Afterwork with MaxContact — Wed 13 May, Manchester [Register now]
Afterwork with MaxContact — Wed 13 May, Manchester [Register now]
MaxContact Wins at the 2025 Megabuyte Emerging Stars Awards
We’re proud to announce that MaxContact has been named the Best Performing Company in Customer Relationship Management at the 2025 Megabuyte Emerging Stars Awards!
A Significant Achievement
This recognition places us among an elite group of 50 Emerging Stars, selected from an initial pool of over 6,000 companies. With only 825 meeting the strict eligibility criteria in a challenging economic climate, this award reflects our team’s commitment to innovation and excellence.
“Despite experiencing some softness in sectors like energy and longer sales cycles in recent years, MaxContact has maintained c. 30% revenue growth, ahead of most other vendors in the contact centre software market. A key proponent of this is its conversational AI product strategy, with AI-enabled products featuring in 80%+ of deals.”
Moving Forward
This award validates our strategic direction and focus on delivering innovative solutions that address real customer needs. Our investment in conversational AI technology, Spokn AI, continues to drive our success and differentiate us in the market.
We remain committed to supporting our 100+ UK customers across BPO, communications, financial services, utilities, and retail sectors with solutions that enhance their customer engagement capabilities.
We’d like to thank our dedicated team, partners and valued customers for their ongoing support and confidence in MaxContact.
About Megabuyte
Megabuyte supports UK scale-up and mid-market software & ICT Services companies to develop robust growth strategies, understand their competitive landscape and customer sentiment, benchmark their financial performance and valuation, and identify and track M&A targets. They provide proprietary insights and data through their subscription research service, offer packaged consulting services, and give access to their network of some 500 tech sector CEOs through events and their expert network.
About the Emerging Stars Awards
The Emerging Stars awards are part of the Megabuyte100 award series which collectively celebrate the 100 best-performing technology companies in the UK. The awards identify the UK’s best-performing technology scale-ups as defined by Megabuyte’s proprietary Scorecard methodology, complemented by expert qualitative insights from their analysts. Evaluation criteria encompass factors such as size, growth, and margins, highlighting the top 50 best-performing scale-up companies in the UK.
Learn More
For further information about the 2025 Megabuyte Emerging Stars Awards and to see the complete list of winners, click here to access the full Megabuyte report.
Here’s to continued success and innovation throughout 2025!
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Are we at the beginning of the end, or the end of the beginning? As far as Covid-19 is concerned, nobody seems entirely sure. The vaccination rollout promises an eventual release from lockdown, but scientists remain cagey about when everyday life might properly resume.
In the meantime, many of your sales and customer service staff are getting used to working from home. They may be there for a while yet, at least until a combination of the vaccine rollout and better summer weather allows for a cautious return to the office.
Even then, not every business will be forcing staff back into work full time. Social distancing rules are likely to remain in place for the foreseeable future, limiting the number of employees in the same space at the same time.
There’s also growing speculation that many companies will never return to pre-Covid work practices, and that some form of flexible working will become standard practice. A recent Call Centre Helper poll showed that just 7% of contact centres planned to return to the office as normal2, and ONS reported a 47% increase in demand for home working amongst call centre staff1. The data’s there to see, hybrid working, where employees spend some of the week in the office and some working from home, will become far more widespread once the pandemic ends.
The hybrid model of work
There are certainly benefits to it. According to research from Slack, most knowledge workers want a hybrid remote-office model in future. Hardly any want to return to the office full time. Those results are mirrored across sectors and industries, inferring that companies who want to attract the best talent may have to offer hybrid working as a benefit.
Even among businesses with large sales and customer service teams, the benefits of hybrid working may outweigh inevitable misgivings. Many businesses believe they can cut post-pandemic costs by reducing office estates and moving to smaller premises that only have to accommodate a proportion of a firm’s total workforce at any one time.
Put it all together, and it means remote working probably isn’t going anywhere, even after Covid. And even businesses that remain determined to return en masse to the office eventually have no real idea of when that time might be.
So, we’re trying to balance all of this, with changing consumer contact habits – increased adoption of new channels and differing contact patterns – as well as a globally reported increase in contact centre demand, with support firm ZenDesk seeing a steady 16 per cent increase in support contact requests above pre-pandemic levels3.
Productivity challenges
So instead of holding on to pre-pandemic processes, businesses might be better asking how they can adapt more effectively to the ‘normal’ of today while also preparing for whatever tomorrow might throw at them.
