Call Centre Quality Monitoring: Why Sampling Isn't Enough
Quality assurance is one of the most compliance-critical functions in any contact centre, and one of the most under-resourced. For most operations, the gap between what QA teams can review and what regulators now expect to see evidenced has never been wider.
Most contact centres review a small fraction of their calls. A QA analyst picks a handful, scores them, flags what went wrong, and then moves on. It feels like it ticks the box for quality assurance. But for Ofcom-regulated telecoms operations and FCA-regulated financial services firms, it’s not enough, and the consequences of getting it wrong have never been higher.
This article explains why call sampling creates compliance exposure, what always-on monitoring looks like in practice, and what to look for when evaluating your current approach.
What is call quality monitoring?
Call quality monitoring is the process of reviewing agent-customer interactions to assess whether they meet your quality, compliance, and performance standards.
It typically covers:
What was said and how the agent handled the conversation
Whether compliance scripts and protocols were followed
How vulnerable customers were identified and managed
Whether the outcome was appropriate for the customer
How performance compares against your scoring framework
When call quality monitoring is done consistently, it gives you a documented evidence-base across every call type, agent, and campaign. But when it’s done poorly or too infrequently, it leaves gaps that regulators are increasingly likely to find before you do.
How do most contact centres currently monitor calls?
Sampling is the typical approach many call centres take to monitoring calls. A QA reviewer listens to a set number of calls per agent per month, scores them against a framework, and feeds the results back into coaching. It is time-consuming work, so let’s break down the numbers.
Example:
A single reviewer handles 50 calls a month at 30 minutes per call.
This amounts to 25 hours of review time.
And it is still only a fraction of the total call volume reviewed.
The problem here is not the effort; it's the coverage. On average, contact centres manually evaluate 5% of calls per week, meaning many QA operations are leaving the majority of interactions unreviewed. This means:
You don’t know whether your agents are consistently identifying vulnerable customers.
You don’t know whether compliance scripts are being followed on the calls you did not pick.
You are not building an evidence bse, only a small sample.
Manual call sampling statistics
FCA Consumer Duty: you need evidence across every interaction, not a snapshot
For debt collection, insurance, and other FCA-regulated contact centres, the stakes are different but the problem is the same. Consumer Duty requires firms to demonstrate they are delivering good outcomes for retail customers, not just on the calls they reviewed, but consistently and measurably across their entire operation.
The FCA has shifted decisively from implementation to enforcement. Regulators are no longer asking whether you have a quality monitoring process. They are asking whether you can prove, with documented evidence, that your agents are handling vulnerable customers correctly, following compliant scripts, and not causing foreseeable consumer harm. And that’s for every call, not just the ones you checked.
A sampling approach does not produce that evidence. It produces a snapshot.
For more on what the FCA now expects from contact centres in financial services and debt collection, see our Consumer Duty guide.
The problem with call sampling: A Summary
Sampling typically covers around 5% of calls per week, leaving the 95% of interactions unreviewed and unverifiable
Compliance drift happens slowly. By the time sampling catches a behaviour, it is already established and harder to coach out
Poor agent behaviour on outbound calls can go undetected long enough to trigger carrier blocking or an FCA flag
Vulnerable customers may not be identified correctly on calls you never reviewed
Good performance goes unrecognised as you cannot replicate what you cannot see
A sample tells you what happened on the calls you chose to review. It does not tell you what is happening in your operation
From sampling to monitoring: what's actually required
Moving from sampling to consistent call monitoring is not simply a matter of reviewing more calls. It requires the right infrastructure in place, and historically, that infrastructure was either too expensive, too time-consuming, or both.
At a minimum, always-on monitoring requires:
Call recording across all interactions, not just selected campaigns or call types
Transcription that converts voice to text accurately enough to be reviewed and searched at scale
A platform that connects recording, transcription, scoring, and reporting in one place rather than across multiple disconnected tools
Without all three, monitoring at scale either falls back on human reviewers (which is where the 25-hours-per-50-calls problem comes back in) or produces data too inconsistent to be useful as a compliance evidence base.
MaxContact's Conversation Analytics brings all of this together in a single platform. Call recording, real-time transcription, and reporting sit alongside each other. This gives your QA team a single place to monitor, review, and evidence what is happening across every interaction, without stitching together multiple tools or managing separate systems.
The reason most contact centres have defaulted to sampling is not because they did not want better coverage. It is because the operational cost of achieving it manually was prohibitive. A team large enough to review every call would cost more than most mid-market operations can justify. But that has changed.
How Conversation Analytics makes always-on monitoring feasible
Conversation Analytics is the platform that makes consistent, always-on call monitoring operationally viable for mid-market contact centres.
Rather than relying on a QA team to manually select, listen to, and score calls, Conversation Analytics connects call recording, transcription, scoring, and reporting in a single platform – automating quality assurance. Every interaction is captured, transcribed, and made reviewable, giving your QA team complete visibility across all call types, all agents, and all campaigns without the resourcing overhead of manual review at scale.
The cost comparison is significant. Replicating meaningful call coverage with human reviewers alone would cost an estimated £14,000 per month in analyst time for a mid-sized contact centre. Conversation Analytics delivers that coverage at a fraction of the cost, freeing your QA team to focus on coaching, calibration, and the complex calls that genuinely need a human eye.
How AI call monitoring surfaces insights faster
AI is what makes the insights from always-on call monitoring actionable rather than overwhelming.
Without AI, full call coverage creates a different problem; more data than a QA team can meaningfully review and act on. AI-powered call monitoring solves that by doing the heavy lifting on routine scoring, so your team's attention goes where it matters most.
Benefit
What it means for your operation
Structured scorecards answered automatically
Every scorecard question is answered using transcript evidence; no manual listening, no reviewer subjectivity.
Transcript-linked evidence
Every score links back to the exact exchange that informed it, giving you a defensible audit trail.
Faster review cycles
Review time drops from 30 minutes to 5 minutes per call, recovering around 4 days of analyst time every month.
