Bringing the in-store expert online: How Bergzeit reinvented gear discovery with conversational commerce
For decades, Bergzeit has guided outdoor enthusiasts to the right gear for every journey — from summit pushes to weekend trail runs. With more than 500 trusted brands and a reputation for deep product knowledge, the European leader in mountain sports apparel and equipment set out to replicate its hallmark in-store expertise online. With Dynamic Yield’s solution Shopping Muse, Bergzeit went beyond traditional filters and drop downs to deliver AI-powered, conversational shopping experiences that inspire, guide, and serve customers still exploring their options.
higher conversion rate among shoppers who engaged with Shopping Muse
increase in average order value from assistant‑guided sessions
more revenue per user from customers who used the AI assistant
Introduction
The best way to help someone find the right product isn’t a filter or a dropdown — it’s a conversation. Bergzeit, one of Europe’s leading providers of mountain sports apparel and equipment, recognized that real innovation in e‑commerce would come from restoring something human: real, in‑the‑moment advice. As part of a partnership with Mastercard, the company set out to reinvent how shoppers discover gear online.
Offering products from over 500 trusted brands, Bergzeit has established a reputation for in‑depth product knowledge and a service‑driven mindset. For decades, it has helped outdoor enthusiasts find the right gear for every journey, whether a summit push or a weekend trail run.
“From the start, Mastercard’s Dynamic Yield team delivered. Shopping Muse didn’t feel generic — it felt like us. The AI was tuned to our tone, our customers, and how we sell.”
– Annette Zeidler Teamlead Webshop, Bergzeit
The Challenge
Bergzeit needed to replicate that same tailored service in its online store. They were already seeing strong results from their work with Mastercard Dynamic Yield, using personalized product recommendations to tailor content to each shopper’s preferences.
But the company wanted to go further. How do you help customers who aren’t looking for a specific product — but for direction? While personalization responded well to behavior‑based signals, it didn’t fully support shoppers who were still exploring — those unsure of what to search for or looking for inspiration and expert guidance along the
way. Traditional e‑commerce experiences, including dropdown menus, filters and static carousels, all had their limitations. They couldn’t match the nuance of an in‑store expert.
Bergzeit saw an opportunity to bridge that gap in a market where artificial intelligence (AI)‑powered shopping experiences were still rare, especially among European retailers.
The Execution
Enter the Dynamic Yield solution Shopping Muse: a conversational assistant powered by generative AI, designed to make online shopping feel more intuitive, guided and human.
Bergzeit became one of the first in the region to adopt the solution. With Shopping Muse, customers could describe what they needed in everyday language — from typing “gear for a rainy trail run” to uploading a photo — and receive curated suggestions based on activity, style and use case.
The rollout was quick and straightforward. The assistant worked out of the box with no changes to the product feed or new workflows. Bergzeit used seven pre‑built templates
— including notification widgets, dynamic content and custom code — to accelerate setup. From a single interface, the team customized the assistant’s tone, logic and visual style to reflect the brand.
Shopping Muse launched across key entry points, including the homepage, product listing pages and product detail pages. On product detail pages, it supported product bundling with “complete the set” suggestions — curated combinations of complementary gear and accessories. Notification widgets provided a consistent entry point on every page, making it easy for shoppers to engage at any stage of their journey.
Behind the scenes, Shopping Muse draws on deep learning affinity models to interpret preferences and contextual signals. To increase precision, Bergzeit fed in product‑level data, including material, fit and style tags. The result was an experience that felt personal across languages and native to Bergzeit’s tone. Performance dashboards provided the team with a clear view of what was resonating and what to optimize next.
The Results
Recent performance data made the impact unmistakable. Customers who engaged with Shopping Muse — by typing a query or clicking on a product — converted at a rate 3.4 times higher than the average. Revenue per user was 4.9 times higher, and shoppers viewed
5.5 times more pages per visit. The average order value also rose by approximately 30%.
These behaviors point to stronger intent and a more confident path to checkout — all driven by a shopping experience that felt conversational and expert‑guided. The value was clear not only in the numbers but also in how naturally the assistant integrated into both the tech stack and the shopper journey.
Bergzeit’s results affirmed its investment in conversational product discovery — and sparked new thinking about what’s next. The team is now exploring ways to blend traditional search with conversational AI, creating a hybrid experience that supports both clear intent and open‑ended exploration.
The Key Takeaway
Bergzeit continues to benefit from integrating Shopping Muse into its digital storefront, bringing the depth of in‑store expertise into a seamless online experience. For retailers looking to elevate product discovery, Mastercard’s Dynamic Yield solution combines conversational commerce with advanced AI to transform large catalogs into intuitive, high‑conversion journeys.
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