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Analytics and reporting

Contact Centre Analytics

The library holds 76+ ready-made reports, covering everything needed by the Clients to understand how their process is managed, are there any SLA breach, Are their Customer's happy and satisfied with continue and there are grievances going unnoticed. OptiML reporting is the most powerful reporting tool of its time and have successfully all Client needs from the readily available reports itself with almost nil additional work involved.

With OptiML, every transcript can be searched and analysed, revealing patterns and problems that no one ever recorded with a disposition code. And behind it all, every AI interaction is tracked—turn by turn—showing exactly what it cost.

  • 76 reports ready to run
  • Drag-and-drop dashboard
  • Semantic search over transcripts
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76 Report definitions in the library
6 Export formats, Parquet included
Drag-and-drop Dashboard builder for the rest
Every transcript Searchable by meaning

How it helps Customers for their Review meetings

In Contact Center operations, multiple stakeholders need different things at the same time. While Operations wants queue depth and handle time, the Client wants their six numbers and Finance wants to know what one conversation actually costs once you add up the model call, the transcription and the synthesis, in the currency the invoice goes out in rather than the one the vendor happens to price in. With OptiML all three read the same rows to get their response.

Every channel, in one set of numbers

A containment number that only covers web chat is not a containment number. It is a fraction. Every channel writes to the same conversation record, so a report on containment describes the operation rather than a vendor's slice of it. Nobody spends Monday reconciling two exports that disagree about how many contacts there were.

By the numbers

Few Facts - at a glance

  • 76 +

    report definitions across operations, executive, telephony, quality, campaigns and SLA

  • 6

    export formats — CSV, Excel, PDF, JSON, HTML and Parquet

  • Drag-and-drop

    dashboard builder — bind any widget to any metric, filter it, and share it

The process

How It Works

The four stages, end to end

Nothing here asks you to stand up a warehouse first. The record arrives complete. From there it is four steps, and the last one is where people stop asking you for the report at all.

  1. One record per conversation

    Voice, WhatsApp, web chat, email and SMS all land in the same conversation record: transcript, disposition, quality score, cost and latency on one row. Nothing stitches four systems together overnight. There is no second version of the truth to argue about.

  2. Open a report, or build the view

    The 76 definitions cover the weekly pack. For the quarterly board view, or the screen bolted to the wall above the floor, drag widgets onto a canvas and bind each one to whichever metric it should show. No ticket to the BI team.

  3. Narrow to the actual question

    Narrow the report to the queue and the fortnight the question is actually about. Then there is the question you cannot filter for, the one where you remember what was said but not which words were used. Search the transcripts themselves and keep the result set, not the count.

  4. Schedule it and hand it over

    Set it once. A report on a cadence arrives by email, which is how people stop asking you for it. Export the same rows as CSV, Excel, PDF, JSON, HTML or Parquet when the data team would rather work in their own tools.

Features

Every capability you need in one module

1. The report library

Most of what a contact centre reports on every week is already written. What is left is the board view and the wallboard, and those you build yourself.

76 report definitions spanning operations, executive summary, telephony, agent scorecards, campaign performance, quality, SLA and forecast accuracy. Call volume with peak-hour analysis, which is the report that turns the 9am spike from something the floor manager keeps mentioning into a number the roster can be built against. Average handle time. First-contact resolution as a report in its own right, rather than a column somebody derives in a spreadsheet. Containment, fallback and handover rates per agent. Conversion tracking with attribution models and funnel analysis.

  • Call volume with peak-hour analysis
  • Average handle time
  • First-contact resolution, as a report of its own
  • Containment, fallback and handover rates, per agent rather than per queue
  • Conversion tracking with attribution models and funnel analysis
Operations Executive summary Telephony Agent scorecards Campaign performance Quality SLA Forecast accuracy

How Workforce Management produces the forecast

2. Dashboards you build yourself

Drag widgets onto a canvas, bind them to any metric, filter by channel, team, agent, queue, campaign or date range, then share. Two shapes get built more than any other. An executive dashboard for the quarterly read, and an operational wallboard for the floor carrying queue depth, service level against target and agent state, all of it refreshing live.

