The Do’s and Don’ts of Implementing Analytics

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Published On: 14th Sep 2026 08:00

Analytics can unlock valuable insights into customer behaviour, agent performance, and operational trends, but simply turning it on rarely leads to real improvement.

So, what are the do’s and don’ts of implementing analytics in the contact centre? We asked our panel of technology experts for their top tips and advice.

Don’t Assume the Project Is Complete Once the Solution Is Built

Don’t isolate your operational colleagues. Bring them along on the journey. They must understand the objectives and buy into the project to ensure successful adoption.

And don’t assume the project is complete once the solution is built. Extracting genuine value from analytics demands continuous investment, regular refinement, and ongoing resource allocation.

Don’t default to the cheapest available option either. Selecting technology based solely on initial price often means sacrificing essential capabilities, which can cost the business significant long-term value.

Contributed by: Luke Cuthbertson, Head of CX Consulting Practice, Route 101

Do Retire Outdated Metrics and Rethink How Performance Is Measured

Many teams continue to measure success through legacy metrics, applying old operational thinking to new tools, and treating analytics as an add-on rather than a core capability. 

The reality is that analytics, especially when supported by AI, exposes behaviours, inefficiencies, and opportunities that traditional approaches simply cannot see. But unlocking that value requires a fundamental shift.

Teams must be willing to retire outdated metrics and KPIs, rethink how performance is measured now analytics tools are available, and, importantly, embed the data into everyday decision-making. 

Successful organizations won’t just implement analytics, they’ll evolve their operating model around it to become a living system.

Contributed by: Lewis Gallagher, Senior Solutions Consultant, Netcall

Do Fix the Audio Before You Buy the Insight

Analytics inherits every defect in your recordings. Where your agent and customer share one audio channel, the system must separate them in software – and that separation degrades on crosstalk, background noise, and similar-sounding voices.

Every measure built on top inherits the error: talk-time ratio, interruptions, silence, who sounded frustrated.

Transcription is the second foundation, and it is not accent-neutral. Error rates run substantially higher for regional and non-native speakers – 12–25% in real-world conditions against roughly 4% for a human transcriber.

If a fifth of the words are wrong for your Glaswegian, Geordie, or Multicultural London English callers, your analytics under-counts their problems, and nothing on the dashboard will tell you it is happening.

Record in stereo. Ask suppliers for accuracy benchmarks on UK-accented telephony audio, not clean studio speech.

Don’t Trust the Sentiment Score More Than the Science Does

Sentiment is the most demonstrated and least interrogated feature on the market, and the science under it is shakier than the dashboards imply.

Decades of research on emotional expression point the same way: how someone sounds is not a reliable guide to how they feel.

A raised voice is not dependably anger, and clipped politeness is not dependably calm. That unreliability is exactly why European AI regulation now restricts emotion recognition outright rather than simply cautioning about it.

Use sentiment as a triage signal, a way to surface interactions worth a human look. Don’t use it as a score, don’t put it near an appraisal, and treat any supplier quoting sentiment accuracy to two decimal places as telling you more about their marketing than their model.

Contributed by: Chris Mounce, Product Training & Enablement Specialist, evaluagent

Don’t Try to Track 15 KPIs at Once

The challenge was never a shortage of data, but turning that raw material into information that actually drives decisions.

Too often, AI’s return on investment has been hard to prove simply because the “before” state was never properly measured, so there’s no meaningful delta – or change – to point to.

• Do: Start with a customer data platform, bringing everything together as your foundation, and set clear objectives first: it’s the what and why, not the how.
• Don’t: Try to track 15 KPIs at once. If you have 15 KPIs then nothing is key.

Contributed by: Martin Taylor, Co-Founder and Deputy CEO, Content Guru

Watch the video below to hear Richard Manthorpe, Product Director at Content Guru, outline a few tips that can make analytics work:

Don’t Rely on Static Dashboards and Sampled Data

Avoid looking at only 5–10% of interactions when you’re making decisions, which leaves hidden friction points and revenue leaks invisible. Traditional dashboards tell you what happened, but require manual digging to explain why.

Move away from static charts and embrace real-time conversational intelligence that automatically summarizes complex issues and prescribes actionable solutions.

Contributed by: Matthew Clare, VP, Product Marketing, UJET

Do Start With a Clear Question

Contact centres can collect huge amounts of data, but more dashboards do not necessarily lead to better decisions.

