Case study · QiQ Platform
Kärcher UK cut customer wait times by 67% and processing costs by £216k
Peak wait times fell from over 25 minutes to under 9, while the team handled 20% more customer interactions. QiQ's AI read every conversation, found what was driving the volume, and recommended the fixes.
The client
A premium consumer brand where service is part of the product
Kärcher is the global leader in cleaning equipment: pressure washers, floor care, and home and garden products, sold to consumers and professionals across the UK.
A customer who buys a premium machine expects premium support when they need a warranty claim, a spare part or a repair.
Quantanite is Kärcher's only customer experience partner in the UK, and runs all of its customer support across voice and email.
The challenge
Strong average scores were hiding a blind spot at peak
Through 2025 the operation met its quality targets. Voice QA averaged 95% and email QA 98%, across 57,893 queued contacts.
But sample-based QA reviews only a fraction of conversations, so it could not explain what happened when volume spiked. During the March and April peak the gap showed: one in five calls went unanswered, customers waited over 25 minutes to get through, and email backlogs pushed responses to the seven-day SLA limit.
Sampling could not show why customers came back again and again, or which points of friction were process problems rather than people problems.
peak-season calls abandoned before anyone answered
average wait to get through at the worst point, April 2025
email response time at peak, at the SLA limit
The solution
AI replaced sampling with full coverage, then recommended the fix
In January 2026, Quantanite deployed QiQ across every Kärcher UK voice and email interaction.
QiQ's AI goes beyond reporting. It links sentiment, outcomes and recurring themes to the operational data behind each conversation, finds the cause of the friction, and recommends the specific change that removes it.
On transfers, it found that most transferred calls were not a team member failing to answer a question. They hit a process barrier: a documentation requirement, a warranty validation step, or a repair workflow that could not be completed in the conversation. Kärcher redesigned those processes, and the transfer rate fell.
Reads 100% of voice and email interactions for sentiment, outcome and theme.
Traces each unresolved contact to its root cause: process, product or people.
Proposes a specific operational fix, not just a dashboard reading.
Measures whether the change moved the number, then runs the loop again.
The results
Six months, the same seasonal peak, a measurably different operation.
The voice transfer rate fell from 5.6% to 3.7% as more contacts were resolved first time. Handle time stayed flat: the gain came from better resolution, not shorter calls.
87% of unresolved interactions traced back to process dependencies such as documentation, warranty validation and repair workflows, not to individual performance. Improvement effort was redirected to match.
Call abandonment halved across the first half of the year. At peak, the average wait fell from 26 minutes to under 9.
Interactions rose from 37,188 to 44,616 in H1 2026, with email volume up 89%. Service quality went up under the extra load, not down.
| Measure | Before QiQ (2025) | After QiQ (H1 2026) | Change |
|---|---|---|---|
| Transfer rate (voice) | 5.6% | 3.7% | 33% lower |
| Call abandonment (Jan to Jun) | 13.4% | 6.7% | 50% lower |
| Peak abandonment (Mar to Apr) | 20.7% | 9.9% | 52% lower |
| Peak wait time | 26 min | Under 9 min | 67% faster |
| Email response time | Up to 7 days | 3 to 5 days | 2 to 4 days faster |
| QA score (voice) | 95% | 97% | 2 points higher |
| Gap to first-contact resolution target | 60% below | 33% below | 45% of the gap closed |
| Gap to NPS target | 60 points below | 32 points below | 47% of the gap closed |
“Traditional QA showed us a sample of our customer conversations. QiQ shows us all of them.”
David Napper Supply Chain Director, Kärcher UK
What comes next
From operational intelligence to commercial intelligence
Finding the 87% was more than an efficiency gain. It showed what AI surfaces when every conversation is read rather than sampled.
If QiQ can find where the friction sits, it can find where the next opportunity sits. The same conversations carry expansion signals, retention risk and revenue opportunity, and that is where QiQ is heading next: from fixing operations to commercial intelligence.
FAQ
Questions about QiQ and this deployment
What is QiQ?
QiQ is Quantanite's AI platform for customer operations. It reads 100% of voice and email interactions, links sentiment, outcomes and operational data to explain why customers get in touch, and recommends fixes for the causes underneath.
How did Kärcher UK reduce its transfer rate by 33%?
QiQ read every conversation and traced transfers to their causes. Most came from process requirements, such as documentation, warranty validation and repair workflows, not from the team's capability. Kärcher redesigned those processes, and the voice transfer rate fell from 5.6% to 3.7%.
What other results did Kärcher UK see?
Call abandonment fell from 13.4% to 6.7%, peak wait times improved by 67%, and email response times came down from up to seven days to three to five. Kärcher also closed 47% of the gap to its NPS target, while absorbing a 20% rise in total interactions over the same period.
How is QiQ different from traditional QA?
Traditional QA manually scores a small sample of interactions against a checklist. QiQ reads every interaction, attributes unresolved contacts to their root causes, recommends specific operational fixes, and then checks whether those fixes worked.
See what your own conversations are telling you
Send us a sample of past interactions. QiQ comes back with what is driving demand, avoidable cost and revenue leakage, calculated from your own data.