Kärcher UK cut customer wait times by 67% and processing costs by £216k
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.
A premium consumer brand where service is part of the product
Kärcher is the global leader in cleaning equipment, selling pressure washers, floor care and home and garden products into the UK consumer and professional market. Customers who buy a premium machine expect premium support when a warranty claim, spare part or repair is involved.
Quantanite is Kärcher's sole customer experience partner in the UK, handling all inbound customer service across voice and email.
Strong average scores were hiding a blind spot at peak
Through 2025 the operation performed well against 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 became visible. One in five calls went unanswered, customers waited over 25 minutes to reach an agent, and email backlogs pushed responses to the seven day SLA limit.
AI replaced sampling with full coverage, then recommended the fix
In January 2026 Quantanite deployed QiQ across all Kärcher UK voice and email interactions. QiQ's AI does not stop at reporting what happened. It connects sentiment, outcomes and recurring themes to the operational data behind every conversation, identifies what is causing the friction, and recommends the specific operational change that removes it.
Applied to transfers, that loop was direct. The AI found that most transferred calls were not agents failing to answer a question. They were agents hitting a process wall: 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.
Six months, the same seasonal peak, a measurably different operation
Fewer transfers
Voice transfer rate fell from 5.6% to 3.7% as more contacts were resolved on the first attempt. Handle time held steady, so the gain came from better resolution rather than shorter calls.
Root cause identified
of unresolved interactions traced to process dependencies such as documentation, warranty validation and repair workflows, rather than agent performance. Improvement effort was redirected accordingly.
A calmer peak season
Call abandonment halved across the first half of the year. At peak, average wait time fell from 26 minutes to under 9 minutes.
A larger workload, absorbed
customer interactions handled in H1 2026, up from 37,188, as email volume grew 89%. Service quality improved rather than declined under the extra load.
| Metric | 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% closed |
| Gap to NPS target | 60 points below | 32 points below | 47% closed |
"Traditional QA showed us a sample of our customer conversations. QiQ shows us all of them. It proved that most repeat contacts were process problems, not people problems."
From operational intelligence to commercial intelligence
Finding the 87% was not only an efficiency win. It was proof of what AI analysis of every conversation surfaces when every conversation is read rather than sampled.
The same evidence base points outward, at the expansion signals, retention risk and revenue opportunity sitting inside those same conversations. That shift, from fixing operations to unlocking commercial intelligence, is the direction QiQ is being built toward next.
Questions about QiQ and this deployment
What is QiQ?
QiQ is Quantanite's AI platform for customer operations. Its AI analyses 100% of customer interactions across voice and email, connecting sentiment, outcomes and operational data to explain why customers contact support, then recommends the specific fixes that resolve the underlying cause.
How did Kärcher UK reduce its transfer rate by 33%?
QiQ's AI analysed every Kärcher UK conversation and traced transfers to their root cause. It found most were driven by process dependencies such as documentation requirements, warranty validation and repair workflows rather than agent capability. Kärcher redesigned those processes, and voice transfer rate fell from 5.6% to 3.7%.
What other results did Kärcher UK see after deploying QiQ?
Call abandonment halved from 13.4% to 6.7%, peak season wait times improved by 67%, email response times moved from up to seven days down to three to five days, and 47% of the gap to the NPS target was closed. Kärcher absorbed a 20% increase in total contact volume over the same period.
How is QiQ different from traditional contact centre QA?
Traditional quality assurance manually reviews a small sample of interactions and scores them against a checklist. QiQ's AI analyses every interaction, attributes unresolved contacts to their root cause, recommends specific operational fixes, and then validates whether those fixes worked.
See what your own conversations are telling you
Send us a sample of past interactions. In two weeks, QiQ shows what is driving demand, avoidable cost and revenue leakage, computed from your data.