About

DKTrimmer is a Danish e-commerce company selling a wide range of tools, machines, and accessories. Due to the size and complexity of the assortment, customers frequently need guidance on product compatibility, specifically which accessories, parts, or add-ons fit which machines and models.

Providing accurate compatibility guidance is critical, as incorrect purchases lead to frustration, returns, and additional support workload.

The Challenge

Rather than implementing a simple chatbot with predefined answers, DKTrimmer, faced with around 50 daily product compatibility inquiries that were often repetitive and time-consuming, wanted to understand:

• What customers actually needed help with

• Which inquiries could be reliably automated or standardized

• Where human support should remain involved

The goal was not automation for its own sake, but measurable efficiency, delivering faster, more reliable and consistent compatibility answers, reducing customer service workload, and leveraging their existing compatibility sheet covering roughly 500 model numbers.

The Approach

Building on DKTrimmer’s existing data foundation, we developed a tailored AI solution designed to handle complex compatibility questions instantly. 

The AI was designed to: 

• Understand detailed product and model-specific compatibility questions

• Navigate DKTrimmer’s compatibility data accurately in real time

• Surface gaps in product or compatibility information based on customer conversations

In addition to answering customers, the solution continuously generated insights by flagging conversations where information was missing or unclear, turning support interactions into a source of ongoing data improvement.

Results

After implementation, DKTrimmer saw immediate operational impact:

• Approximately 80% reduction in customer inquiries related to product compatibility 

• Faster response times and higher customer satisfaction 

• Internal adoption, with employees using the chatbot as a daily reference tool 

Takeaway

The DKTrimmer case clearly demonstrates that effective AI automation has the potential to go beyond what human support can normally solve with the right data foundation.

By combining structured product data with continuous insight from real customer interactions, DKTrimmer transformed a major support bottleneck into a scalable and continuously improving system that reduces workload while improving both data quality and customer experience.