How to reduce costs while improving your customer experience with efficient and effective self-service technology.
With 14,000 employees and nearly 900 stores, this company is one of the UK's leading health and beauty retailers - and growing fast. It has pharmacies with consultation rooms in over 220 stores, as well as an additional 19 containing nurse clinics. In 2011, it embarked on a $70 million Big Data project as part of a plan to build new capabilities in analytics and machine learning. Suffering from high waiting times on voice calls, the brand discovered that around third of the queries into agents were for issues such as delivery updates and reward card information, which could be easily dealt with via self-service. Keen to ensure that automating these queries wouldn’t harm the customer experience, the retailer implemented a new NextGen IVR system supported by NLP, ensuring that for inbound queries the automated system can quickly identify the intent of the call and if it is one better dealt with by an agent it will seamlessly transfer the query.
The company receives thousands of customer queries every day, which often led to call centre congestion and low customer satisfaction ratings. It recognised that many calls were simple queries they could easily deal with using conversational interactive voice response (IVR) technology.
The challenge was to implement automation and AI-powered technology while still delivering a personalised experience. This required data from various sources and in different formats to be integrated in a central, accessible location. Only with this level of data orchestration could the system usefully answer an array of basic customer queries.
To tackle its call centre conundrum, the company was also searching for a solution that leveraged natural language processing (NLP) functionality, with the target of achieving a 25%+ reduction in calls to agents.
Engage Hub’s conversational IVR solution gives customers a self-service option, delivering greater flexibility and efficiency. Utilising the latest NLP functionality, call intention is detected in real time, and the caller is quickly routed to the correct resolution point.
The results have been overwhelmingly positive. Providing 24/7 immediate, personal answers has boosted customer satisfaction and relieved call centre congestion. The virtual assistant now handles 66% of common queries, which has enabled to company to reduce call centre staff by 25%.
Agents are now free to handle the complex issues, which has also contributed to the rise in customer satisfaction levels.
The solution is flexible so it can develop as the company and available technology evolves. For example, it could integrate with the likes of Google Home and Amazon Echo to facilitate online ordering. And because the NLP processing is channel agnostic, they can roll out it out over all their communication channels as need.