality Builds Reliability
    Accurate product data, a clean data pipeline, and transparent data protection and security processes provide the foundation for reliable recommendations.