Or to put it simply, how do you equip your remote staff with the tools they need to work as productively away from the office as they can in it? How do you train and mentor your teams remotely? How do you continue to delight customers and drive sales when most of your team is working from home? When your workforce returns to a socially distanced office, or splits its time between the office and home, how do you maintain a consistent customer experience?
Businesses have been asking similar questions since last March, of course. But many now realise that the sticking-plaster solutions hastily implemented then are no longer enough, especially when it comes to customer contact. Communications platforms need to give employees the tools they need today, while future-proofing businesses for whatever next month, next year or even the next decade might bring.
Is cloud-first the answer?
It’s for that reason that businesses of all kinds are turning to cloud-based solutions. When your contact centre solution lives in the cloud, your agents can access it from anywhere, on any device, onboarding new starters and completing system training remotely is easier. And, with solutions like MaxContact, new features and functionality are consistently introduced as market trends and business needs change.
But there’s more to a future-proof solution than simply the convenience of cloud. It has to be highly reliable, flexible and secure, while giving you the data you need to measure performance and implement change.
MaxContact is cloud-native for that reason. You get the assurances with the combination of a fully equipped contact centre solution that fulfils all these requirements combined with a resilient uptime guarantee of 99.999% so dropouts and downtime won’t affect sales and customer service. Whilst real-time dashboards and custom reporting give managers full transparency over their teams’ efficiency, wherever they happen to be located.
reduction in training, the issue of training a workforce in the contact centre fast and easily remotely has been of major benefit
This valuable data can eventually be used to inform decision making around post-pandemic working models, giving a real insight into the benefits and challenges of remote working models based on your specific circumstances for every campaign and every call centre agent. This data becomes invaluable in a world were presenteeism in some form has been part of most of our everyday lives for the past 12 months.
Security concerns
Working from home has meant that the companies networks – that were once a secure perimeter – have expanded to every employee home and the plethora of devices they use. There’s now an increasing need to deploy communications solutions with network and data centre security baked in. But we go further. Granular permissions mean you can limit the data your home working teams have access to and remove restrictions at the click of a mouse on those days when they are working from the office.
In fact, MaxContact gives you that kind of agility throughout your contact centre operation. You can add and remove users in minutes, and equip new sites in just a couple of days. MaxContact lets you calculate your staffing requirements using statistical analysis so that, wherever your workforce is based, you always have the right staff with the right skills in place.
In other words, powerful contact centre solutions like MaxContact don’t just solve the temporary challenges of remote working. They equip your business for an uncertain future.
Use our powerful cloud platform to create an agile, secure and streamlined contact centre that not only adapts to the unpredictable challenges of the post-pandemic world.
Most outbound sales teams would describe themselves as “data-driven”. They track activity, review performance reports and measure success against targets.
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But reporting on results isn’t the same as being data-driven. In outbound sales, data only creates value when it is used to actively influence decisions; ideally, while activity is still happening rather than when it is reviewed days later.
A genuinely data-driven outbound sales team will use live performance data to shape how calls are placed, which leads are prioritised, how agents are routed and where coaching is applied. Data, technology and execution work together as a single system.
In this article, we explore what “data-driven” should really mean for outbound sales teams operating in a contact centre environment. We look at the outbound sales metrics that matter most, how technology turns those metrics into real-time decisions, and share the latest data from our Benchmark Report to help you determine whether your performance is average or genuinely competitive.
Use data to decide which leads deserve agent time
Outbound sales teams should focus on maximising productive talk time as the foundation. But the next question becomes, who should agents be spending that time speaking to?
The average first-call close rate across outbound sales teams is 25%, with 31% of teams achieving rates between 20% and 29%. This shows that conversion performance is driven less by how many calls are made and more by how effectively effort is focused.
Understanding which metrics genuinely influence outcomes is critical here. Our complete guide to call centre reporting metrics breaks down the KPIs that matter most, and how they should be interpreted in context rather than in isolation.
Sales teams should concentrate on prospects that are most likely to convert. Which means the first-in, first-out approach to lead prioritisation is an ineffective strategy.
This is where intelligent lead prioritisation tools powered by AI have a huge operational impact. By pulling data from multiple sources, such as recent engagement, historical call outcomes, conversion performance, and potential deal value, intelligent lead prioritisation ranks leads dynamically. As prospect data signals change, prioritisation updates are applied automatically, which means agents consistently spend their available talk time on the opportunities most likely to deliver results.
Use data to match the right agent to the right lead
Data-insights need not stop at determining high-value and high-intent leads. It can also influence who handles them.
While the mean average revenue per call across outbound sales teams is just under £230, over 45% of teams generate less than £59 per call. This gap highlights how widely outcomes can vary depending on agent capability.
