The Retail CX Problem

Retail contact centres are caught in a difficult position. According to the ContactBabel 2025 UK Retail Customer Experience Report, over 28% of inbound calls to UK retail contact centres come from customers who tried and failed to resolve their issue online. That is well above the 21% industry average. Customers are not calling because they want to; they are calling because the digital journey broke.

The investment is there. Retail has the highest web chat usage of any sector. 60% of retailers are actively ramping up AI investment. But investment alone is not delivering outcomes. Retail also has some of the lowest chatbot effectiveness scores of any sector, which points to a structural problem: technology deployed without a clear understanding of the customer journey it is meant to serve.

Underneath this sits an omnichannel fragmentation problem that most retailers recognise but few have solved. The Puzzel State of Contact Centres 2026 report found that only 3% of contact centres operate on a single unified platform, with the average organisation managing 3.9 different contact centre technologies. When channels do not share context, customers repeat themselves. When customers repeat themselves, loyalty erodes.

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This is for you if:

  Your contact centre is absorbing high volumes of calls from customers who could not self-serve online

  You are piloting or planning AI but lack a clear framework for escalation and guardrails

  Your web, phone, chat, and in-store channels do not share a unified customer view

   Loyalty metrics are under pressure and you are not confident your CX is a differentiator

   You need to handle card payments securely across multiple contact channels without disrupting the customer experience

 

The Business Case for AI in Retail Contact Centres

Gartner projects that conversational AI will reduce global contact centre labour costs by $80 billion by 2026. The efficiency opportunity is real, and the competitive pressure to act is building. According to Puzzel's State of Contact Centres 2026 report, 83% of CX leaders say AI-powered self-service is effective, with 39% reporting faster resolution times and 30% seeing measurable improvements in cost per contact, agent productivity, or customer satisfaction.

But the same data reveals a significant readiness gap. While 85% of organisations say they are prepared to implement AI, only 34% feel fully prepared to execute at scale. The most common barriers are lack of internal AI expertise, data privacy concerns, and integration complexity. This is where poorly scoped deployments happen, and where brand trust gets damaged fastest.

The distinction that matters: retailers deploying AI to cut cost and retailers deploying AI to protect loyalty are making fundamentally different decisions. Cost-cutting deployments optimise for deflection. Loyalty-protection deployments optimise for resolution, for keeping the right interactions human, and for ensuring every automated touchpoint reflects the brand standard customers expect. We design for the second outcome.

The CCMA Contact Centre Technology Report 2026 puts it plainly: AI's highest returns come from agent augmentation and agentic workflows with clear guardrails. The retailers seeing real ROI are not those who deployed fastest. They are those who deployed most deliberately.

Technology Investment (1)
it’s what we do best

Client reviews

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Justine Long
Head of Operations,
CA Auto Finance

“Saved us from an expensive mistake”

We had vendors trying to sell us something we didn’t understand. Mark was different - he was completely impartial and focused on finding what we actually needed. He took all the techinical jargon and made it simple to understand the real business impact.

More importantly, he caught things we would have completely missed. On paper, everything looked similar, but Mark knew what looked similar wasn’t actually similar. The expertise probably saved us from making a very expensive mistake.

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Ben Hallatt
COO, Ashtons Law

“Made complex decisions manageable”

We thought we just needed to upgrade our phone system. Mark helped us see we were thinking way too small. He walked us through what modern platforms can actually do, translated all the technical jargon into real business value, and completely transformed how we interact with clients.

What really stood out was how he made complex decisions feel manageable, instead of pushing a solution, he helped us understand what was actually possible - then stuck around to make sure we got real value from it. Without his expertise, we would have upgraded to another basic phone system and missed this huge opportunity.

What we help Retail teams achieve

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 Consistent CX across every channel

Customers expect to move between your website, app, phone line, and in-store without repeating themselves. We help you build a unified customer view that travels with the interaction, so agents always have full context and no customer starts from zero.

Consistent context means faster resolution and fewer escalations driven by frustration rather than complexity.

 Reduced inbound volume from failed self-service

The goal is not to deflect contacts. It is to resolve them. We design AI-assisted self-service that addresses the root causes of failed digital journeys, reducing the 28% of calls that should never have needed to reach an agent.

