E-commerce is constantly evolving. The same applies to customers' expectations of competent, personal advice in online retail. In recent years, classic guided selling software has proven that structured assistance with product selection increases conversion rates and reduces returns. However, rigid decision trees and visual filters are not always sufficient. What is needed is a new form of digital assistance – interactive, dialogue-oriented, and intuitive. The concept of AI conversational commerce and AI shopping assistants offers exactly that: customers chat with artificial intelligence via voice or text instead of navigating through predefined click paths. In this article, learn what lies behind the term guided selling software and how the new generation of intelligent assistants is leveraging and further developing its strengths.
Here's what you can expect to find in this blog article:
What is guided selling software?
How does guided selling software work?
What are the advantages of guided selling software?
2 cases for successful use of Guided Selling software
Targeted baggage selection: Miles & More's conversion rate increases thanks to guided selling
Spot-on gift ideas: Ex Libris uses Guided Selling for greater relevance
From guided selling software to AI shopping assistant: the next level of digital consulting
What is the new AI shopping assistant?
How does an AI shopping assistant work?
What are the advantages of the AI shopping assistant?
One system, three levels of maturity: How digital assistance is evolving
Conclusion: The future of purchasing advice is dialogue-based, personalized, and intelligent.
Guided selling software is a software program that allows you to assist your customers in selecting items and guide them to the right product in e-commerce. This makes it easier for them to choose the product they want. Overall, this leads to the right purchase decision, which is reflected in lower return costs for your company.
An online consulting tool helps your customers determine their needs when they are not familiar with the features of a product. The guided selling software asks specific questions and provides possible answers via visually prepared filters. The customer can easily answer these questions and thereby convey to the consultant which product meets their expectations.
The guided selling software then displays the products that best suit your customer first in the results list. The instant result function immediately changes the results list as soon as the customer answers another question. Since the products presented are tailored to their specifications, they feel more confident and more inclined to make a purchase.
Traditional guided selling is based on a fixed decision tree: customers answer a series of predetermined questions and are guided step by step to the right product selection.
Modern, AI-supported variants go one step further. They not only take into account the user's answers, but also their clicking and purchasing behavior, which is incorporated into a store-specific knowledge base and made available for consultation. On this basis, the results list is adapted to personal preferences in real time. For example, in terms of brands, models, or product types.
What makes it special is that the AI model learns with every interaction. This means that recommendations are continuously improved, making advice increasingly accurate and relevant.
It often happens that a customer has a need but cannot specify it precisely. For example, in the case of complex products that require explanation. In such cases, it can be difficult to select the right product, as different requirements apply depending on the intended use.
The more uncertain the customer is, the less likely they are to make the purchase. If they do buy despite their uncertainty, there is a good chance that the customer will not be satisfied with the product and will return it. This is where guided selling software can be effective, because it:
We reveal more about how you can effectively avoid returns in our blog article Avoiding returns: The role of personalization in e-commerce consulting.
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Lufthansa and Ex Libris have implemented different shopping assistants. Despite their differences, they have both achieved the same result: the shopping experience is now more enjoyable and easier, enabling customers to buy the right products.
For travelers, finding the right suitcase is essential. If it is larger than necessary, you will be carrying unnecessary volume. If it is too small, you will have problems fitting everything you need for your trip. To avoid these problems, Miles & More, a subsidiary of Lufthansa, has integrated a luggage advisor. With the wide variety of luggage that Miles & More sells, it is easy to lose track. But with the Baggage Advisor, no customer should have any difficulty finding the right suitcase to suit their needs and requirements.
Excerpt from Lufthansa's baggage advisor for selecting external features (source: screenshot of the baggage advisor on worldshop.eu)
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Miles & More made sure that customers weren't shown a page with zero results. Instead, they added a reasoning feature to the offers they showed. This feature shows which features the customer is looking for do and don't apply to each product. This way, customers can see at a glance which products meet their needs and wants.
“With the support of Epoq's Guided Selling Software, we were able to significantly increase conversion in the luggage sector. In conjunction with the Recommendation Engine, it has become an indispensable part of worldshop.eu for us.”
– Thomas Hilus | Digital Marketing Manager | Miles & More GmbH
Ex Libris relies on its gift finder as a prime example of self-explanatory products. This interactive tool uses keyword tags instead of explanation-intensive advice. Users simply select topics or areas of interest, such as favorite authors, music genres, or product types (books, movies, games). The system combines these tags to generate suitable recommendations and presents the results in real time.
Excerpt from Ex Libris' gift finder for selecting suitable gift ideas by tags (source: screenshot from exlibris.ch)
These examples show how much potential structured online counseling has. But with today's technology, even more is possible.
Guided selling is a success story in digital consulting. However, with increasing expectations for real-time, interactive, and contextual service, there is a need for a new level of service: today's customers expect more than structured but rigid advice. Instead of navigating through predetermined click paths, they want to engage in dialogue —have terms explained, chat, ask specific questions, and be able to respond immediately.
