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.

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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.

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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.

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Challenge 1: Call length is rising, and post-call admin is a big reason why

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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.

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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.

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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.

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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.

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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.

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Challenge 2: Repeat contacts are eroding margin and driving churn

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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.

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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.

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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.

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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.

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Challenge 3: QA based on a sample of 1–2 calls per week isn't good enough

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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.

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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.

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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.

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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.

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Challenge 4: Personalisation requires the right building blocks first

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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.

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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

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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.

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The bigger picture: it's not about solving one problem in isolation

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The demo Conor ran at the webinar wasn't designed to show five separate features. It was designed to show how they connect.

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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.

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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.

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That's the direction of travel. And a lot of it is available right now.

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Watch the full webinar and explore the resources

▶ Watch the full replay on YouTube → https://youtu.be/C2ED-KwbKns

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📄 Download the Contact Babel UK Contact Centre Decision-Makers' Guide → https://www.contactbabel.com/

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📅 Book a demo or speak to your account manager → https://www.maxcontact.com/book-a-demo

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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.

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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."

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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

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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.

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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%).

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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.

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Five Focus Areas for Contact Centre Leaders in 2026

Based on our findings, these are the areas that will have the most impact:

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.

High-volume cold calling based on limited data is no longer a cost-effective outbound strategy and in the B2C world can be non-compliant.

With both sales and debt collection, the public has grown wary of unsolicited calls and generic conversations. But that doesn’t mean outbound dialling is over as a revenue engine.

It means it has to be smarter, multi-channel and data-led. Based on real-time information and a refined dialling strategy. Often personalised in tone, timing and approach.

So, if you’re reselling UCaaS today, there’s a strong chance your customers’ outbound results are being held back by the platform they’re on. When revenues stagnate, contact rates fall or conversions get harder to close, the problem usually isn’t effort - it’s strategy, data and tooling. This blog sets out what a high-performing outbound operation looks like, so you can have that conversation with confidence.

The outbound metrics your customers should be measuring

The foundation of any smart outbound strategy is good information. Help your customers understand that without the right data, they can’t tell whether calls are reaching the right people, whether agents are performing, or whether their scripts are working. Measurement isn’t a nice-to-have - it’s where improvement starts.

Outbound KPIs to share with your customers:

•      Connect rates: are calls being connected to a real person?

•      Contact rate: how often are agents reaching the right decision-maker?

•      Data penetration rate: is their data being used effectively - are they making the most of high-value leads?

•      Conversion rate: the percentage of contacts that result in a positive outcome

•      Calls to success rate: the number of calls needed per successful result

Take conversion rate as a case in point. It tells your customers two things at once: the quality of their contact data, and the effectiveness of their team.

Better data means a higher likelihood of reaching the right person. Skills-based routing - matching the right agent to the right call- increases that further. And stronger training, combined with more refined scripts, means more of those conversations end the way they should.

Qualitative insight matters as much as the numbers

Quantitative KPIs don’t tell the full story.Improving contact rates will generate more conversations - but without the right skills in place to handle them, conversion rates won’t follow.

Encourage your customers to combine the numbers with qualitative insight: what objections are coming up most, what their customers are saying about competitors, and where conversations are breaking down.Helping them bring both lenses together is one of the most valuable things you can do as a partner - and it’s a conversation most resellers never have.

Industry-specific KPIs worth knowing

The metrics above apply broadly, but it’s worth helping your customers zone in on numbers that are specific to their sector.

In debt collection, promise to pay (PTP - the percentage of calls resulting in a commitment to pay) and percentage of debt collected are key indicators. In sales, first-call close rates and average revenue per call say a lot about campaign effectiveness.

MaxContact’s KPI Benchmark Report gives a detailed breakdown of what good looks like across sectors. It’s a useful resource to share with customers who want to know how their numbers stack up.

Benchmarking: what good looks like

Once your customers know what to measure, the next step is helping them understand what the numbers mean.

MaxContact’s own research found that the largest proportion of respondents - 34%, across both sales and debt collection - reported conversion rates of between 10% and 19%. Cold outbound sales calls typically convert at 1–3%; warmer, more targeted calls can reach as high as25%.

Broad benchmark ranges for common outbound KPIs:

•      Average handling time: 4–12 minutes

•      Contact rate(cold calls): 5–15%

•      First call resolution: 10–40%

These are broad ranges and will vary significantly by sector and product complexity. The more important thing for your customers is to track their own numbers consistently over time - and to understand what’s driving movement in either direction.

What your customers can do to improve outbound performance

Once your customers are tracking the right metrics,the focus shifts to moving them. Here are the levers most likely to make a meaningful difference - and the conversations worth having:

•      Team training and coaching - conversation analytics can surface objection patterns, benchmark individual and campaign performance, and show exactly where coaching will have the biggest effect.

•      Smarter dialling strategy - when are their contacts most likely to answer? Are they prioritising by lead value? Are they using the right dialler mode for the campaign? These are practical questions you can help them think through.

•      Omnichannel engagement - how does combining SMS, email and calls affect contact and conversion rates? Could AI agents handle routine calls while human agents focus on more complex or sensitive interactions?

The performance advantage you can offer your customers

Helping your customers understand and act on their outbound performance data is a powerful way to open the door to a bigger conversation. Standard UCaaS platforms can’t offer the range of insight and capability that a specialist customer engagement solution like MaxContact provides - and once customers seethe gap, the case for change makes itself.

Think conversation analytics, AI chatbots, workforce management, intelligent outbound dialling and sophisticated contact strategies - capabilities that standard UCaaS systems simply can’t match, and that enterprise-grade platforms price out of reach for most teams.

MaxContact delivers measurable results - from 200–300% increases in contact rates to doubling sales teams’ conversion rates. Benchmark Insights Report.

That’s because its intelligent, intuitive platform lets teams build smarter outbound strategies and tailor them for every campaign.

Talk to the MaxContact partner team about adding a specialist customer engagement solution to your portfolio. Book a call

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