When self-service works properly, inbound volume falls and the contacts that do reach agents are genuinely complex ones worth the handling time.

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Loyalty-protecting escalation protocols

High-value customer interactions should reach a human, quickly, with full context already preserved. We build escalation triggers into every AI deployment from the outset: defined thresholds for sentiment, complexity, and complaint type that hand off cleanly to the right agent.

Guardrails are not a bolt-on. They are the architecture.

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Secure, compliant contract handling

Retail contact centres handle card payment data across more channels than almost any other sector: voice, IVR, web chat, and digital.

We assess your payment data flows, identify compliance gaps against PCI DSS v4.0.1, and implement controls that protect cardholder data without adding friction to the customer journey.

Use cases

CX and AI use cases for Retail

Customer service + returns

Handle the highest-volume, lowest-complexity contacts automatically, with clean handoffs for anything that needs a human.

Talk To An Expert

  • > AI triage and web chat with 24/7 coverage

  • > Order status, returns, and refund handling without agent involvement

  • > Compliant detection with immediate escalation to a trained agent

  • > Automated post-contact summaries and CRM logging 

  • > Consistent response quality regardless of channel or time of day

Omnichannel orchestration

Give every agent a complete picture of the customer, regardless of where the conversation started.

Talk To An Expert

  • > Unified customer timeline across web, app, phone and in-store

  • > Context-aware routing so the right agent receives the right contact

  • > No repeated authentication or repeated problem description

  • > Real-time agent assist with relevant customer history and next-best-action prompts

Loyalty + retention

Identify at-risk customers before they leave, and give agents the tools to retain them.

Talk To An Expert

  • > AI sentiment analysis flags dissatisfaction signals during live interactions

  • > Real-time retention prompts for agents handling high-value or at-risk customers

  • > Post-interaction analysis to identify recurring friction themes across the contact base

  • > Proactive outreach triggers based on behavioural and interaction data

Operational efficiency

Reduce the admin burden on agents and give team leads the visibility they need.

Talk To An Expert

  • > Automated call and chat summaries after every interaction

  • > AI-assisted QA across 100% of contacts, not just sampled calls

  • > Better reporting on resolution quality, sentiment trends, and channel performance

  • > Reduced after-call work so agents spend more time on customers

Use case

Customer service + returns

View use casearrow-image

Customer service + returns

Handle the highest-volume, lowest-complexity contacts automatically, with clean handoffs for anything that needs a human.

Talk To An Expert

  • > AI triage and web chat with 24/7 coverage

  • > Order status, returns, and refund handling without agent involvement

  • > Compliant detection with immediate escalation to a trained agent

  • > Automated post-contact summaries and CRM logging 

  • > Consistent response quality regardless of channel or time of day

Use case

Omnichannel orchestration

View use casearrow-image

Omnichannel orchestration

Give every agent a complete picture of the customer, regardless of where the conversation started.

Talk To An Expert

  • > Unified customer timeline across web, app, phone and in-store

  • > Context-aware routing so the right agent receives the right contact

  • > No repeated authentication or repeated problem description

  • > Real-time agent assist with relevant customer history and next-best-action prompts

Use case

Loyalty + retention

View use casearrow-image

Loyalty + retention

Identify at-risk customers before they leave, and give agents the tools to retain them.

Talk To An Expert

  • > AI sentiment analysis flags dissatisfaction signals during live interactions

  • > Real-time retention prompts for agents handling high-value or at-risk customers

  • > Post-interaction analysis to identify recurring friction themes across the contact base

  • > Proactive outreach triggers based on behavioural and interaction data

Use case

Operational efficiency

View use casearrow-image

Operational efficiency

Reduce the admin burden on agents and give team leads the visibility they need.

Talk To An Expert

  • > Automated call and chat summaries after every interaction

  • > AI-assisted QA across 100% of contacts, not just sampled calls

  • > Better reporting on resolution quality, sentiment trends, and channel performance

  • > Reduced after-call work so agents spend more time on customers

Want to find the fastest ROI in your contact centre?

We’ll review your current journey and highlight practical opportunities across customer experience, AI and platform consolidation - connected to the systems you already run. 

AI Agents, built around Retail workflows

Helpful automation, with clear boundaries.

We help you design AI agents that handle specific retail processes without increasing risk to your brand or your customers. That means defined capabilities, documented escalation paths, and compliant data handling built in from the start, not retrofitted after a problem surfaces.

