Good design drives good business. Many of the high growth companies of the digital age have proved that. The success of these businesses has created an appetite for other companies to invest in customer experience (CX) in the hope of achieving similar outcomes.
As organisations worldwide have begun to embrace a customer-led approach, they have been faced with no shortage of customer journey maps, concepts and prototypes. But how do they choose which initiatives to prioritise? Which will have the biggest impact on the bottom line?
Richard Moule, Optimisation Director at EY-Seren explains how CX Analytics can bridge the gap between CX design and the bottom line.
How do you combine customer research and commercial analytics?
There is a tendency to view an analytical approach and a customer-led approach as mutually exclusive. They needn’t be.
The analytical route involves taking a data-driven approach to determining the relationship between customer actions and business metrics. The customer-led approach involves talking with customers (individually, small groups or larger groups through quantitative research) to understand where painpoints or unmet needs exist within customer journeys.
In single channel journeys, such as eCommerce, it can be straight forward to show a direct relationship between customer actions and business outcomes via analytics – friction can be identified through quite basic conversion analysis.
Where customers are interacting across multiple channels, it is harder to draw the correlation. Customer research can allow us to understand how people are swapping between channels. Using this as a framework, we can determine the underlying drivers and data sets that are illustrative of the customer’s needs at each stage, for each channel.
In short, we use research to chart multichannel journeys and then measure all of the moments of truth that ultimately dictate the commercial success of those journeys through analytics.
How do you know what to measure?
Collecting data is not the hard part. The first challenge comes in determining what is meaningful to measure and indicative of commercial success. When you try to measure everything, you know the cost of everything and the value of nothing.
Key Performance Indicators (KPIs) should be, by definition, small in number but highly pertinent to the success of a business. Determining what is key, versus interesting, is a critical step in determining what to measure. Our job is to identify the metrics that really matter for what both the customer and the business is trying to achieve. Once you have defined this, it is a case of finding the data sources that most accurately reflect those metrics – it could be from finance, digital analytics, or customer data, or a combination. Aligning departments against a shared understanding of the customer journey is vital to getting engagement across the business.
What decisions can CX analytics help to make?
Any decision that requires an understanding of the commercial impact of changing a customer proposition.
Whilst primary research can help to answer the question “is it a problem/opportunity?”, analytics allows us to understand the scale of the problem or opportunity. By combining qualitative insight with analytics, we are able to confidently determine the viability of investments in CX.
This could be questions as simple or complex as:
- Should we invest in more staff for the contact centre or develop a new self-service mobile app?
- How will revenues change if we adjust the position of the paywall?
- What is the best way to increase cross-sell and up-sell to existing customers?
- How much is one point of NPS worth to our business in revenue terms?
CX analytics affords us a balanced answer – it takes the likely resulting customer behaviour from a design decision (validated through user testing), scales it (by effectively understanding behavioural customer segments) and predicts the commercial outcome against which to assess the effort (by modelling commercial data) to determine a trustworthy ROI.
Where most design business cases take a “top-down” approach (taking a set of unknown or assumed variables), CX analytics allows us to use historic data to provide a more accurate assessment.
What 3 bits of advice would you give companies considering adopting CX Analytics as an approach?
- Spend time defining the right metrics – The broader the range of metrics, the harder it is to determine the relationship between customer experience and commercial outcomes. We use a tool called a “measurement framework” to facilitate this.
- Focus on behavioural metrics, not just financial – Whilst the intent behind this approach is commercial, it is important to understand the underlying behavioural drivers of customer actions to then determine the commercial impact. More often than not, behavioural metrics are a lead indicator of commercial outcomes.
- Take a long term view – Whilst CX analytics may well yield “quick wins”, it is most effective when embedded alongside a culture of continuous improvement. That can take time.