Experian is a leading global information services company providing consumer information, credit services, decision analytics and marketing services to customers. The Nottingham based contact centre deals with customer enquiries handling around 200,000 calls per month across 270 agents. Here we delve deeper into how speech analytics helped Experian achieve their retention goal. A high proportion of calls relate to the CreditExpert product, an online monthly subscription service which helps customers manage their credit report and score and also offers identity and fraud protection. The contact centre strategy is to provide best possible service which in turn directly correlates to customer retention, and this is all important. Therefore, understanding why customers initially signed up for the service and making sure these benefits are provided through their membership package delivers enormous value to the company. Prior to implementing speech analytics, business insight was derived from the telephony and IVR systems as well as anecdotal information shared by agents. It was evident to Experian that better technology could deliver these results faster and more effectively. Chris Barkataki, Strategy Manager at Experian comments: “When we first started looking at Speech Analytics our retentions goal was the obvious choice for achieving a return on investment but interestingly the proof of concept uncovered other quick wins such as addressing non-talk time on calls. It made sense for us to implement analytics immediately so that better decisions could be made based on what our customers and employees were saying.’Working closely with Business Systems and through a Proof of Concept, Nexidia Speech Analytics was identified as the appropriate solution. Integral to the implementation was ensuring the technology was correctly embedded into the culture of the organisation. According to Lee Hancock, Operations Analyst at Experian “The mentoring programme delivered by Business Systems was really beneficial, providing onsite support on a regular basis and it was great to have someone who knew the system that we could bounce ideas off. The provision of an analytical framework was also useful in terms of getting our people to really understand how they approach a problem, think through it and drive positive change.” View the full case study here or contact us to find out more on Speech Analytics. Written by: Business Systems UK
Blog 22 July, 2026 The Cost of Attrition: Why Workforce Engagement Management is a Self-Funding Strategy Contact centre attrition remains one of the most expensive challenges facing customer support leaders. CX Today reports annual turnover rates of 35-45% remain common across the industry, with each departure costing between £10,000 and £15,000 in recruitment, onboarding and lost productivity. For a 200-seat operation, that equates to roughly £700,000-£1.35 million in annual attrition costs
Blog 30 April, 2026 Customer Experience Tools: How to Choose (and Implement) the Right CX Platform for Your Business Choosing the right customer experience platform is a major decision for many businesses. The platform you choose shapes how customers interact with your business across every channel, determines what insights you can extract from those customer interactions, and influences whether or not your teams can deliver consistently excellent service. Yet many organisations approach this decision
Blog 16 April, 2026 Conversational AI in UK Contact Centres: Moving Beyond Basic Chatbots Many contact centres in the UK have implemented chatbot technology in some form or another, but with varying degrees of success. Recent industry research reveals that nearly 70% of customers become frustrated with chatbots and prefer speaking to human agents, and abandonment rates for basic chatbot interactions continue to remain stubbornly high. The problem isn’t
Blog 10 April, 2026 Proactive Customer Service: How Contact Centres Can Use Proactive AI to Anticipate Customer Needs The traditional model of customer service is almost entirely reactive: a customer discovers a problem, contacts your organisation, and waits for a solution. This approach places the burden squarely on the customer, requiring them to identify issues, navigate your contact channels, and often endure multiple interactions before their problem is solved. Proactive customer service powered
Blog 29 January, 2026 Microsoft Teams Recording Without the Risk: A Practical Guide for Regulated Organisations Microsoft Teams has become the backbone of collaboration across financial services, insurance, the public sector and other regulated industries. Trading conversations, client discussions, internal decisions and approvals are now happening daily across voice, video, chat and shared files. That shift brings opportunity, but it also introduces risk. For organisations operating under regulations such as FCA,
Blog 5 December, 2025 The clock is ticking: Why end-of-life recording systems are a critical compliance risk Outdated recording technology isn’t just an inconvenience, it’s a ticking time bomb for regulated firms. For financial services and other heavily regulated industries, end-of-life (EoL) voice recording systems can create dangerous blind spots. When vendors withdraw support, these unsupported platforms become vulnerable, exposing your firm to major compliance penalties under frameworks like MiFID II, FCA,
Blog 20 November, 2025 Proactive AI vs Reactive AI: Understanding the Difference Artificial intelligence is changing the way organisations across the UK engage with customers, but all AI solutions aren’t created equal. Many still rely on reactive models that respond only once a customer makes contact. Proactive AI takes a more advanced approach, identifying needs and acting before the customer does. Understanding the key differences between proactive
Blog 20 November, 2025 5 Ways Proactive AI Can Reduce Manual Workload in Contact Centres Contact centres today face a familiar challenge: maintaining exceptional service while managing high volumes, rising costs, and limited resources. Agents are spending valuable time on repetitive, manual work instead of focusing on complex, high-value interactions that truly build customer loyalty. This is where Proactive AI makes a measurable difference. By combining automation with intelligence, it