Consistent scoring across your entire operation
The same criteria, applied the same way, across every agent, call type, and campaign every time.
Human oversight built in
Your QA team reviews outputs, calibrates scoring, and focuses on complex calls. AI handles the routine. Governance stays with your team.
The result is not just faster QA. It is a more reliable, more defensible evidence base built on every call, not a sample of them.
What to look for in your call quality monitoring approach
Is your evidence transcript-linked? Generic summaries are not a defensible evidence base. Scoring decisions need to be traceable back to what was actually said.
Is your scoring consistent? If different reviewers score the same call differently, your evidence has a credibility problem. Consistent scoring logic applied across all interactions removes that subjectivity.
Does your QA sit within your analytics platform? If scoring, feedback, and reporting live in separate tools, you create friction and risk. Everything should be in the same place.
Is human oversight built in? Your QA team should be able to review, challenge, and calibrate outputs. Always-on monitoring supports human-led governance, it does not replace it.
Are you scoring the right calls? Configurable triggers and criteria by call type, queue, campaign, or outcome, mean your monitoring effort goes where the compliance risk is highest.
The question is not whether you can afford to monitor every call
It is whether you can afford not to.
Ofcom and the FCA have both made clear that evidence of compliance needs to be consistent, documented, and demonstrable. A sampling process may satisfy an internal audit. It is unlikely to satisfy a regulator asking for proof of good outcomes across your entire customer base.
Always-on call quality monitoring closes that gap. It gives your QA team better data, gives your compliance function defensible evidence, and gives your operation a consistent view of what is actually happening on the phones across all calls, rather than just the ones you happened to pick.
Download the UK Contact Centre Regulatory Guide 2025–2027 to see how the FCA and Ofcom compliance obligations facing your sector map to your call monitoring approach and what good evidenced practice looks like in both.
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When you get it right, you build trust, loyalty, and efficiency. If you get it wrong, you risk frustrating customers, increasing churn, and even regulatory trouble.
Long waiting times and poor call handling don’t just test patience; they directly impact outcomes. Customers who are satisfied with wait times are 2.6x more likely to repurchase, and 3x more likely to recommend a brand (Qualtrics 2025).
So, if you’re a contact centre leader aiming to reduce customer churn and strengthen reputation, then optimising call handling operations is essential. Drawing on insight from our ,, here are the five most common mistakes that hurt customer experience and compliance and how to avoid them.
1. Long average handling times without a call resolution
55% of customers abandon calls because of long waits. It’s an all too familiar frustration, but it’s the way contact centres tackle it that makes all the difference.
The knee-jerk reaction is to push agents to “be faster,” but it often backfires. When speed becomes the only metric, compliance takes a back seat, important details are missed, and customers end up calling back because their issue wasn’t fully resolved the first time around. That adds more volume, along with more cost and frustration.
The more effective approach is to focus on resolving calls the first time. That involves giving agents the tools and context to handle conversations confidently and consistently:
Skills-based call routing means customers reach the right person the first time. While routine queries go to newer agents, complex or sensitive issues are routed straight to specialists or agents with more experience.
Call recording and reporting tools can uncover repeated bottlenecks and delays, helping managers coach more effectively.
Agent assist features, such as call scripts and prompts help to keep conversations on track without rushing, reducing compliance risks.
By fixing the causes of long average handling time, such as poor routing, lack of context, or inefficient workflows, contact centres can cut waiting times and keep customers from hanging up.
For deeper strategies on reducing average handling time (AHT) while preserving that all-important customer experience, see our guide on How to Reduce Average Handle Time.
2. Poor call routing
Yes, being left on hold is frustrating, but being bounced between agents and departments is worse. In fact, 34% of customers abandon calls after being transferred multiple times.
Every unnecessary transfer forces customers to repeat themselves, delays resolution, and erodes trust in your service. It’s inefficient and leaves people questioning whether your business is competent at all.
Intelligent call routing solves this by matching enquiries to the right place first time:
Skills-based routing directs complex or sensitive cases to the most experienced agents.
IVR menus streamline routine queries and cut unnecessary transfers.
CRM integration gives agents context immediately, so customers aren’t asked to repeat themselves.
With fewer transfers and faster resolutions, customers stay on the line and crucially, on your side.
3. Lack of agent training on compliance protocols
When customers call with complaints or sensitive issues, they want to feel heard and reassured they’re in safe hands.
But if an agent sounds unsure or handles a situation incorrectly, trust is lost. Our Voice of the Consumer Report shows this has real consequences: 35% of customers have abandoned a call because the agent couldn’t understand their situation.
So, what’s the solution? Invest in ongoing coaching and visibility:
Drag-and-drop scripting tools guide agents through tricky or regulated conversations step by step.
Speech analytics and sentiment analysis flag risks early and speed up QA reviews.
Targeted coaching and live monitoring allow managers to step in before issues escalate.
Well-trained agents aren’t just more compliant. They’re more confident, faster, and deliver better CX.
4. Not capturing or acting on customer feedback
When service quality falls short of customer expectations, they rarely hold back: 66% leave reviews after a negative experience. One of the biggest mistakes many contact centres make is failing to capture or act on their feedback, thus missing opportunities to fix the most common issues that lead to customer complaints in the first place.
With the right technology in place, contact centres can take customer feedback (one of the richest sources of improvement) and turn it into action.
Here’s how:
Speech analytics records 100% of calls, and with speech-to-text transcripts, managers can review real conversations. By spot-checking and searching for recurring issues, like complaints about wait times or poor transfers, managers can act on weaknesses in call-handling processes.
CRM integrations can also be utilised to link feedback with customer history, highlighting any customer retention risks or gaps in agent onboarding.
Post-call surveys and IVR feedback can capture immediate customer sentiment and reactions, feeding CX metrics such as CSAT and NPS.
When feedback loops are closed, customers feel heard, agents improve faster, and compliance risks are caught before they escalate. This is only possible with a well-defined, data-driven contact strategy guiding your approach.