When data is used to create value, agent assignment isn’t random or purely availability-based. Instead, performance data is used to match leads with the agents most likely to convert them. For example:
Higher-value or more complex opportunities can be routed to experienced agents with deeper product knowledge or a proven track record of closing similar deals.
Price-sensitive or early-stage leads may be better suited to agents who perform strongly at qualification and objection handling.
Sector-specific prospects can be matched with agents who have previous success in that industry or campaign type.
Skill-based routing makes this possible by using historical performance data such as conversion rates by product, deal size, objection type, or lead source. As new performance signals are captured, routing rules can be refined so decisions improve continuously.
Use real-time performance data to intervene early
Outbound sales performance can change quickly. So, relying on end-of-day or weekly reports limits how effectively teams can respond. Retrospective reporting removes the opportunity to correct issues such as poor lead targeting or gaps in agent performance.
Access to real-time performance data gives sales managers the visibility they need to intervene without burning through contact. Live dashboards show early signals, such as declining connect rates, falling conversion performance, or uneven agent productivity.
Instead of waiting for performance reviews, managers can guide execution as it happens. This might involve reallocating resources, adjusting call scripts, changing lead allocation, or providing targeted coaching.
Contact centres that use real-time insight to guide daily decision-making are better positioned to protect conversion rates and maximise the impact of agent time.
For outsourced or multi-client environments, this ability to intervene early is particularly important. Our article on how BPOs can meet their KPIs explores the additional performance and reporting challenges faced by outsourced contact centres.
Use Conversation Analytics to understand why performance varies
Surface-level metrics such as contact rate, conversion rate and first-call close rate explain what is happening in outbound sales. But the why behind performance differentiation is dependent on agents, campaigns, or lead types, and teams need insight from the conversation itself.
Our Conversation Analytics analyses 100% of outbound calls, transforming unstructured call audio into actionable insight that would be impossible to capture through manual review or random sampling.
With the ability to analyse conversations at scale, sales leaders can review and identify the underlying drivers of performance. This insight helps explain why certain agents convert more effectively, why objections stall progress, or why specific lead types underperform despite similar call volumes.
In practice, Conversation Analytics supports data-driven outbound sales teams by enabling:
More targeted coaching: Identify the techniques used in successful calls and pinpoint where individual agents need support
Better script and messaging optimisation: Surface patterns in high-performing conversations and common objections
Improved quality and compliance oversight: Analyse every call rather than small samples
Earlier identification of emerging issues: Spot shifts in sentiment, objections, or competitor mentions
If you’re looking for a broader view of how these metrics work together, our guide on how to measure call centre efficiencyexplores how performance indicators combine to drive overall effectiveness.)
Key benefits for outbound sales teams include:
Enhanced Agent Training: Identify successful techniques and areas for improvement, allowing for targeted training programmes.
Customer Sentiment Analysis: Detect changes in tone and emotion, helping agents adapt their approach in real-time.
Quality Assurance at Scale: Analyse every call, ensuring comprehensive QA and quick identification of compliance issues.
Identifying Sales Opportunities: Recognise patterns in successful calls to refine sales scripts and strategies.
Competitor Intelligence: Flag mentions of competitors, providing valuable market insights.
Trend Identification: Quickly spot emerging trends in customer behaviour or common objections.
By implementing speech analytics, outbound sales teams can gain data-driven insights that lead to more effective strategies, improved customer experiences, and better business outcomes. Use these insights to identify common objections, spot successful sales techniques, and provide targeted coaching to your team. A recent study by Forrester found that companies using AI-driven speech analytics saw a 10% increase in customer satisfaction scores and a 15% improvement in first-call resolution rates.
With speech analytics, you’re not just collecting more data – you’re gaining the ability to understand and act on the nuances of every customer interaction, transforming your outbound sales operation into a truly data-driven powerhouse.
Sustaining data-driven outbound sales performance
When combined with performance data, conversation analytics closes the loop between insight and action. Conversation analytics doesn’t sit alongside metrics. It explains them and enables more confident decisions and continuous improvement.
Using more tools or tracking additional metrics doesn’t automatically make an outbound sales team data-driven. Data only becomes valuable when it actively guides decisions across the contact strategy, from how calls are dialled, and leads are prioritised, to how agents are routed, coached and optimised.
In genuinely data-driven teams, agents and managers understand what key metrics mean, how they influence outcomes and when intervention is needed. Performance reviews focus on interpreting trends and agreeing on clear next actions, rather than simply reporting on results after the fact.