  • Executive dashboard for the quarterly read
  • Operational wallboard for the floor, refreshing live, with queue depth and service level against target
  • Filtered to one team, one campaign, one week
  • Share with named people

Supervisor Console, the live floor behind the wallboard

Illustrative interface. Volumes, scores and costs are sample data from a demo tenant, not a performance claim.
Illustrative interface. Queue depths, service levels and agent states are sample data, not a performance claim.

3. Find the conversation

A regulator asks about a phrase. A product manager asks what customers actually said about the new tariff. Both questions are searches across every transcript, on every channel.

Full-text search across every transcript, plus semantic search for the times you remember the meaning and not the words. Filter by outcome, sentiment, score, disposition, agent, compliance flag or any tag. Export the result set. Or save the search as a report and run it again next month — the compliance sweep you ran in March is a saved search, not a fresh afternoon of work.

  • Full-text and semantic search over every transcript, on every channel
  • Filters for outcome, sentiment, score, disposition, agent, compliance flag or tag
  • Export the rows, not the count
  • Save a search as a report

Quality Management, where a result set gets scored

Illustrative interface. Quotes, counts and scores are sample data, not a performance claim.

4. Topics you didn't know to look for

Reports answer the questions you already knew to ask. Topic mining and cost tracing answer the two you didn't: what is starting to go wrong, and what it is costing you per turn.

Topic mining clusters conversations into themes without anyone defining a taxonomy first. Nobody has to name the problem before it can be counted, which is how a new one surfaces in week one rather than in the monthly review. Sentiment tracking flags an interaction that is deteriorating while it is still live. Predictive intent anticipates why the next contact is coming.

  • Clustering with no taxonomy defined up front
  • Sentiment tracking with dip detection, live rather than in a nightly batch
  • Predictive intent on the next contact
  • Themes you can filter by channel, queue, team or date

Omnichannel, where every channel writes the same record

5. Cost, traced

Finance asks what one conversation costs. Per-turn cost is traced across the model, the speech-to-text and the text-to-speech, rolled up per conversation, per agent and per organisation in the currency you report in. Budget compliance runs against the caps you set. Per-stage latency traces show when a turn breached its sub-second target and which stage was responsible, so the argument about whether it was the model or the network gets settled by a number instead of by whoever is louder.

  • Per-turn cost by provider, rolled up per conversation, agent and organisation
  • Multi-currency rollups
  • Budget compliance tracked against the caps that stop a run
  • Per-stage latency traces, from transcription through model to synthesis

AI Governance caps that stop a run

Illustrative interface. Costs, caps and latencies are sample data from a demo tenant, not a performance claim or a price list.

6. Scheduled and delivered

A report nobody opens is a report nobody reads. Schedule it, deliver it, and hand the raw rows to the data team in the format they asked for.

Schedule any report to run on a cadence and land in an inbox before the Monday meeting. Export in CSV, Excel, PDF, JSON, HTML or Parquet. Parquet is on that list because the data team asks for it in the first week, every time.

  • CSV
  • Excel
  • PDF, for the pack that gets printed and carried into a room
  • JSON
  • HTML
  • Parquet

Talk to us about pulling these numbers over the API

Use Cases

Where Contact Centre Analytics delivers value

Dashboard builder with scheduled delivery

The Monday pack that sends itself

A BPO running three client programmes (illustrative)

Scenario

Each client wants the same six numbers, filtered to their own queues. One executive dashboard gets built on the canvas, duplicated per programme with the queue filter changed, shared with the named account team and scheduled for 07:00 on Mondays.

Outcome

The reporting analyst stops rebuilding the same spreadsheet three times a week. Every client sees the figure that came out of the conversation record rather than one that was retyped at nine on a Sunday night.

Full-text and semantic conversation search

A regulator asks about one phrase

A mid-market lender (illustrative)

Scenario

The question is whether customers were told how the renewal price changes. Semantic search finds the conversations where that was the meaning even when the words differed, filtered to negative sentiment, quality scores under 3.5 and the last thirty days across voice, WhatsApp and email.