5. Over-reliance on AI or automation
70% of customers prefer to speak to a human for complex situations, and 20% say AI doesn’t understand them. The takeaway from those statistics is that automation is powerful. But only if it supports rather than replaces live agents.
Used well, automation makes operations more efficient:
IVR menus and AI agents handle simple, repetitive tasks like account checks or payment reminders instantly.
Seamless escalation to live agents ensures sensitive or complex queries are handled with empathy and context.
This hybrid approach keeps costs and waiting times down, but also reassures customers that when they need to speak to a human, someone is available.
These five mistakes; long handling times, poor routing, inadequate training, ignoring feedback, and over-reliance on automation do more than just hurt customer experience. They also increase compliance risks due to inconsistent handling and breaching customer trust.
Used effectively, software and automation can support your people, not replace them. By combining the right tools and processes, contact centres can deliver a service that’s faster, more compliant, and more human, even under cost pressure.
See how MaxContact helps you meet customer expectations and improve compliance. Book a demo today.
Blog
5 min read
WHAT OFCOM AND PECR REGULATIONS REALLY MEAN: A QUICK GUIDE
The rules governing how UK contact centres dial, who they can call, and what it costs to get it wrong have changed significantly. This guide cuts through the complexity so you know exactly where you stand.
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Industry regulator Ofcom produces regulations around what contact centres can and can't do when it comes to automatic dialling and CLI. On top of that sits the Privacy and Electronic Communications Regulations (PECR), enforced by the ICO. This covers consent, suppression against the TPS and CTPS registers, and fines for getting marketing calls wrong.
The regulations can be confusing, having undergone numerous iterations over many years. There is no single source of truth - there isn't even a complete version of all the regulations in one place. And as of 2026, the landscape has shifted again.
With that in mind, we've produced a no-nonsense guide to the current regulations surrounding the use of automatic calling equipment (ACS), updated to reflect the Data (Use and Access) Act 2025 (DUAA) changes now in force, the updated Ofcom CLI guidance applied from 29 January 2025, and the complaints provisions due to take effect from 19 June 2026.
It's important that you know these regulations, because neither Ofcom nor the ICO accept ignorance as a defence. And the penalties have changed significantly. The maximum PECR fine (which used to be capped at £500,000) is now £17.5 million or 4% of global annual turnover, whichever is higher. That's a 35-fold increase. Directors can also be held personally liable for serious breaches.
For reference:
ACS = Dialler software
Abandoned call = dropped call
Connect = Live call passed to an agent
The guide is split into two parts: the Ofcom rules that govern how you dial, and the ICO/PECR rules that govern who you can call and what it costs if you get it wrong.
Part 1: Ofcom rules for automated dialling
Silent calls
There are three main causes of silent calls:
False positives
Abandoned calls (with no message)
Agents receiving calls and not speaking or being on mute, which is a reasonably significant cause.
In 2010 Ofcom said companies “should ensure their abandoned call rate is less than 3% of all live calls.”
That seemed clear enough. If dropped (or abandoned) calls were less than 3% of your total, you were safe. Or so many of us thought.
But as it turned out, this was a misinterpretation. Ofcom has since clarified that 3% was meant as a measuring stick and the actual target is 0%. In other words, you can attract regulator scrutiny with any percentage of dropped calls.
Despite Ofcom’s clarification, many people in the industry still think the 3% rule applies – and some even run their diallers with 3% in mind. We have even seen suppliers of dialler equipment advertise the 3% rule as compliant.
It isn’t. This is why we developed our un-droppable algorithm, which helps contact centres stick to 0% dropped calls even in blended environments.
Knowing how to calculate the drop call rate accurately is essential if you want to remain compliant, and there are still quite a few systems that get it wrong. They either use the wrong formula or, knowingly or otherwise, add inbound and manual dial connects into the equation to artificially reduce the drop call rate.
The correct formula is:
Drop rate = Drops/(Drops + Connects)
It’s worth checking Ofcom’s guidance (see Section A3.8) on calculating the drop call rate. It has examples with AMD both on and off.
15 second minimum ring time
This rule stipulates that you have to call a number for a minimum of 15s before disconnecting as a no answer.
The rule was introduced to prevent the practice of “pinging”, whereby diallers would ring a number for 1 second to try and generate a missed call. The next day agents would dial all the numbers found to be “live”. You can imagine how annoying this was for customers.
The only contentious point around the 15s minimum ring revolves around preview calls, which are automated but in every other way are the same as a manual call. Manual calls are not restricted to the 15s minimum. Because of this, whether or not you need to adhere to the minimum ring time rule on preview calls is open to interpretation. The Ofcom wording is in Section A2.15.
Rotating CLI
Not long ago, there was a trend for calling line identification (CLI) calls to display local numbers. The system would present a Manchester number when calling a Manchester number, a Newcastle number when calling a Newcastle number, and so on.
This was primarily done to increase connect rates, and it worked pretty well. It also rotated the numbers, so people didn’t recognise you.
But because Ofcom and the ICO base complaints on the CLI, it was seen as a way of avoiding investigation because contact centres were presenting 150+ different numbers. So complaints to a single number were low, even when complaints about the call centre as a whole might have been very high.
Ofcom acted, and carriers are no longer allowed to automatically rotate numbers, so the practice is vastly reduced. But you can still present different numbers if you have a valid reason. For example, a well-established car dealership with branches around the UK, but a central call centre, can present a local dealer’s number.
There’s a lot of controversy around AMD use. Ofcom now makes firms take false positive rates into consideration when calculating drop rates (though it has suggested it may drop this).
This is because inadequate systems with poor AMD were causing silent calls on false positives. In other words, when the system thought a live person was an answering machine, no message played and the call was not passed to an agent (see below on leaving a message).
But AMD use is not banned, and it can play an essential role in the productivity of contact centres. In fact, it can increase efficiency by 100% in some cases, but it must be used correctly.
CPA stands for Call Progress Analysis and is part of the AMD function. Two seconds is the amount of time your CPA is given to determine whether the called party is an answering machine or a live person.