The most effective outbound sales teams connect data. By linking real-time performance insight with intelligent technology and informed decision-making, they improve results while activity is still in progress, not once opportunities have already passed.
If you want to understand how your outbound sales performance compares to other UK contact centres, benchmarking is the most effective next step.
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Here’s a number worth sitting with: 30 minutes.
That's how long it takes to manually score one call. Listen back, fill in the scorecard, write up the notes, log the result. Do that 50 times a month and you've lost on average 4 days per reviewer to scoring alone.
Most QA teams know this. They're not slow or inefficient - the maths just doesn't work. One reviewer for every 25 agents, 30 minutes a call, finite hours in the week. Something must give, and that’s coverage. The industry average sits at around 5% of calls reviewed, which means 95% of what happens on your contact centre floor stays invisible.
Not just to your QA team. To your compliance records. To your coaching programme. To the agents who deserve consistent, fair feedback on every call they handle.
That's the problem AI Call Scoring is built to fix.
Your standards applied to every call you wish to score.
The way it works is straightforward. You define your existing QA standards - built around your business rules, your compliance requirements, your definition of what a good call looks like. AI Call Scoring applies them to your selected calls, scoring each one against your criteria using evidence taken directly from the transcript.
No algorithm deciding what good looks like on your behalf. You set the standard.
What this means for your QA team day to day
One of the things that doesn't get talked about enough in QA is how demoralising inconsistency is. Two reviewers score the same call differently. An agent pushes back. The process loses credibility. And meanwhile, the team is so buried in manual scoring that the actual coaching - the conversations that change behaviour -never happen.
AI Call Scoring brings review time down from around 30 minutes to about 5 minutes per call. Your QA team stop being a scoring machine and start doing what they're good at - calibrating standards, making judgment calls, and coaching agents to improve.
For a reviewer handling 50 calls a month, that's roughly four days back every month. That's a lot of coaching time that wasn't there before.
It's not just for big teams
This is worth saying clearly because it matters: AI Call Scoring isn't just a tool for large operations with dedicated QA departments.
For teams of 50 or more agents, the time savings are significant - around 133 days per year across four QA staff, worth approximately £15k in team time. But beyond the hours, scoring more calls consistently means you start seeing the patterns that a small sample will never show you.
For smaller teams of 10 to 30 agents, it's even more of a shift. Structured QA without dedicated headcount. Team leaders reviewing scored calls in minutes. Compliance coverage that doesn't require a compliance team. And a framework that grows with the business.
When compliance is non-negotiable
For contact centres operating in regulated sectors, the stakes have risen. Consumer Duty, now actively enforced by the FCA, places a direct obligation on organisations to evidence that customers are receiving good outcomes.
When a complaint lands, you can't point to a sample. You need evidence that the specific interaction was handled correctly. AI Call Scoring gives you an auditable record of every scored call, with auto-fail rules that catch compliance breaches - a missed disclosure, an incomplete ID check - regardless of how the rest of the call went. Every call you score is evidenced, auditable and defensible.
Your team stays in control
We want to be clear about this: AI Call Scoring is there to support your QA team, not sideline them. Every scored result can be reviewed, edited, challenged or discarded. Your people stay in the loop. The AI does the volume work - your team does the thinking.
It all lives inside Conversation Analytics — scored calls, common objections, objection handling effectiveness, top performers and saved compliance views, together in one place.
Already on Conversation Analytics? It's yours.
AI Call Scoring is included within Conversation Analytics at no extra cost. If you're already using the suite, it's available to you now.
This is also just the start. Automated QA at Scale is coming later this year - fully automated scoring across campaigns at volume. More on that soon.
Outbound still pays - your customers just need a smarter approach
High-volume cold calling is losing ground. Here's what a high-performing, data-led outbound strategy looks like - and how to sell it to your customers.
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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
Blog
5 min read
Are You Ready for AI In Your Contact Centre?
Learn what AI readiness really looks like - and download the scorecard to assess yours.
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AI doesn’t fix contact centres. It scales them. If your journeys are joined up, automation can reduce the pressure your team is facing. However, if they’re fragmented, AI amplifies the friction - faster transfers, repetition and customer effort. That’s why the most useful question contact centre leaders can ask themselves isn’t “What can AI do?” - it’s, "Are we actually ready for it?".
Whether you’re running sales and retention in telecoms, payment collections with vulnerability considerations in finance, customer support in utilities, or managing multiple client programmes in a BPO, the readiness question is the same - do we have the foundations to automate without increasing customer effort or operational risk?