 

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Enquiry Agent

Captures the reason for contact, order details, and urgency, then routes correctly across channels.

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Service Agent

Handles routine requests, including order status, returns, and account updates, then escalates exceptions cleanly.

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Retention Agent

Detects dissatisfaction signals in real time and surfaces retention prompts for agents handling at-risk customers.

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Intelligence Agent

Tags interaction themes, flags emerging issues across the contact base, and surfaces coaching opportunities for team leads.

Always with clear guardrails: what the agent can do, what requires human review, and how customer data is handled. Escalation is not an afterthought. It is designed in before anything goes live.

 

What 'good' looks like

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Faster response times across customer channels

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Less manual admin after calls and meetings

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Cleaner CRM data without constant policing

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Better visibility for leaders and team managers

A deployment approach that reduces risk

CX and AI Advisory

Before any technology is selected, we map your customer journey, identify the highest-friction touchpoints, and define what good outcomes look like for your specific retail context.

Find out more

Technology Selection

We help you choose the right tool for each use case: a chatbot for high-volume, low-complexity contacts, or an AI agent for multi-turn journeys that require context and judgement. Vendor-neutral, always.

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Phased Rollout

We start with a controlled pilot on a single high-volume, low-complexity use case, validating escalation triggers and resolution quality before scaling across channels.

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Ongoing Monitoring and Auditing

AI models drift. Brand standards do not. We establish a monitoring cadence that keeps your AI outputs aligned with your service standards, catching issues before customers do.

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Trusted by leading teams, delivered with leading platforms

Our Customers

  • alcumus
  • AVFC
  • Ashton
  • CA
  • PKF-Logo
  • severn
  • nottingham-forest.0594f24a

Our Technology Partners

  • zoom
  • ring central
  • goto
  • dialpad
  • nice
  • teams

Our Integrations

  • HubSpot
  • Salesforce Logo
  • teams
  • Dynamics 365
  • WhatsApp
  • ServiceNow
  • jira
  • zendesk

Our Clients

CA
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alcumus-logo-color
alcumus-logo-color

Put the team behind 100+ communications
transformations to work for you

True specialists

We decode communication tech daily. While platforms push monthly AI releases, we're already stress-testing real-world outcomes to ensure you get 100% value from these capabilities.

Battle-tested experience

Elite technical credentials matter. But what sets us apart? We'll challenge assumptions and flag risks before they become problems. We map technology to business processes, helping you redesign workflows to take advantage of modern capabilities.

Long-view partnership

Our clients stay 6+ years because we evolve with their needs. No quick fixes – we're architects of lasting transformation.

Frequently asked questions

Why are so many retail AI deployments failing to deliver results?

Most retail AI deployments fail because they are scoped for cost reduction rather than customer resolution. Retail also has the highest web chat usage of any sector but the lowest chatbot effectiveness scores, pointing to a structural problem: technology deployed without a clear understanding of the customer journey it is meant to serve.

 

What is the biggest CX challenge for UK retail contact centres right now?

According to ContactBabel's 2025 UK Retail CX Report, over 28% of inbound calls to UK retail contact centres come from customers who failed to self-serve online, well above the 21% industry average. Fixing the root causes of failed self-service is the highest-impact opportunity available to most retail operations teams.

What is the difference between a chatbot and an AI agent for retail?

A chatbot handles defined, rule-based interactions: order status, FAQs, basic routing. An AI agent handles multi-turn, context-dependent conversations and can take actions within systems. The right choice depends on the complexity of the interaction, the channel, and the escalation requirements of each use case.

 

 

How do you protect customer loyalty when deploying AI in a retail contact centre?

Loyalty protection requires escalation protocols designed in from the start, not added later. That means defined sentiment and complexity thresholds that trigger a clean handoff to a human agent, full context preserved across channels, and AI outputs that consistently reflect your brand standard, monitored on an ongoing basis.

 

Does a retail contact centre need to be PCI DSS compliant?

If your contact centre handles card payment data across any channel, voice, IVR, web chat, or digital, PCI DSS v4.0.1 compliance is the expected standard. Retail handles payment data across more touchpoints than almost any other sector, making multi-channel compliance assessment a priority for most retail operations teams.

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