Many providers say two seconds is not enough and, as a result, AMD can’t be used compliantly. They’re wrong. In our case, if we can’t determine whether the answered call is an answering machine or not, we pass the call through to an agent and play it safe.
If your current system “holds” onto the call longer than two seconds you are non-compliant, which is why you often get recommended to turn AMD off rather than the vendor resolving the problem.
In a silent call, someone answers the phone only to be met with silence from the other end. Needless to say, Ofcom is not in favour of silent calls.
It’s recommended that an answer phone message is left, so false positives would no longer result in silent calls. The problem here is the huge proliferation of answer phone messages, but Ofcom’s number one priority is to tackle silent calls. It all comes down to the contact centre: you have to make the choice.
When dialling predictively you are calling more people than you have agents, which can occasionally result in dropped calls. Instead of silent calls, Ofcom insists a drop call message is played to the consumer. It also offers guidelines on what the message should and shouldn’t say.
In the context of AMD, a false positive occurs when the system detects an answer machine even though a person has answered the phone. This results in silent calls and complaints from consumers.
The recommendation from Ofcom here is to play an answer machine message. Consumers will hang up, but at least they won’t experience a silent call that can be at best annoying and at worst frightening.
Carrier-level call blocking has moved from an emerging measure to an established part of Ofcom's approach to nuisance and silent calls, and it has intensified. What it means is that termination endpoint carriers such as EE, Vodafone, BT and O2 (Telefónica), can block you if they think you are making nuisance calls to their customers. This isn't the carrier you are using to make calls, it's the network the called party is on.
Carriers share a database of nuisance callers. If one blocks you, the others may follow.
This is an automated response to perceived nuisance calling, based on two main factors:
Connect rate or ASR (Answer Seizure Ratio). If your connect rate to Vodafone (for example) is low (i.e. people aren't answering the phone) then Vodafone will interpret this as people not wanting to talk to you.
ACD (Average call duration). Taking Vodafone again as an example, if call duration length is low Vodafone might view this as customers not wanting to speak to you. "Low" typically means less than 30 seconds. Leaving an answer machine message can help, as it increases the average call duration.
These factors will often result in an automatic calling block to Vodafone numbers from your CLI.
The only way to get around this is to change your number. You should also make a complaint to the termination carrier if you think they have blocked you by mistake, but be aware there is no formal appeals process, so prevention through disciplined call pacing, accurate targeting and message quality is a far better strategy than remediation.
What changed in January 2025
Ofcom's updated CLI guidance came into effect on 29 January 2025, closing a long-standing loophole that allowed scammers abroad to spoof UK numbers. Under the updated guidance, calls entering the UK from overseas that present a UK number as a Presentation Number must be blocked, with a limited number of legitimate exceptions (for example, UK mobile users genuinely roaming overseas).
For legitimate UK contact centres, the direct impact is small, but the indirect impact matters. Consumer trust in unknown numbers is at a historic low, carriers are more willing than ever to block, and the bar for what looks like "legitimate" dialling behaviour to a carrier algorithm keeps rising.
There is also a live Ofcom consultation (published July 2025) on extending blocking to calls from abroad that spoof UK mobile (+447) numbers. This is likely to land in 2026 and will tighten things further.
Unfortunately, as Ofcom makes clear, this blocking policy is actively encouraged:
Page 6 – Technical Measures (Ofcom forms Strategic Working Group)
Page 5 – Strategic Working Group (Ofcom confirms the SWG has blocked a large number of nuisance calls since its formation)
You are not allowed to call previous dropped calls within 72 hours, or answer machines the same day (note: not 24 hours), unless you can guarantee an operator is present. Preview or manual dialling is fine. This is one of the reasons MaxContact has mixed-mode dialling, which means we can automatically move records from “predictive” to “preview” and back again.
What exactly “harassment” means is not clearly defined and is open to interpretation. The term “a reasonable amount” is often used, but it’s unclear what that means in practice.
This needs Ofcom clarification. It can boil down to the nature of the calls. Debt collectors have a valid reason for calling but how much is too much? We have seen agreements in place between the FCA and some contact centres that allow X calls per day but no more than Y times per week, for example.
Maximum attempts to a user
Again, this is not defined in the regulations and needs clarification. Common sense should be applied, and the strategy modified in line with the nature of the call.
DNC list
Do you need an internal one? It's not in the Ofcom regulations, but it's good practice and operationally sensible. There does need to be a way for people to remove themselves from your calling lists, either by speaking to an agent or more commonly through self-service IVRs.
It's also worth being clear that the Telephone Preference Service (TPS) is the UK's official Do Not Call register for landlines and mobile numbers. If a number is registered with TPS, you are legally required under PECR to refrain from calling it for unsolicited sales and marketing purposes and this is not discretionary. Your internal DNC list and TPS suppression are separate obligations and both need to be in place. See Part 2 for the full PECR and TPS compliance picture.
The mention of DNC lists in the Ofcom regulations is in Section A1.25 here.
Part 2: ICO and PECR consent, suppression and fines
This is where things have changed the most. The rules on who you can call, and what evidence of consent you need, have been in place for years. But the financial consequences of getting them wrong are no longer what they were.
PECR fines explained
The Data (Use and Access) Act 2025 (DUAA) received Royal Assent on 19 June 2025, with key enforcement provisions coming into force on 5 February 2026. The headline change is the fine cap. Previously, the maximum PECR fine was £500,000. Under the DUAA, PECR fines are now aligned with UK GDPR: a maximum of £17.5 million or 4% of annual global turnover, whichever is higher. That's a 35-fold increase for calling TPS-registered numbers without consent, making automated marketing calls without consent, or failing to produce evidence of consent when the ICO asks.
Director personal liability also applies. Since 2018, the ICO has been able to issue personal fines directly to company directors for PECR breaches specifically to stop directors escaping penalties by dissolving firms and restarting under a new name. This is a board-level risk, not an operations one.
