Using data analytics to deliver more personalised customer service

Consider unique behaviours

Aphrodite Brinsmead, senior analyst for customer engagement at analyst Ovum, says personalisation and analytics are intertwined and when developing a multi-channel strategy organisations need to consider the unique traits and behaviours of their customers.

“They should be reviewing existing behaviours, use of different channels across the web and which questions customers are commonly asking in different channels. Understanding trends is essential before deciding how to add new channels or connect data,” says Brinsmead. 

“Organisations should then focus on reducing customer effort and improving first-contact resolution rates. They should try to retain context as customers switch channels, use analytics and push relevant data to both customers and agents,” she says.

Finding the preferential times and ways to engage with customers is key to personalisation, and data analytics can unlock this intelligence and save money. Gartner says contextually relevant knowledge needs to be available from any channel, including website, mobile app or during interactions with a customer engagement centre.

According to Gartner, delivery of contextual knowledge to an employee reduces a provider’s time to answer, which raises competency and satisfaction. It also makes sense financially, as when a proper knowledge management discipline is in place, firms can reduce customer support costs by 25% or more.

“Look at ways to connect the content with customer data so customers receive personalised information based on their preferences. By having information on typical customer journeys and support questions, the organisation can predict what information a customer needs,” says Brinsmead.

Knowing your customer as an individual and making their journey as smooth as possible is key to a positive experience, says Jamie Turner, chief technology officer at address management firm Postcode Anywhere. He believes personalised customer service is essential for survival in the digital economy.

“Service is like insurance – when you need it, you really need it. It shouldn’t be taxing or complex, it should be frictionless and painless. Those companies that get it will be here for the long term. There’s very little loyalty online, so you need to fight to keep your customers. Too many organisations still focus on acquiring customers rather than keeping the ones it has happy,” says Turner.

Investing in analytics

However, it is not easy to achieve effective personalisation of customer service or experience without investing in analytics.

“It’s what everyone wants and it’s hard to do properly. We all like the pub that knows ‘your usual’ and the corner shop that knows what you've come in for before you say a word. That's personal, but it's very hard to scale,” says Turner.

According to Turner, good analytics can help an organisation become proactive rather than reactive to customers’ expectations. 

“It’s something very important to us, and we've built a bunch of technologies to help us understand and predict what our customers ‘feel’. That way we can hopefully pre-empt things and be ahead of the customer,” he says.

He believes big data has a role to play in evolving a smarter service which acknowledges customers’ individual likes and dislikes.

“Big data is absolutely the key. It means different things to different people, but for me big data is more an approach. It’s really about collecting as much data as you can, then using technology like machine learning to sift out the important bits from the noise. One of the challenges is being able to react, or ideally act, in real time,” says Turner.

He says it is no longer enough to rely on insights gained through big batch processes of data which deliver “insights” a few days after they would have been useful.

“People offer the best service because they unwittingly process loads of cues from behaviours and make instant judgements on how to behave. Mirroring that in technology will help provide truly natural and supportive personalisation that’s also useful to the customer,” says Turner.

Don’t be intrusive

However, with big data comes big responsibilities. Ovum’s Brinsmead says best practice means using analytics in a non-intrusive fashion. 

“Be wary of using customer data to push offers and sales, or risk losing the trust of customers,” she says.

According to Brinsmead, organisations need to use data wisely and creatively by integrating knowledge across websites, social feeds, community-driven information, mobile applications and automated chat.

“Customers don’t want to have to leave a mobile application to then go to a community or chat to get technical assistance,” she adds.

Be wary of using customer data to push offers and sales, or risk losing the trust of customers

It is also important to understand that customer choice about how they want to interact can change at any stage of the journey and this should be easily facilitated.

“Live support will always be required for questions containing personal, complex or urgent requests. Organisations should realise when an interaction needs go to a live agent and allow the customer to quickly connect. Organisations should push context about the customer’s web history or previous questions to an agent in advance,” says Brinsmead.

Brian Manusama, a research director at Gartner, says organisations that use big data for customer service will increase customer satisfaction by providing rich, analytical, personalised customer services. As a result, the organisation can benefit from increased revenue through predictive analysis. Avoiding problems before they escalate is the most sensible path to reducing support costs and retaining customers.

“Through analysis, organisations can get a better understanding of the service issues customers are experiencing, and take action to avoid problems and resolve issues before customers are reaching out to customer service,” says Manusama.