Outcome

Compliance hands back a list of conversations anyone can open and read. The result set exports in one click. The ones worth a second opinion go straight to quality review.

Topic mining and sentiment dip detection

The problem nobody had a name for yet

A regional telecom operator (illustrative)

Scenario

Four days after a tariff change, clustering groups a run of unrelated-looking calls into one theme about a charge appearing twice on the first bill. Nobody had written a disposition code for it. So it would not have shown up in the volume report at all, and the first anyone heard of it would have been the escalation.

Outcome

Operations sees the theme while it is still small, reads the transcripts sitting behind the cluster, and briefs the floor weeks before the monthly review would have surfaced it.

At a glance

Specification

The numbers and limits, without the sales copy

Specification for Contact Centre Analytics
Specification Detail
Reports 76 definitions across operations, executive, telephony, quality, campaigns, SLA
Channels covered Voice, WhatsApp, web chat, email and SMS on one conversation record
Dashboards Drag-and-drop builder, executive and wallboard variants, shareable and schedulable
Search Full-text and semantic across transcripts, multi-criteria filtering, saveable as a report
Filters Channel team agent queue campaign date range sentiment score disposition tag
Mining Topic clustering, sentiment tracking and dip detection, predictive intent
Cost Per-turn cost by provider, multi-currency rollups, budget compliance against caps
Latency Per-stage traces from transcription to synthesis, sub-second target-breach flagging
Exports CSV Excel PDF JSON HTML Parquet
Delivery Scheduled execution with email delivery, same figures over the API
FAQ

Questions,
answered

What teams ask us before they roll out Contact Centre Analytics — how it works, what it needs from your side, and what happens when it gets something wrong

Still not sure?

Talk to a specialist and get a straight answer.

Ask our team

Nothing on your side. Every conversation the OptiML platform handles is already written as one record, with the transcript, channel, disposition, quality score, cost and latency held together, so the library reports run from the first week you are live. There is no extract job to schedule and no warehouse to model first.

You build it. The OptiML dashboard builder binds any widget to any metric and filters by channel, team, agent, queue, campaign or date range, so a board view or a floor wallboard is assembled rather than requested. A conversation search can also be saved as a report and rerun on a schedule.

Clusters and sentiment dips in OptiML Analytics are prompts to go and look, not verdicts. Every theme opens onto the conversations behind it, so you read three transcripts and decide whether the cluster is real before anyone acts on it. Nothing is scored, coached or escalated on the strength of a cluster alone.

Yes. Any OptiML report exports as CSV, Excel, PDF, JSON, HTML or Parquet, and a search result set exports the same way, rows rather than totals. Scheduled runs deliver by email on a cadence, and the same figures are available over the API if your team would rather pull than receive.

OptiML Analytics reports on the conversation records held in the region you choose at deployment, and nothing is copied to a separate analytics estate somewhere else. Reports and dashboards inherit the access rules of the records underneath them. A team lead sees their own queues, and a shared dashboard carries the filters it was shared with.

Keep exploring

Additional supporting modules

Native modules that share the same record, knowledge and governance

Platform module

Quality Management

Every interaction scored on 15 dimensions, feeding the quality and scorecard reports.

Explore
Platform module

Workforce Management

Erlang-C forecasting and rosters, and the source of the forecast-accuracy reports.

Explore
Platform module

AI Governance & Guardrails

Per-call token, cost and latency tracing. These are the rows behind the cost reports.

Explore
Connected solutions

Where Contact Centre Analytics is used

The Solutions pages that lean on this module, and what it looks like once it is configured for a particular floor, job title or job to be done.

13 solutions built on this module

By industry

Sector floors that run on it

4

By role

Job titles that answer for it

5

By use case

Jobs it is put to work on

4
Browse every solution
Talk to a specialist

Bring last month's reporting pack

Send whatever you report on today. A volume report, an agent scorecard, a photograph of the wallboard behind the supervisor. We will rebuild the same view live on the call, so you can see what carries across, what the conversation record adds and what you would stop maintaining by hand.

  • 30 minutes
  • Your own reports, rebuilt live
  • No slide deck unless you want one

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