In September 2025, the ICO fined Home Improvement Marketing Ltd for instigating more than 2.4 million automated marketing calls without prior consent. The pattern is consistent: the ICO is fining fewer organisations but at higher individual values, and contact centres are over-represented. Making thousands of calls a day across multiple campaigns multiplies the opportunity for a TPS-registered number or a broken consent chain to slip through. Getting this right is now a commercial risk question, not a technical configuration one.
TPS compliance
If you are making unsolicited sales or marketing calls to UK consumers, you are required by law under PECR to screen against the Telephone Preference Service (TPS) the UK's central opt-out register for individuals, sole traders and partnerships who don't want to receive marketing calls. There is no threshold, no exemption for small volumes, and no grace period.
A few points that catch contact centres out in practice:
TPS applies at the point of the call, not the point of data purchase. "The data was TPS-screened when we bought it" is not compliant.
Consent overrides TPS. If someone has given valid, specific, evidenced consent to receive calls from you, you can call them even if they're on TPS. The burden of proof sits with you.
Screening means before the call, not after. You can't call to check whether someone is happy to be called - that call is the breach.
The ICO standard is that marketing lists must be screened at least every 28 days if the list is still being called. That's 28 days (four weeks) not "monthly". If you're still calling the same list, that's 13 screenings a year, not 12. Real-time screening via an API into the dialler is the strongest position to be in.
If your third-party data supplier says it screens against TPS, you're still responsible for confirming that it does. Spot-check the data, ask for screening logs, and ask what consent statement was presented at the point of data collection. If the answer is vague, you share responsibility for any breach.
CTPS is the business-to-business equivalent of TPS. The Corporate Telephone Preference Service covers corporate subscribers. For example, limited companies, PLCs, LLPs, Scottish partnerships, government bodies, schools, colleges and charities, who have registered their objection to receiving unsolicited marketing calls.
If you're running B2B outbound, CTPS compliance is a legal requirement. The same PECR enforcement regime applies, which means the same £17.5m or 4% of turnover cap.
Two failure modes trip B2B contact centres up repeatedly. First, assuming B2B is exempt. It isn't. Second, screening against TPS but not CTPS; a B2B list screened only against TPS will still contain CTPS-registered numbers. If you're calling businesses, you need both.
Automated decision-making and AI in your dialler
This is a genuinely new area, and one that will matter more through 2026.
The DUAA makes it easier to deploy AI-driven processes in contact centres (automated lead scoring, AI-driven call routing, AI-assisted collections prioritisation, AI quality scoring) but introduces mandatory safeguards. If you're using AI to decide who gets called, in what order, or with what script, you now have specific obligations. Customers must be informed of significant automated decisions that affect them, must be able to challenge those decisions, and must be able to get a human to look at them. From 19 June 2026, they'll also have a new right to complain directly to you as the data controller.
In practice:
Map where AI is making decisions in your contact strategy
Document your lawful basis for each
Make sure there's a human-override route your agents and team leaders know how to action.
ICO guidance on ADM under the DUAA is expected through 2026.
MaxContact is your friend here. Our sophisticated customer engagement solution will keep dropped calls to an absolute minimum (in fact, close to zero), while helping you remain compliant.
The regulatory landscape for UK contact centres has shifted significantly, and it will keep shifting.
Download the UK Contact Centre Regulatory Guide 2025–2027 for a full breakdown of what Ofcom, the ICO, and the FCA now expect from your operation, and what the consequences look like if you get it wrong.
Blog
5 min read
Your Contact Centre Has Four Problems. AI Is Already Solving Them.
Most contact centre teams are sitting on the same four challenges. Here's what the data says — and what good looks like.
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If you run a contact centre, the chances are you're managing rising call times, inconsistent quality reviews, repeat contacts that erode margin, and a personalisation gap that's hard to close without the right data infrastructure underneath it.
None of these are new problems. But the distance between where most operations are today and what's now achievable is narrowing fast - and the teams pulling ahead aren't waiting for a full platform overhaul to make it happen.
At MaxContact's recent webinar, hosted by Marketing Director Kayleigh Tait and Principal Product Manager Conor Bowler, we worked through four specific challenges that are costing contact centres time and money right now - and showed, live, how AI is solving each one. Here's what we covered.
Challenge 1: Call length is rising, and post-call admin is a big reason why
Average service call duration in the UK is now 422 seconds - seven minutes per call - according to Contact Babel. That's the highest figure recorded in 20 years of data collection, and it's been climbing steadily since 2004. There's no sign it comes down on its own.
A large part of the reason is fragmentation. 96% of agents are still navigating multiple systems on every single call. Only 4% of UK contact centres operate from a single unified desktop. 40% of agents are juggling more than four applications at once - doing real-time system-surfing while simultaneously trying to solve a customer's problem or make a sale.
Then there's wrap time. 18% of every call is post-call admin: writing up notes, updating records, triggering next steps. That's queue time growing while your agents do data entry.
The commercial impact is significant. For a 50-agent contact centre making 50 calls a day, a 50% reduction in wrap time is worth over £175,000 a year - based on MaxContact's own ROI modelling.
What good looks like:
An agent wrap-up summary that generates automatically within seconds of a call ending, built from a live stereo transcript that's already separated the agent's voice from the customer's. The agent reviews it, makes any edits, and submits. No blank page. No three to five minutes of typing between every call.
MaxContact's Agent Wrap-Up Summary feature — currently in alpha testing and moving to beta in mid-June — does exactly this. Prompts are fully configurable via Prompt Studio, so the output format, structure, and language match your operation's context, whether that's a collections agency, a sales team, or a customer service function.
Challenge 2: Repeat contacts are eroding margin and driving churn
42% of UK consumers have already switched provider because of a poor contact centre experience - not because of a product issue, but because of the experience itself. A further 38% have seriously considered it. MaxContact's consumer research, shared at the After Work with MaxContact event, makes clear this isn't an edge-case risk.
