Markerstudy Distribution provides millions of insurance policies in the United Kingdom across a number of brands. The organisation has used analytics for many years to help automate quality assurance processes and to help ensure that vulnerable customers receive appropriate levels of care. As practices became harmonised across the organisation, Markerstudy recognised a greater opportunity to enhance it’s service for vulnerable customers and to support a wider improvement in customer experience.
01 Before
Differing vulnerable customer practices
Markerstudy Distribution operates along several brands and lines of business. NiCE worked with a part of Markerstudy Distribution, which until recently was managed under four distinct organisational umbrellas. As a result, there were four distinct quality assurance departments, each with its own manager and own team members. Each used a different process to identify calls involving a vulnerable customer, a category which encompasses a variety of needs ranging from being hard of hearing to suffering a bereavement. And each of those processes was fundamentally manual. “We could tell from call reviews if an agent had correctly identified and adapted to a vulnerability, but not always if the agent had correctly categorised them,” said David Harrison, Associate Director, Customer Insights and Operations at Markerstudy Distribution.
02 Desire to change
A unifying window of opportunity
As Markerstudy Distribution began merging those previously distinct four groups, the organisation recognised a key opportunity to make several process improvements. The business issued wide-ranging RFPs to instill consistentdata-driven approaches across several disciplines, and leadership saw an opportunity to transform quality assurance, capture more actionable insights, and improve support for vulnerable customers. “We saw an opportunity to gain insights that weren’t possible with our old systems - unless someone spent time manually building and filtering spreadsheets in different ways,” Harrison said.
03 NiCE solution
Sentiment and vulnerability insights in real-time with Enlighten AI
With expanded use of Interaction Analytics, Quality Central, and the introduction of Enlighten AI, the organisation was able to build upon existing experience and familiarity with NiCE solutions. “It was an easy decision for us when the opportunity for voice analytics came up because we already knew the system and how it had changed our quality processes,” Harrison said. “We were really impressed, and NiCE made it incredibly easy.”
Markerstudy Distribution uses Interaction Analytics with Enlighten AI to automate most quality assurance checks, which in turn speeds up identification and implementation of process improvements. With real-time analysis and scoring of agent soft skill behaviours, customer sentiment has improved and agents are better trained to handle sensitive calls. “NiCE Enlighten AI helps pinpoint calls and adapt processes to better support our agents and customers,” Harrison said.
Surveys collected during the pilot of Enlighten AI revealed an unanticipated 10% rise in voice-of-the-customer scores. With that insight in hand, the program was rapidly expanded, and Markerstudy Distribution now monitors approximately 100,000 calls a month in real-time, ensuring that vulnerable customers, as defined by the UK Financial Conduct Authority, receive prompt support.
The organisation can better train agents on a wide variety of difficult scenarios, such as a bereavement, and build teams of specialists who score best in those encounters to give callers the best possible experience.
“Overall our customers will experience more support and empathy, because they’ll be dealing with a smaller population of higher-skilled people,” Harrison said.
NiCE specialists, including Value Realization Services, took responsibility for building initial voice queries and now routinely advise internal experts and identify out-of-the-box use cases for Enlighten AI. “We probably wouldn’t be where we are today without that support,” Harrison said.“Today we’re doing robust testing before we launch any query so that it’s reliable and consistent, which it has been in how it measures people in the automated QA.”
Harrison said that the Enlighten AI work has helped develop a wide range of process improvements. “We’ve delivered between 450 and 500 consumer improvements as part of this journey.”
04 Results
Consistent, clear understanding
Markerstudy Distribution has transformed its customer interactions and processes with Enlighten AI solutions. Enlighten AI now classifies vulnerabilities consistently and accurately. Agent training is more nuanced around sensitive issues, and in turn, the workforce is more skilled and confident. “This allows us to do deeper dives, improve call routing, and provide appropriate support,” Harrison said.
There are also measurable business benefits. One real-time retention tool designed around callers whose policies have just expired is expected to generate £160,000 annual savings for the company. And when complaints are received, surveys show that trust scores post-complaint are up 50% since the Enlighten AI implementation.
The hundreds of process improvements spurred on by the company’s wider consumer experience efforts have generated an estimated £2 million in revenue and savings. “Overall, it’s giving us more of a culture of transparency and accountability,” Harrison said. “Our agents are more interested in why the customer is on the phone, not just on doing ten required things each call. The AI does the heavy lifting, and that makes the job more enjoyable and our agents more engaged.”
05 Future
Wider scope for Enlighten AI-assisted interactions
Markerstudy Distribution plans to use Enlighten AI call insights for chat and other communication channels. This will further enhance its ability to identify and support vulnerable customers across the business, ensuring a consistent and high-quality experience across all touchpoints.
To peer organisations still evaluating their options, Bradley Fitzakerley advises prompt and decisive action. “Be bold about it. You have to adapt your model to maximise the benefits of new technology,” he said. “That’s what we’re doing: we’re going to learn more about our business to help customers.”
