How we helped Just Carpets get more insights on Support
E-COMMERCE
AI AGENTS
FLOWS
OPEN AI
The Company
A leading European online retailer for carpets and flooring solutions, Just Carpets is known for its high-quality products, strong online presence, and dedicated customer service.
Company name
Just Carpets
Industry
E-COMMERCE
Company size
50+
Location
Kampen
What we did
~40%
Reduction in repetitive analytics work
95%
More insights into the actual problem -> solutions
100%
Accurate estimations of the correct tags
The Challenge
Just Carpets’ support team handled thousands of tickets each month in Trengo. While tickets had labels and tags, there was no certainty they reflected what customers were actually saying.
The company couldn’t confidently answer:
Are tickets correctly categorized?
Do the tags match real customer intent?
Which issues take the most time to resolve?
Without analyzing the actual conversation content, leadership only had a partial picture of the workload. There was also a strong suspicion that mislabelled tickets were hiding the most valuable automation opportunities.
The idea of building a new SaaS platform for AI was stalled — there was no validated dataset to guide the investment.
The Approach
Step 1 – Discovery & Data Consolidation
We began with a tooling discovery phase, working with support staff to map workflows. All ticket data — including customer and agent messages, internal notes, and existing tags — was exported into a single structured dataset.
Step 2 – Semantic Content Analysis
We deployed a custom LLM agent to review every ticket, reading the actual text to:
Verify if tags matched the ticket’s true content.
Suggest primary and secondary reclassifications where mislabels were found.
Detect product and service mentions for accurate filtering.
Score sentiment progression across the conversation.
Identify recurring triggers through root cause analysis.
Step 3 – Automation Opportunity Mapping
With accurate tagging restored, we quantified complexity, urgency, and resolution times for each ticket type — identifying the top candidates for automation based on ROI potential.
The Solutions
We delivered a clear, lasting solution to detect exactly what customers’ tickets are about — not just what they are tagged as. This live analysis tool processes every new ticket in real time, reading the actual conversation to generate a deeper, more actionable report than Trengo’s native analytics.
This includes:
Continuous validation and improvement of tag accuracy.
Agent performance tracking across response quality, sentiment handling, and resolution speed.
Conversation sentiment scoring to detect issues early.
Trend detection to surface new or rising support topics before they become major problems.
By combining automation with an always-on analysis engine, Just Carpets’ support team now has a permanent intelligence layer — ensuring they can make data-backed decisions, keep the automation roadmap current, and adapt quickly as customer needs evolve.
"Before, we thought we knew what customers were asking — now we know. The analysis changed our understanding of the workload and gave us a clear path to automate where it counts. Plus, the new reporting tool means we’ll never lose that clarity again.”
Gijsbert
Operations Director
The Results
By combining content-level analysis with automation, Just Carpets achieved:
Reliable tagging and classification, ensuring accurate reporting and AI training.
Reduction in repetitive manual tag work, freeing the team to focus on complex cases.
Ongoing operational intelligence via the new AI analysis tool, surpassing the insights available in Trengo’s built-in analytics.
The result: faster customer support, more confident data-driven decisions, and a scalable automation roadmap — all without building a costly new platform.