First contact resolution is what Contact Babel calls the "miracle metric." It's consistently cited as one of the top two KPIs most influential on customer satisfaction. Every repeat call is a direct hit on that number - and at roughly £5 per service call, a repeat contact doubles your cost before you've factored in agent time and churn risk.
The AI angle here is often misunderstood. 69% of customers rate AI worse than humans for understanding their issue - but the problem usually isn't the AI itself. It's where it's introduced in the customer journey. AI deployed in an emotionally charged or complex situation will struggle. The bigger failure point is the handover: when a customer escalates from an AI interaction to a human agent and has to repeat everything from scratch. That's where trust breaks.
What good looks like:
Context continuity. When a human agent picks up - regardless of whether the previous interaction was with an AI agent, a chatbot, or a colleague - they start with the full picture. Customer history, intent, what happened last time, what was agreed. Not a blank screen.
That requires clean data flowing across your channels and a single interface for agents to work from. It's a foundational requirement, not an aspirational one.
Challenge 3: QA based on a sample of 1–2 calls per week isn't good enough
The average contact centre reviews one to two calls per agent per week. Contact Babel's most recent guide describes this explicitly as "neither fair nor valid as a performance measurement tool." That's not a MaxContact opinion - it's the industry's own assessment of its standard practice.
The consequence is that coaching decisions, script adjustments, and performance reviews are all made on a handful of conversations selected at random. Objection handling failures, compliance drift, and the moments where an agent is genuinely struggling can remain completely invisible until the problem is already embedded.
What good looks like:
100% call coverage. Scorecards built on every conversation, not a sample. AI that makes that achievable without overwhelming your QA team.
MaxContact's AI call scoring — now generally available to all Conversation Analytics customers — reduces QA review time per call from 30 minutes to 5 minutes. That's approximately four days of analyst capacity returned to the team every month. Capacity that can go into actual coaching, script development, and performance improvement.
Scorecards are fully configurable: yes/no questions, rating scales, observation notes, auto-fail criteria. Business context can be set per scorecard so the AI understands your products, processes, and compliance requirements before it starts scoring. Scheduled auto-QA at scale — allowing always-on scoring as calls come in, or one-off compliance campaigns across historical data — is moving to beta on 6 July, with general availability planned for early August.
Challenge 4: Personalisation requires the right building blocks first
76% of consumers say personalised communications influence their brand choice, according to Salesforce's State of the Connected Customer. Personalisation at conversation level isn't a luxury - it's a commercial lever.
But it doesn't start with AI. It starts with having the right infrastructure in place:
Customer history and intent available before the conversation starts
In-call sentiment detection so agents know when someone is frustrated or at risk
Consistent context across channels - what happened on the last call, the last chat, the last AI interaction
Next-best-action guidance that surfaces what your best agents do in key moments, and replicates it across the team in real time
Once those building blocks are in place, personalisation stops being an aspiration. It becomes the logical next step, because you already have everything you need.
The bigger picture: it's not about solving one problem in isolation
The demo Conor ran at the webinar wasn't designed to show five separate features. It was designed to show how they connect.
A single agent interface. An automated wrap-up that feeds clean data into the next interaction. Real-time transcription with stereo accuracy that improves everything built on top of it. AI scoring across 100% of conversations. Context that follows the customer, not the channel.
The teams that are getting this right aren't deploying AI as a standalone fix for one metric. They're building a connected system where each piece makes the next one work better.
That's the direction of travel. And a lot of it is available right now.
Call Centre Quality Monitoring: Why Sampling Isn't Enough
Quality assurance is one of the most compliance-critical functions in any contact centre, and one of the most under-resourced. For most operations, the gap between what QA teams can review and what regulators now expect to see evidenced has never been wider.
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Most contact centres review a small fraction of their calls. A QA analyst picks a handful, scores them, flags what went wrong, and then moves on. It feels like it ticks the box for quality assurance. But for Ofcom-regulated telecoms operations and FCA-regulated financial services firms, it’s not enough, and the consequences of getting it wrong have never been higher.
This article explains why call sampling creates compliance exposure, what always-on monitoring looks like in practice, and what to look for when evaluating your current approach.
What is call quality monitoring?
Call quality monitoring is the process of reviewing agent-customer interactions to assess whether they meet your quality, compliance, and performance standards.
It typically covers:
What was said and how the agent handled the conversation
Whether compliance scripts and protocols were followed
How vulnerable customers were identified and managed
Whether the outcome was appropriate for the customer
How performance compares against your scoring framework
When call quality monitoring is done consistently, it gives you a documented evidence-base across every call type, agent, and campaign. But when it’s done poorly or too infrequently, it leaves gaps that regulators are increasingly likely to find before you do.
How do most contact centres currently monitor calls?
Sampling is the typical approach many call centres take to monitoring calls. A QA reviewer listens to a set number of calls per agent per month, scores them against a framework, and feeds the results back into coaching. It is time-consuming work, so let’s break down the numbers.
Example:
A single reviewer handles 50 calls a month at 30 minutes per call.
This amounts to 25 hours of review time.
And it is still only a fraction of the total call volume reviewed.
The problem here is not the effort; it's the coverage. On average, contact centres manually evaluate 5% of calls per week, meaning many QA operations are leaving the majority of interactions unreviewed. This means:
You don’t know whether your agents are consistently identifying vulnerable customers.
You don’t know whether compliance scripts are being followed on the calls you did not pick.
You are not building an evidence bse, only a small sample.
Manual call sampling statistics
FCA Consumer Duty: you need evidence across every interaction, not a snapshot
For debt collection, insurance, and other FCA-regulated contact centres, the stakes are different but the problem is the same. Consumer Duty requires firms to demonstrate they are delivering good outcomes for retail customers, not just on the calls they reviewed, but consistently and measurably across their entire operation.
The FCA has shifted decisively from implementation to enforcement. Regulators are no longer asking whether you have a quality monitoring process. They are asking whether you can prove, with documented evidence, that your agents are handling vulnerable customers correctly, following compliant scripts, and not causing foreseeable consumer harm. And that’s for every call, not just the ones you checked.