Starting with a clear question can help the project stay on track and ensure an outcome that actually solves a problem, instead of adding more noise to a system already overflowing with data points.

Do Build Trust in the Data Before Trusting the Insight

Analytics is only as reliable as the data behind it. If different systems report different figures for the same KPI, teams quickly lose confidence in the results and go back to spreadsheets or manual checks.

Before introducing advanced analytics, organizations should establish clear definitions, ownership, and data quality standards. It is important to make sure different systems are working from consistent definitions and data.

It is also important to understand where the data comes from and how frequently it is updated. This becomes even more important as AI and predictive analytics become part of the contact centre, because poor-quality or incomplete data can amplify errors at scale.

So before asking analytics to tell you what is going to happen next, make sure you trust what it says happened yesterday.

Contributed by: Zaineb Ahmed, Marketing Manager, Peopleware

Do Always Route the Insight to the Department That Can Fix It

Test every insight against one sentence: [named owner] in [department] will fix [specific thing] by [date]. If the only name that fits is yours, the finding hasn’t been routed – it’s been dumped!

• Do: Run a monthly contact-driver forum where the top five reasons that customers contacted you are put in front of billing, product, web, and claims, each with a named owner and a due date. The contact centre is the last honest listening post in most businesses. Analytics is how you make it audible to people who never take a call.
• Don’t: Leave the findings inside the contact centre, where the only available lever is efficiency. If the insight is “the renewal letter is confusing” and the only person in the room is the operations manager, you’ll get a new agent script instead of a fixed letter, and the calls will keep coming.

Do Build Contact-Reason Categories From What Customers Actually Say – Not Generalities

Take 100 interactions, read them, and compare them with the disposition the agent selected. That gap is the accuracy ceiling of everything you build on top. And if more than 10–15% of contacts land in “Other”, the model is wrong, not the data.

• Do: Build contact-reason categories from what customers actually say, not generalities. For example, “Billing” is a department, not a reason. “I don’t understand why my premium went up” is a contact reason, and it tells you what to fix.
• Don’t: Just seed your categories from agent-selected wrap-up codes or validate against them. Agents choose under AHT pressure and default to whatever sits at the top of the list. Inherit that and you get complete coverage of the wrong categories: confidently wrong, at scale, with a dashboard behind it.

Contributed by: Taoufik Massoussi, Product Manager, Enghouse Interactive

Do Combine Real-Time and Historical Analytics

Organizations that rely solely on historical reporting are always reacting to the past. Those that layer in real-time visibility can manage the present, and that’s where the biggest operational gains are made.

You need to shift your analytics model from lagging metrics to leading metrics. For example, a small increase in dissatisfied customers on specific topics highlighted by real-time speech analytics can help you prevent a bigger problem in the short-term future, thus preventing further dissatisfaction.

Contributed by: Jonathan Kershaw, Head of AI and Contact Centre Experiences, Vonage

Don’t Confuse Measurement With Improvement

A dashboard can tell you that QA scores are falling, which agents are struggling, why customers are contacting you, or where sentiment is declining. But the most important question is: what happens next?

If customers repeatedly contact you about the same issue, does that insight trigger a process change? If several agents struggle with the same part of a conversation, does it become a coaching priority? If sentiment falls around a particular policy or process, is someone responsible for investigating why?

Analytics should create a clear path from insight to action. Without that next step, organizations risk building increasingly sophisticated reporting systems without actually improving anything.

Define who owns the response when analytics identifies an issue and how progress will be measured afterward. The real value of analytics comes from what the organization does differently because of what it has learned.

Contributed by: Jonathan Kenu Escobedo, Customer Success Manager, MiaRec

What Lessons Have You Learnt the Hard Way When Implementing Analytics?

Click here to join our Readers Panel to share your experiences and feature in future Call Centre Helper articles.

For more great insights and advice from our panel of experts, read these articles next:

• Are You Doing Enough to Protect Your Contact Centre Data?
• 10 Smarter Ways to Use AI Augmentation
• How to Manage QA Across Different Channels

Author
Megan Jones

Megan Jones, Editor, Call Centre Helper

Megan interviews inspiring people across the contact centre industry to capture these amazing voices and turn them into best practice articles – covering all elements of what it takes to deliver truly outstanding employee and customer experiences.

Connect with Megan on LinkedIn

Read more by Megan Jones

Reviewed by: Jo Robinson

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