A leading Canadian insurer wanted to understand what was driving demand at its contact centre, so it could manage that demand more effectively. Davies Consulting helped it build a far more nuanced picture – then worked with the business to determine which types of interaction should be resourced, eliminated, automated or simplified.
In a highly competitive market, our client was keen to ensure its contact management strategy was as effective as possible. That meant looking at ways to make the operation more efficient – with interactions handled via the most cost-effective channel wherever possible – while improving customer satisfaction, by minimising wait times.
To help with that, it sought to understand what was driving demand on the telephony channel, so it could work out where the best opportunities lay to eliminate or automate certain interactions.
Like most large contact centres, it had traditionally relied on agents to identify what category a call came under. But this process was not accurate; it offered agents limited scope and didn’t allow them to register where a customer had more than one query in the same call.
We devised a solution combining speech analytics and value/irritant analysis. We began by conducting a manual review of a sample of calls to identify the drivers of demand. Within a couple of days, our analysts pinpointed 83 demand topics, covering sales and service. We then extrapolated this, using monthly call volumes, to give the client an initial indication of the number of calls it was receiving around each topic.
Building on that data, we then led a workshop with the client team to consider whether the demand was of value, to the business and its customers, or irritation to one or both. Based on this analysis, we jointly determined whether the business strategy for each demand topic should be to resource, eliminate, automate or simplify.
That then fed into a business change programme, but our role was not done. We then configured the client’s existing Verint speech analytics platform to create more accurate search categories. These included allowing for customers’ different language use, so that multiple search terms might be used for each category. As a result, the client can now categorise around 80% of interactions around the demand topics – allowing it to report in more granular detail on the drivers of demand, and how they have changed.
The initial exercise gave the client a far richer understanding of the drivers of demand, which it could then apply to improve contact handling, address clumsy or complex processes and support the business case for increased automation. On an ongoing basis, having more accurate demand data is enabling the client to become a customer-focused business – and to track the impact of the changes it has made to its handling strategy on demand volumes.
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