Customer service and support

Understand everything your customers tell you, not a sample

The real causes of customer frustration, drawn out of your own conversations, and the tools to help your team answer better and faster.

100%

of exchanges analysed, against under 2% by manual listening

23%

of the flow confirmed automatable on the transport audit

95%

search accuracy for the technical support assistant

The problem

A company handling thousands of calls, emails or tickets a year owns the best improvement material there is, and reads almost none of it. In a typical contact centre, quality is judged by listening to fewer than two calls in a hundred. The other ninety-eight are dead data.

The result is familiar. You steer by instinct. You decide the problem is agent training when it is really a case status the customer cannot look up for themselves. You launch a portal project without knowing how many calls it would remove.

Reading the whole flow changes the conversation. On an audit for a large public transport group, analysing forty-five thousand conversations overturned the original diagnosis and put a precise figure on the share of the flow that could be handled without an agent.

This concerns you if

  • Your first contact resolution rate has flattened and nobody can say why
  • Your teams solve the same problems again each week, problems already solved elsewhere
  • You judge quality on a handful of calls listened to each month
  • Customers phone you for information they could look up for themselves
  • Your experts are the only place your knowledge is stored
Check in five minutes

The builds

What gets built

Les délais indiqués sont ceux d'une mise en production réelle, pas d'une démonstration. On n'en lance qu'un à la fois.

  1. 01 4 to 8 weeks

    Full audit of the customer voice

    Every exchange over a chosen period is transcribed, sorted into a closed classification and scored. Out of it come the improvement areas ranked by severity and volume, the root causes, and the share of the flow that can genuinely be automated.

  2. 02 4 to 6 weeks

    A response assistant for your team

    An assistant that suggests an answer drawn from your resolved cases, your documentation and your procedures, with its sources cited and a confidence level. The agent decides, the assistant prepares.

  3. 03 4 to 8 weeks

    Quality measured across the whole flow

    Every exchange scored against your own quality criteria, dashboards by campaign and by segment, and individual feedback for each agent.

  4. 04 6 weeks and up

    Self-service aimed only at the right reasons for contact

    We automate the reasons that carry high volume and low human stakes, and we explicitly rule out sensitive situations. The list of exclusions is part of the deliverable.

Tools GeminiBigQuerySupabaseCloud RunQdrant

Data privacy

On this lever specifically

A call recording is personal data, and sometimes sensitive data. The processing chain anonymises before analysis, files are identified by technical reference, retention is set per client, and the most sensitive reasons for contact are kept out of any automated handling.

The full framework, level by level

Customer service and support

Common questions

Do we need a large volume for this to be worth it?

A full audit earns its keep from a few thousand exchanges over the period studied. Below that, reading a wide sample with the same tooling already gives you most of the answer for far less money, and that is what I would recommend.

Is this a way of monitoring our agents?

No, and a platform installed in that spirit fails. The scoring exists to find the friction in the customer journey and to give each agent useful feedback on where to improve. Employee representatives have to be informed, and what gets measured is agreed with them.

Our calls are full of trade vocabulary and not always in English. Is that a problem?

No. Transcription is reliable in the languages your team works in, and trade vocabulary is handled by building a glossary out of your own exchanges. That glossary is one of the more useful things the audit leaves behind.

The other levers

Further reading

Next step

Where would you start?

Ten days to map where your teams lose time, put a figure on each lever and name the first system to build. If AI is not the right answer, I will tell you so.

Start the diagnostic See the method

Diagnostic

Étape 1

10 days

€9,500 excl. VAT · fixed fee, one area of the business

  • A map of where the time actually goes in the area audited
  • Each lever costed in hours freed, ranked by effort and by gain
  • The data note: what leaves your systems, and where it is processed
  • A three-month plan, naming the first system to build