“Always-on” support is an operating model, not a staffing one. It's built to remove avoidable demand, protecting your team's time for high-judgement conversations, and making escalation safe when risk or complexity arises.
Always-On Service Starts with Resolution, Not Headcount.
Consumers are increasingly expecting help at any time of day, across voice and digital channels. But increasing headcount to meet 24/7 customer support expectations isn’t sustainable for most contact centres operating on tight margins.
An always-on contact centre doesn’t mean agents working around the clock. It means using AI and automation to absorb predictable demand across inbound and outbound – from service updates and appointment changes to sales follow-ups and renewals, to payment reminders and self-serve arrangements - without needing an agent for every interaction.
The trap many leaders fall into is assuming that automation alone creates always-on. It doesn’t. Always-on is the result of clear journeys, consistent rules, and controlled escalation.
The Real Readiness Problem: Avoidable Demand
Most contact centres don’t struggle because customers contact them. They struggle because customers are contacting them more than once.
A lot of volume is created by operational gaps:
Unresolved issues driving repeat contact
Too many transfers caused by poor routing
Long handle times driven by missing context
Channels operating as seperate service silos
This is the stuff that quietly drains performance. It also explains why some AI programmes stall: they automate interactions on top of broken flows, then wonder why customer effort doesn’t fall, and agent workload doesn’t change.
If you want a pragmatic AI strategy, start by identifying where the operation is generating demand it shouldn’t have to handle.
A Practical Readiness Lens: Demand, Continuity, Control
To make readiness tangible, use this simple lens. If any one of these is weak, automation outcomes will be capped - or worse, you’ll scale the wrong things.
1) Demand: Do You Know What Should Be Automated?
AI delivers value when it absorbs predictable, repeatable demand - the structured interactions that don’t require human judgement. If you can’t clearly separate predictable from complex demand, you’ll either automate the wrong things and frustrate your customers or keep too much with agents and miss the efficiency gains.
A pragmatic starting point is mapping the top drivers and asking: which ones are genuinely structured, and which are only “simple” because we’re not seeing the full context?
2) Continuity: Does Context Move with The Customer?
Customers think in outcomes, not channels. Readiness means your operation can maintain continuity when a conversation starts in chat and moves to voice, or when an outbound reminder triggers an inbound response, or when a customer returns with a follow-up and expects you to remember what happened last time.
If context doesn’t travel, automation becomes a reset button, and resets are where handle time, repeat contact, and frustration grow.
3) Control: Can You Escalate Safely and Measure Outcomes?
Automation should never be a dead end. When complexity rises, or when there’s vulnerability, a complaint, payment risk, or compliance exposure, you need controlled escalation to a human agent with the full context carried across.
If you can’t define escalation rules and success measures beyond containment” you’re not ready to scale. You’re ready to pilot.
Where AI Fits When You’re Ready: Layers, Not Channels
A common mistake is deploying AI as separate tools by channel - a chatbot here, an AI agent there - and expecting it to add up to an always on operation. It simply adds more mini contact centres to the one you already have.
A more practical approach is to treat AI as layers across the operating model:
Decision layer (AI Agents): Interprets intent, resolves structured interactions, and prevents outbound activity from automatically creating inbound pressure through unmanaged follow-up
Asynchronous layer (chatbots and messaging): Allows customers to complete routine tasks without joining a queue, while keeping journeys connected across voice and digital
Visibility Layer (Conversation Analytics): Shows where demand originates, where conversations stall, and what drives repeat contact so you can improve routing, coaching, and automation design based on evidence rather than instinct
When these layers support end-to-end workflows, AI stops being a bolt-on and becomes a genuine performance lever.
A Quick Readiness Check: The Questions Most Teams Skip
If you’re planning AI-enabled automation this quarter, these questions are worth answering before you commit time and budget:
What proportion of our demand is truly predictable and repeatable?
Where do customers repeat themselves, get transferred, or drop out?
What's creating repeat contact and how will we remove it?
What are our escalation triggers for risk, vulnerability or complexity and do we trust them?
How will we measure success beyond containment - effort, quality, outcomes, stability?
Do inbound and outbound journeys reinforce each other, or create extra pressure?
If those answers aren’t clear yet, that’s not a blocker, it's your roadmap.
Pressure-Test Your Readiness With The Scorecard
If you want a structured way to benchmark readiness across the foundations that matter - demand, continuity, escalation, and operational fit - our scorecard is designed for exactly that. Use it to create alignment internally, prioritise improvements, and shape an automation roadmap that holds up under real-world volume, not just pilot conditions. Download the Always-On Contact Centre Readiness Scorecard here.
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