A sampling approach does not produce that evidence. It produces a snapshot.
For more on what the FCA now expects from contact centres in financial services and debt collection, see our Consumer Duty guide.
The problem with call sampling: A Summary
Sampling typically covers around 5% of calls per week, leaving the 95% of interactions unreviewed and unverifiable
Compliance drift happens slowly. By the time sampling catches a behaviour, it is already established and harder to coach out
Poor agent behaviour on outbound calls can go undetected long enough to trigger carrier blocking or an FCA flag
Vulnerable customers may not be identified correctly on calls you never reviewed
Good performance goes unrecognised as you cannot replicate what you cannot see
A sample tells you what happened on the calls you chose to review. It does not tell you what is happening in your operation
From sampling to monitoring: what's actually required
Moving from sampling to consistent call monitoring is not simply a matter of reviewing more calls. It requires the right infrastructure in place, and historically, that infrastructure was either too expensive, too time-consuming, or both.
At a minimum, always-on monitoring requires:
Call recording across all interactions, not just selected campaigns or call types
Transcription that converts voice to text accurately enough to be reviewed and searched at scale
A platform that connects recording, transcription, scoring, and reporting in one place rather than across multiple disconnected tools
Without all three, monitoring at scale either falls back on human reviewers (which is where the 25-hours-per-50-calls problem comes back in) or produces data too inconsistent to be useful as a compliance evidence base.
MaxContact's Conversation Analytics brings all of this together in a single platform. Call recording, real-time transcription, and reporting sit alongside each other. This gives your QA team a single place to monitor, review, and evidence what is happening across every interaction, without stitching together multiple tools or managing separate systems.
The reason most contact centres have defaulted to sampling is not because they did not want better coverage. It is because the operational cost of achieving it manually was prohibitive. A team large enough to review every call would cost more than most mid-market operations can justify. But that has changed.
How Conversation Analytics makes always-on monitoring feasible
Conversation Analytics is the platform that makes consistent, always-on call monitoring operationally viable for mid-market contact centres.
Rather than relying on a QA team to manually select, listen to, and score calls, Conversation Analytics connects call recording, transcription, scoring, and reporting in a single platform – automating quality assurance. Every interaction is captured, transcribed, and made reviewable, giving your QA team complete visibility across all call types, all agents, and all campaigns without the resourcing overhead of manual review at scale.
The cost comparison is significant. Replicating meaningful call coverage with human reviewers alone would cost an estimated £14,000 per month in analyst time for a mid-sized contact centre. Conversation Analytics delivers that coverage at a fraction of the cost, freeing your QA team to focus on coaching, calibration, and the complex calls that genuinely need a human eye.
How AI call monitoring surfaces insights faster
AI is what makes the insights from always-on call monitoring actionable rather than overwhelming.
Without AI, full call coverage creates a different problem; more data than a QA team can meaningfully review and act on. AI-powered call monitoring solves that by doing the heavy lifting on routine scoring, so your team's attention goes where it matters most.
Benefit
What it means for your operation
Structured scorecards answered automatically
Every scorecard question is answered using transcript evidence; no manual listening, no reviewer subjectivity.
Transcript-linked evidence
Every score links back to the exact exchange that informed it, giving you a defensible audit trail.
Faster review cycles
Review time drops from 30 minutes to 5 minutes per call, recovering around 4 days of analyst time every month.
Consistent scoring across your entire operation
The same criteria, applied the same way, across every agent, call type, and campaign every time.
Human oversight built in
Your QA team reviews outputs, calibrates scoring, and focuses on complex calls. AI handles the routine. Governance stays with your team.
The result is not just faster QA. It is a more reliable, more defensible evidence base built on every call, not a sample of them.
What to look for in your call quality monitoring approach
Is your evidence transcript-linked? Generic summaries are not a defensible evidence base. Scoring decisions need to be traceable back to what was actually said.
Is your scoring consistent? If different reviewers score the same call differently, your evidence has a credibility problem. Consistent scoring logic applied across all interactions removes that subjectivity.
Does your QA sit within your analytics platform? If scoring, feedback, and reporting live in separate tools, you create friction and risk. Everything should be in the same place.
Is human oversight built in? Your QA team should be able to review, challenge, and calibrate outputs. Always-on monitoring supports human-led governance, it does not replace it.
Are you scoring the right calls? Configurable triggers and criteria by call type, queue, campaign, or outcome, mean your monitoring effort goes where the compliance risk is highest.
The question is not whether you can afford to monitor every call
It is whether you can afford not to.
Ofcom and the FCA have both made clear that evidence of compliance needs to be consistent, documented, and demonstrable. A sampling process may satisfy an internal audit. It is unlikely to satisfy a regulator asking for proof of good outcomes across your entire customer base.
Always-on call quality monitoring closes that gap. It gives your QA team better data, gives your compliance function defensible evidence, and gives your operation a consistent view of what is actually happening on the phones across all calls, rather than just the ones you happened to pick.
Download the UK Contact Centre Regulatory Guide 2025–2027 to see how the FCA and Ofcom compliance obligations facing your sector map to your call monitoring approach and what good evidenced practice looks like in both.
Download
5 min read
What UK Customers Really Want from Contact Centres in 2026
We've just published our Voice of the UK Consumer 2026 report — and the picture it paints for contact centre leaders is both urgent and actionable.
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We surveyed 1,000 UK adults who had interacted with a contact centre in the last 18 months. The findings reveal something that goes beyond wait times, channel preferences, and AI adoption. This year, the biggest barrier to customer contact isn't the interaction itself - it's getting consumers to engage in the first place.
The Numbers Don't Lie: Trust Is Now an Operational Problem
Before we get to what consumers want, we have to address what's getting in the way. Our research reveals a structural trust deficit playing out before a single agent picks up the phone.
