Customer service might once have been synonymous with a telephone call centre, but these days, it can be so much more. Users have a lot of touchpoints with your organisation, all of which constitute a ’voice’ for the customer – by interacting with your different platforms and websites, they are leaving data about their experience that can help you interpret their attitudes and needs.
Listening to these customer voices and taking action to meet their needs is vital to the development of the company – they inform how you interact with them, the level of service you offer, the investments and staffing levels you provide and the technology and systems you adopt.
Perhaps even more important is how customers perceive your ‘customer ethos’ – listening to their needs and acting accordingly encourages customers to believe that you care about them and build experiences around their needs.
This means that measuring how your customers perceive you, how much you are appreciated compared to the competition, is also vital. This is usually achieved through the mechanism of Net Promoter Score (NPS). Although a useful tool for measuring customer loyalty, there are some serious drawbacks with this method.
The first is the generally small sample size used, which is often only around for 10 percent of the entire customer base. Even then, very few of these people will actually respond and when they do, different scores will often be given for the customer’s different touchpoints on their journey.
Overcoming these drawbacks often requires expert help. As an example, a particular telecoms brand needed help to interpret its NPS. It wanted to gain more insight into how customers felt about them, in order to optimize the customer experience. NTT DATA UK helped define the areas of focus as well as evaluate weightings and reporting mechanisms.
However, while improvements were made, the emerging picture was incomplete, so it was supplemented with a wider KPI dashboard. This was reported monthly to a digital leadership team, providing a broader view of customer interactions and metrics across the digital platform, resulting in a richer suite of core customer metrics.
This type of data can feed into predictive analytics solutions, allowing you to anticipate what customers will do next and helping you make the right response at the right time. With this knowledge, you can ensure customers get a seamless, hyper-personalised experience, a goal that has become one of the most urgent priorities for many organisations.
These days, best practice should include intelligent analytics based predictive modelling. One of the most effective methods is that of behaviour based lookalikes. This technique gives marketers the ability to enhance and improve the usefulness of small samples by capturing data on the actions of the group being analysed.
Instead of simply targeting people by their characteristics of age, sex or social profile, the technique captures where people go. For example, starting with a core customer audience, we can map where they go and then map other potential customers who go to the same places. These people don’t look like the core audience but they do behave like them. Data on behaviour helps us get to know our existing and potential customers better, informing how we design the customer experience journey.
Essentially, customer loyalty and preferences can be boiled down into hard metrics. These can be used to provide a richer customer experience that helps support the brand. This is sound business practice, as it will always be more cost-effective to retain existing customers than to find new ones.
To find out more please contact Michele Biron, Head of Customer Experience, NTT DATA UK Michele.Biron@nttdata.com.