4th July 2023
This year’s LISTEN UK event was bigger and better than ever, with plenty of food for thought being shared among the CallMiner community. Among the panel of insightful speakers was Davies’ own Director of Consulting Services, Sean Keane, and Vice President of Client Management, Michael Anderson. The experts delivered a thought-provoking keynote entitled “How to turbo-charge your CX using Interaction Analytics”. Here, we explore the key takeaways from it.
When it comes to offering a great customer experience (CX), the role of analytics is key to moving our services forward. But what many organisations fail to recognise when conducting analysis on their CX strategy, is that a return on investment won’t come from analytics alone. But rather, from using the insights your analysis provides to be more effective, rather than focusing on what will be easier and more efficient to implement.
In Sean and Michael’s keynote, they shared four key points in your customer services journey where you can leverage data and interaction analytics to create a smoother experience. Let’s discuss these in deeper detail.
When done correctly, a customer service strategy should help an organisation to do at least one of four things: make money, save money, improve experience, and stay compliant.
During the keynote, the concept of building good CX via a digital-first common-sense journey was introduced. The speakers recognised that most businesses are leveraging the power of a digital-first approach. But they acknowledged that bringing in an intelligent human touch and using closed-loop insights can help to drive action that is productive and effective, helping to power products, services, and customer development for businesses.
By leveraging the power of interaction analytics and data, there are four areas within the common-sense customer journey that can be significantly improved. These are:
Something many businessowners and leaders do is tend to focus solely on the good, and what’s going right, and neglecting to look deeper at what’s gone wrong and what could be improved. And when we think about curating and unlocking a better CX strategy, it’s imperative that organisations are building a customer-centric culture and strategy that seeks to understand failure demand—that is, what went wrong for them to get in touch with their company rather than only focusing on value demand. And interaction analytics and data can be used to illuminate these crucial pieces of information for you.
Through considering the demand that’s being caused by unnecessary failure, and identifying what those failures are, you can work to eradicate them and create a better CX strategy that puts the customer at the heart of everything you do. Which customer service is a great opportunity to demonstrate the remarkable service you do have to offer, lower rates of customer contact are far more telling as they indicate a smoother, more seamless customer journey.
This is also beneficial for organisations as when your rates of customer contact are minimised, you can also reduce your spend on customer service agents and technology catering for demand that was caused by things going wrong.
Understanding the intent behind customer contact is imperative to designing a CX that satisfies your customer base and can help you to understand the efficiency and effectiveness of your wider business processes. Conducting regular deep dives into your CX can demonstrate what’s unclear, incorrect, or needs improvements and data and analytics can play a large role in deciphering these through collection and analysis of recordings and logs of past customer interactions.
Utilising the power of Machine Learning, data and interaction analytics can analyse your call recordings and written customer service transcripts at scale. Once collected, it can then work to ascertain how much of this content is value demand, and how much of it is failure demand.
The breakdown of this data is produced at a significantly more efficient rate than any human could, and provides scope to resolve the things that are going wrong and generating this unnecessary demand. This is beneficial for both organisation and customer, with a lesser need for customer service support going forwards, meaning less CX spend for businesses and less issues for the customer.
Self-service customer service functions are continually growing in popularity, with many business websites hosting their own digital resolution functions to help deal with customer queries. However, among these, customers are regularly being displayed a pre-determined list of reasons why they might be getting in touch. And often enough, this is a very limiting list of generic areas of the business such as Sales, Delivery, and Technical Support.
The way interaction analytics and data aim to solve this issue is to offer an intelligent service. The technology utilises cues from customer reasoning about their intent for contacting, whether that’s speech-led or something that’s been typed into a chat function—and then it conducts all the internal back-end complexities to figure out what it is that the customer needs.
Data and interaction analytics can help you by listening to the call recordings that are currently coming into your customer service department and assessing the data you have in these recordings. Once you understand that, it’s a fast-track solution to creating a self-service function that routes the customer intelligently to the correct person or department for your query.
As well as improving self-service functions, data and interaction analytics can be used to determine what customers want during a query via the use of bots. Bots are typically used to help complete end-to-end transactions. And do so by absorbing data inputs and lending support through the customer journey, going on to handle the complexities within the internal processes and complete the transaction.
Additionally, data and interaction analytics can help businesses make improvements by looking at incomplete customer journeys where bots could not complete the query. By collecting insights that show where bots failed, the gaps in an organisation’s CX journey and wider processes are highlighted. This means it’s better positioned to optimise its bot functions, so it can assist new customers and ensure resolution moving forwards.
And the potential for data and interaction analytics doesn’t end there. The data you gather through bots and other self-service functions can also help you to design segmented routing patterns for e.g., circumstances that need to be handled with sensitivity and with a responsibility of care—something the FCA’s Consumer Duty plans lays out as a requirement for all businesses in the financial services sector. For example, by harvesting buzzwords or capturing information that the technology can pick up and instantly know to direct the customer to specially trained advisors to handle their case.
Good customer service looks different to everybody. And while we find ourselves in an evolving digital world, it’s important that businesses don’t neglect those who have non-digital preferences. Organisations must acknowledge that there’s no one-size-fits-all approach, and that providing multiple lines of contact and communication channels is crucial, particularly to provide a service that welcomes inclusivity and accessibility.
Need help designing your CX strategy, or wish to talk more about interaction analytics? Get in touch with our team today and find out how we can help transform your CX strategy.
Director of Consulting Services
Vice President – Client Solutions
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