Process management with AI-scored calls

Process and product owners are often asked to improve first call resolution and cut cost, but without visibility into why calls happen and why issues go unresolved, they are working blind. Individual tools help — but the real leverage comes from combining them.

Automatic summaries and automatic quality scoring each reduce cost and improve efficiency on their own. Used together, they turn everyday conversations into a practical basis for process management: raising the first call resolution rate, reducing repeat calls and cutting cost. This article explains how.

Understanding why customers call

An automatic summary does more than write up a conversation. Alongside the text, each call's reason is placed into a category designed specifically around the content of your conversations.

That categorisation lets product and process owners see past individual calls to the patterns beneath them. They can filter to the conversations relevant to their role — a particular product, a particular process — and analyse exactly the slice that matters, instead of trawling through everything.

Assessing whether the issue was resolved

Automatic quality scoring looks at the flow of the conversation, and specifically at resolution. Experience shows that getting their issue solved is the single most impactful part of a customer's experience, so information about resolution is invaluable.

Each conversation is scored on problem-solving:

• A full point when the issue is solved.
• Half a point when it is partly solved, with something still to be done.
• No points when it is not solved at all.

Users can then filter calls by whether the issue was resolved, partly resolved or unresolved — turning a soft judgement into something measurable across every call.

Understanding why issues go unresolved

When an issue is not solved within a call, there is a further assessment of why. The reasons are categorised, and they tend to fall into two groups:

• Within the agent's control — cases where more could have been done, and the issue might have been solved with better training or support.
• Outside the agent's control — a process or product problem that no amount of agent effort would have fixed.

That distinction is exactly what product and process management needs. It separates coaching opportunities from process defects, so effort goes to the right place.

Putting the two tools together

With summaries and quality scores applied to every conversation, you can filter out the unresolved calls and aggregate them by reason category and by reason for non-resolution.

A common finding is that many issues go unresolved simply because they were not fully addressed or the resolution was not confirmed with the customer. Partly resolved issues tend to generate repeat calls — which lowers first call resolution and pushes cost up.

From there, the practical workflow is:

1. See what you solve well, and what you do not — compare resolution across topics and reason categories.
2. Combine the views — cross-reference the top reasons for calls with the top reasons for non-resolution to find the costly overlaps.
3. Size each issue — measure the volume it creates, ideally by total call duration rather than just call count, so long calls are weighted correctly.
4. Compare to the cost of fixing it — set the cost an issue creates against the cost to resolve it, and you have a system for prioritisation.
5. Read the underlying calls — go back into the conversations themselves to pinpoint which process is affected and where the change should be made.

What is the impact?

Every process you improve after analysing real, current data is likely to save time and money down the line — and resolving issues faster raises customer satisfaction too.

As an illustration, an operation handling tens of thousands of calls a month can save a substantial amount simply by improving its first call resolution rate by a few percentage points. The exact figure depends on volume, call cost and where the unresolved issues sit — which is precisely what this analysis reveals.

Frequently asked questions

How do summaries and quality scores work together?

Summaries tell you why customers call, categorised by reason. Quality scores tell you whether the issue was resolved and why not. Combined, they show which call reasons most often go unresolved and drive repeat contact.

How does this raise first call resolution?

By exposing the reasons issues go unresolved — separating agent coaching needs from process and product defects — so you can fix the right cause and stop the repeat calls that a partial resolution creates.

How should we prioritise which issues to fix?

Size each issue by the volume and duration of calls it creates, then compare that cost to the cost of fixing it. Ranking issues this way makes prioritisation straightforward and defensible.

Does this replace manual quality review?

It replaces the reliance on a tiny random sample. Scoring runs across every call, and managers still read the underlying conversations to decide exactly what to change.

Where to go next

• See the bigger picture: Efficiency with AI
• Go deeper on quality: Automated call-centre quality assurance
• Explore the products: Quality assurance and automatic summaries
• See it applied: Use cases

Want to find the costly, unresolved issues hiding in your call volume? Book a demo and we will analyse them on your own conversations.