How to Turn Customer Experience Data into Actions
Most organizations have plenty of data. But without context, it’s meaningless. Find out how to turn your customer experience data into actions that make a difference in the organization.
Collecting customer feedback is just the start of a CX program – you need to be able to take that data and turn it into improvements and actions that make a real difference in the business.
Here are a few things you need to get right in order to go from big data to useful data.
Empower and Incentivize People
CX data is nothing without the people delivering the experience to the customer. For example, say you find that by reducing call resolution time (CRT) in your call center, you can cut customer churn by 5% – the CX team isn’t going to be on the phone with customers, so you need to bring your call center team on the journey with you.
Transparency is key here – by giving people throughout the business access to the metrics that matter to them, you can show them how they impact the customer experience. That way, when you need to call on them, they’ll understand how the initiative will benefit them.
To go back to our call center example, you could work with managers in the call center to incentivize staff to reduce complaint handling times. Then they could track how the team is performing and see their impact on churn, demonstrating the effect of the initiative in real-time.
A great example of empowering others to help deliver on CX improvements is Allianz – the global insurer’s corporate and specialty division, AGCS, runs a CX program across 22 countries with a core CX team of just 3 people.
The AGCS team has been able to make huge improvements by building a network of ‘champions’ across the business. So when they identify potential improvements to the customer experience, they can work closely with the teams and business units affected to drive change from within.
Centralize All Your Feedback
The customer experience takes place across a range of touchpoints, whether it’s online, in-store, or on the phone.
To truly understand how each one is contributing to the overall experience, you need to be able to see them all in one place so you can identify exactly where along the journey you need to make improvements.
Having all your customer touchpoints on the same platform will help you to get a holistic view of the customer experience.
Combine Your Customer Metrics With Key Operational Data
Having all your customer feedback in one place is a great start – but how do you know how the customer experience is impacting your key operational metrics, like revenue, sales, or average customer spend?
Bringing together customer data alongside your operational data allows you to do exactly that. You can analyze data together to see how they’re related and how improvements in the customer experience will impact your key operational metrics.
It means you can identify the actions with the biggest impact, so you can focus your efforts and start to prove the ROI of your CX program to the organization’s leadership.
Get The Right Analytics Tools
Data scientists are a rare commodity, and few organizations have the luxury of having a team of them ready and waiting to dig into your customer experience data.
This is where technology is making massive strides and supplying everyone with the tools they need to make sense of large and complex datasets.
Here are a few useful statistical tests that will help you make more sense of your customer data:
- Key driver analysis – this test investigates the relationship between a number of key drivers and an outcome. So if your outcome is NPS, for example, it would analyze all your variables to identify which ones have a statistically significant effect on the outcome and, most importantly, how they’re currently performing. It means you can quickly identify the variables that have a big impact that may not be performing as well, helping you decide where to focus your priorities
- Text analysis – automatically analyzes and sorts open text feedback. The best tools apply sentiment analysis as well as grouping comments into topics so you can easily see areas that are getting a more positive or negative response, and track trends over time
- Relate – a statistical test which shows whether there’s a statistically significant link between two metrics, for example, your call center waiting time and your NPS score
- Multivariate regressions – a more complicated statistical test that takes a number of variables and shows the impact of each one on your key metric. So you could take hundreds of different variables and run a test to identify which one has the biggest impact on your NPS score, for example. This kind of test allows you to identify the impact of a change in one metric on another, regardless of how many variables you have