How mömax is revolutionizing product discovery with AI shopping assistants

How mömax Is Using AI Shopping Assistants to Revolutionize Product Discovery

Online shopping today often feels like wandering through a supermarket with too many aisles and no staff in sight. Endless product lists, complex filters, and resulting decision fatigue lead to chronically low conversion rates. A furniture retailer achieves 20–40% conversion in-store. Online, the average sits at just 2–3%.
This is where the combination of deep product knowledge and an AI-powered shopping assistant steps in—and delivers measurable impact.

The Core Problem: Choice Overload and an Outdated Search Paradigm

E-commerce search is, in most cases, just navigation. Even “smart” semantic search ultimately drops users into a product list with hundreds of options. Shoppers get overwhelmed, exit the journey, or postpone their decision entirely.

Categories like sofas, kitchens, and mattresses introduce even more complexity—materials, configurations, dimensions, and personal needs. Without structured guidance, revenue potential gets lost.

Search today is essentially a navigation tool. No matter how sophisticated the algorithm, the result is always a list—and the user is left alone again.

What an AI Shopping Assistant Must Deliver

• Alternative entry paths when shoppers feel lost—no more overwhelming filter jungles.

• Context sensitivity—understanding sessions, past behavior, and product data to give meaningful guidance.

• Collection of first- and zero-party data for personalized recommendations and CDP activation.

• Integration with inventory and ERP systems, including real-time store stock for fast delivery or Click & Collect.

• A second layer above the website, enabling intelligent guidance without replacing product detail pages.

mömax in Practice: 20 Years of Furniture Expertise Translated Into AI

mömax has transformed from a traditional furniture retailer into a digital-first omnichannel brand with “two entrances”—store and online—both serving the same customer journey.

Three advantages of physical retail must be replicated digitally:

1. The ability to try products

2. Immediate availability and fast delivery

3. Knowledgeable consultation and guided selling

Consultation is the real differentiator. mömax invested heavily in product data, prioritized high-touch categories, and launched AI-powered advisors for sofas, mattresses, kitchens, and lighting.

Measurable Results

• +40% Average Order Value (AOV)

• +30% Conversion Rate for sessions using the advisor

• 92% Engagement Rate among users who start the assistant

• 43% Click-through rate on recommended products

• −20% Exit Rate compared to sessions without the assistant

These numbers prove that intelligent advice isn’t a “nice-to-have”—it materially changes user behavior, boosts interaction, and drives revenue.

Concrete Solutions: Mattress Advisor, In-Store Kiosk, Kitchen Configurator

Key implementations include:

• Mattress Advisor: asks about size, firmness, sleeping style, allergies; pre-filters products; displays real-time local store stock.

• In-Store Kiosk: mirrors the online assistant; customers receive a QR code for Click & Collect or to share with an in-store sales associate.

• Kitchen Configurator: blends consultation with configuration and lead generation; customers design, add appliances, and book appointments.

The kitchen segment is the perfect example of category complexity. Guided configuration plus digital consultation creates clarity and increases the likelihood of purchase—as well as lead quality for store teams.

From Guided Selling to AI-Native Shopping Experiences

The next evolution moves beyond predefined question trees. AI agents will:

• Work contextually across all categories

• Combine session data with purchase history

• Offer cross-product comparisons and psychological choice framing

• Answer support questions (delivery times, store locations, stock)

• Enhance checkout flows with personalized cross-sells

A single AI agent can handle both product discovery and support—closing the gaps between touchpoints.

Impact on the Retail Tech Stack

Most retailers use 15–20 tools just to manage customer experience.
AI agents consolidate many of these functions, as they perform multiple roles simultaneously.

A typical CX toolchain:

• Acquisition: Ads & platforms

• Discovery & Consideration: Search, guided selling, product discovery

• Evaluation: PDPs, data feeds

• Purchase: Checkout, cross-sell

• Post-Purchase: Support, tracking

A strong AI agent connects these stages into a single experience with far fewer breaks.

Practical Recommendations for Retailers

• Prioritize high-advice categories: furniture, bedding, kitchens, lighting.

• Invest in clean, structured product data—it’s the foundation of every AI initiative.

• Integrate inventory for fast delivery promises and Click & Collect.

• Use conversational data to build powerful first-party datasets.

• Start small—with one category or an in-store kiosk—then scale.

Conclusion

Combining industry-level product expertise with AI-driven shopping assistants solves one of e-commerce’s biggest problems: decision paralysis in high-choice environments.
With contextual guidance, real-time stock integration, and intelligent configuration, retailers like mömax are seeing substantial revenue gains.

The future belongs to AI-native agents that unify discovery, sales, and support.
Retailers who prepare their product data today and digitize their advisory processes will secure a decisive competitive edge.

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