Traditional guided selling software reaches its limits here. The AI Shopping Assistant builds on its strengths and takes digital consulting into a new generation— more flexible, more personalized, and more dialogue-oriented.
An AI Shopping Assistant is a digital shopping advisor that helps customers choose products. It answers questions in natural language, gives personalized recommendations, and guides customers through the entire purchasing process —individually, easily, and around the clock. Unlike traditional guided selling solutions, the AI Shopping Assistant enables dialog-based, interactive advice that resembles a personal conversation in a store. This creates a particularly user-centered shopping experience in the online store.
Example: In a wine shop, a customer asks, "I'm looking for a red wine from Southern Europe between $20 and $30." The AI Shopping Assistant understands the request, filters suitable Mediterranean wines in the desired price category, and presents them in a personalized list of results. The solution thus goes far beyond classic visual filter functions and offers advice that is tailored to the individual wishes of the user.
The AI Shopping Assistant offers customers personalized and dialogue-based advice in the online shop (source: own illustration).
The technical basis of the AI Shopping Assistant is formed by modern AI technologies such as natural language processing (NLP), machine learning, and large language models (LLM). These enable the system to understand natural language, interpret complex queries, and customize recommendations in real time. Unlike conventional tools, the AI Shopping Assistant responds dialogically and accurately recognizes the intentions of users.
The functionality can be seamlessly integrated into existing processes and creates real added value for online shoppers. At the same time, the familiar product search remains unchanged – users can decide for themselves at any time whether they want to use the AI Shopping Assistant or choose the classic navigation path. Product search is particularly useful when customers already know exactly what they are looking for and what features the product should have. However , if there is uncertainty about which product is best suited and which items meet individual requirements, the AI Shopping Assistant can provide targeted support.
Important: Traditional guided selling solutions can also be AI-based and use adaptive algorithms, for example to analyze click and purchase behavior, in order to tailor the results list to the individual preferences of users. The key difference lies in the interaction. The AI Shopping Assistant enables a dialogical experience, comparable to a live chat or chatbot application or a GPT-based chatbot that responds to requests in a personalized manner.
The AI Shopping Assistant demonstrates how AI-based purchasing advice works, with benefits for both customers and retailers.
For your customers:
For you as a retailer:
Another advantage is flexibility: While guided selling is usually product category-specific and must be designed and technically implemented individually for each category, an AI shopping assistant can be integrated once and then used across categories. This significantly reduces the effort required for design and development and makes the solution particularly efficient to use.
Comprehensive market research also shows that these advantages pay off: According to current analyses, the market for AI shopping assistants will grow to $41.9 billion by 2034—with an annual growth rate of 26.1%.¹ Personalization software is thus already becoming the new standard in e-commerce.
The advent of AI-powered shopping assistants marks the beginning of a new chapter in e-commerce: the transition from traditional, rule-based guided selling tools with visual filters to genuine, interactive assistants.
While traditional systems rely on clicks and predefined options, AI-based solutions enable natural, flexible communication—similar to a real consultation.
The following table provides an overview of the three key stages in the development of digital purchasing advice.
From structured questionnaires to intelligent dialogue systems: digital consulting in e-commerce has evolved significantly in recent years. What once began with guided selling is now being taken to a new level by AI-supported shopping assistants.
The key lies in combining relevance, 1:1 personalization, and interaction. This enables you to not only guide customers to the right product in your online store, but also offer them a genuine consulting experience. And that is precisely what will make the difference in the digital commerce of the future. Because those who create a compelling consulting experience today will not only increase their conversion rate, but also customer satisfaction and loyalty. Online shops that anticipate customer expectations position themselves as trustworthy brands in the long term and at the same time create a competitive advantage for themselves.
Source: ¹ InsightAce Analytic
Guided selling software helps your customers select suitable products by asking structured questions and using visual filters. It works like a digital sales advisor and is particularly useful for product ranges that require explanation or are extensive.
This is especially true for complex, consultation-intensive items such as technical equipment, running shoes, or strollers. However, guided selling software can also provide support for self-explanatory, preference-based products such as books or fashion.
Guided selling follows a fixed click path (e.g., via selection fields or tags), while an AI shopping assistant interacts in natural language, understands queries, and responds dynamically to new inputs. The use of LLM technology and 1:1 personalization makes it significantly more flexible and personalized.
Yes, modern guided selling solutions are already based on AI algorithms. They analyze click behavior, for example, and adapt the product list based on what they learn. In contrast, the AI Shopping Assistant opens up a new form of interaction: dialogue-based instead of click-based.
Integration takes place in two simple steps: First, a knowledge base is created from the product catalog and behavioral data, then the provided div element is integrated into the shop system—after that, the AI Shopping Assistant is ready for use.
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