69% of UK consumers always or often screen calls from unknown numbers
46% have ignored a message from a legitimate company because they assumed it was a scam
Only 22% strongly agree they can tell when unexpected company contact is genuine
77% of those who ignored a legitimate call experienced a real consequence such as a missed appointment, an unresolved problem, a missed payment deadline
This is the Trust Gap: the growing distance between a company's confidence in its own outbound contact and what consumers actually believe when they see an unknown number. It affects every sector with outbound ambitions and it can't be fixed by dialling more.
Call Avoidance Varies Dramatically by Sector
Not all sectors face the same screening wall. Our data shows stark differences in call avoidance rates, and the gap between best and worst performing sectors is significant.
Loans, credit and debt management companies are the most avoided, with 37% of consumers saying they'd be least likely to answer a call from this sector. Insurance follows at 25%, with telecoms, technology, and retail/e-commerce close behind at 22–23%. Banks and building societies fare better at 16% avoidance, and notably, they also hold the highest sector trust score at 96%.
The lesson? Trust and answer rates move together. Sectors that have invested in consumer trust over time are reaping the operational benefits in their outbound performance. Those that haven't are paying the price at the identification gate.
"This data should make every contact centre leader pause," says Ben Booth, CEO of MaxContact. "Consumers broadly trust the sectors they deal with, but that trust doesn't translate into picking up the phone. If consumers can't tell the difference between a legitimate call and a scam, outbound strategies will struggle to deliver."
What Actually Makes Consumers Pick Up
The good news is that the Trust Gap is closable. When we asked consumers what would make them more likely to answer, two things stood out clearly:
82% say they would be more likely to answer if caller ID clearly identified the company name
80.5% say a pre-call text or email would make them more likely to pick up
These aren't aspirational preferences - they're operational levers. The problem isn't the dialler. It's the identification gate. Legitimate contact centres aren't losing the persuasion game. They're often not getting on the pitch.
Contact centres should prioritise:
Branded caller ID and carrier number reputation management - so consumers can recognise your call before they decide whether to answer
Pre-call communication - give consumers a reason to expect your call, especially in high-avoidance sectors
Treating contact frequency as a trust variable -too-frequent contact doesn't just frustrate consumers; in regulated sectors, it carries compliance risk
AI Is Here — But Transparency Is Non-Negotiable
UK consumers have been interacting with AI in contact centres for some time. The problem is, many didn't know it.
87% of consumers believe they've interacted with AI or automation in a recent company contact. Of those, 22% were sure or fairly sure they'd been talking to AI — but weren't aware of it at the time. That's more than one in five consumers who discovered, after the fact, that part of their experience was automated.
Nearly 9 in 10 (88%) consumers say it's important for companies to clearly disclose when AI is being used. Half say it's very important.
"The reputational risk of undisclosed AI is real and avoidable," says Ben Booth. "Consumers aren't opposed to AI - they're opposed to being kept in the dark about it. Deploying AI without disclosure doesn't just frustrate customers; it reinforces the same uncertainty that's causing them to screen your calls."
AI Adoption: Where It Works and Where It Doesn't
Consumer opinion on AI is nuanced. Where AI genuinely adds value, consumers are broadly willing to accept it:
Answering FAQs: 36%
Routing to the right department: 35%
Account updates and billing information: 26%
But the picture reverses sharply when it comes to high-stakes interactions. Over half (54%) say they don't want AI involved in emergency situations. Significant numbers also object to AI involvement in complex account problems (50%), financial discussions (49%) and when negotiating terms (46%).
Crucially, 71% of consumers say they'd be comfortable with AI helping resolve an issue faster — as long as a human agent was available throughout. The acceptance of AI is conditional on a clear, accessible escalation path.
Humans Still Matter Where It Counts
Despite the growth of AI and automation, consumers are clear about when they need a person:
Emergency situations - 41% want a human agent
Complex account queries - 33%
Financial discussions — 29%
Explaining a sensitive or personal matter - 26%
Making a complaint - 23%
These aren't edge cases. An AI that handles a billing query well creates modest goodwill. An AI that mishandles a bereavement disclosure or an emergency can permanently damage a customer relationship.
When things go wrong and complaints happen, consumers care most about: a clear explanation of the outcome (39%), being kept updated throughout (37%), appropriate compensation when the company is at fault (33%), and only having to explain the issue once (31%).
What Builds and Breaks Consumer Trust
Our research shows consistent patterns in what drives contact experience, positively and negatively.
What puts consumers off before they even try:
Long wait times: 36%
Being transferred multiple times: 34%
Difficulty reaching a human: 29%
Having to repeat themselves: 28%
What good looks like:
Quick resolution -36%
Easy access to a human when needed - 35%
Knowledgeable agents - 34%
Clear communication throughout - 32%
On channel trust, email remains the most trusted channel for company contact (51%), followed by phone calls (30%) and letters (27%). For outbound communications that don't need an immediate response, email is still the most credible messenger.
Five Focus Areas for Contact Centre Leaders in 2026
Based on our findings, these are the areas that will have the most impact:
Fix the identification gate: Deploy branded caller ID, carrier number reputation management and pre-call communication. The recoverable opportunity isn't every screened call; it's the willing contacts who are filtering themselves out because they fear scams.
Make AI disclosure the default: Clearly disclose AI use at the start of every AI-assisted interaction. In regulated sectors, it's a compliance requirement. Everywhere else, the reputational risk is reason enough.
Protect the human escalation path : Across every question about AI in this study, the most-cited condition for consumer acceptance was the same: a human must be available and clearly signposted. Design the escalation as carefully as you design the AI.
Treat 'only explain once' as an infrastructure target: CRM integration, context-passing between channels, and warm handoffs are the operational response to the number one complaint driver.
Audit complaint journeys against what consumers actually need : A clear outcome explanation, ongoing updates, appropriate compensation, not having to repeat themselves, and a human presence. These five things determine whether a resolved complaint becomes a trust-builder or a churn trigger.
Want the full picture? The Voice of the UK Consumer 2026 report includes sector-by-sector breakdowns across utilities, telecoms, finance/debt, and insurance — with data on vulnerability handling, AI comfort, complaint experience, and regulatory risk. Download the full report here.
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