What is customer journey analytics?
Customer Journey Analytics is the process of understanding the impact of every interaction a customer has with your business.
Often, customer journey analytics starts with a customer journey map, which is presented as a graph, flow chart, or other visual that documents each stage of the relationship between a customer and a brand.
However, instead of just charting their customer journey on a map, customer journey analytics takes a further step to analyse what effect each interaction has on your customers’ decisions.
Further information is overlaid to help analyse how each interaction drives customers toward the end goal.
Customer journey analytics can include analysis of:
- Customer needs
- Emotional highs and lows
- Key metrics per step in the journey
- Customer satisfaction scores, customer effort scores, and other survey results
- And more
Customer journey analytics can help you to direct your customers’ attention and resolve any pain points that stop them from taking desired actions. It helps you to augment your customer experience and develop a customer journey that not only gets customers to where you want them to go, but helps them connect to the journey itself.
Learn how to utilise customer feedback with our free guide
Customer journey analytics vs. customer journey mapping
Many brands have a broad sense of their customer journey but haven’t optimised it by creating a comprehensive customer journey map or analysing what affects their customers’ experience.
Customer journey analytics and customer journey mapping are complementary but different processes. Here are the main ways in which they are distinct, and how they work together.
What is customer journey mapping?
Customer journey mapping is the process of laying out the end-to-end journey in a clear way. Creating a map of every touchpoint your customer will experience means you can see what steps your customers take to reach the end goal of a purchase, signup, or other action.
Often, journey maps are documented at the process level. For example, an insurance provider would map the claims process, and a bank would document the new account process.
Some common components of customer journey maps include:
- The process being evaluated
- The stages of the journey
- Critical customer interactions and touchpoints
- Representative customer quotes
- Key customer expectations
- Metrics like satisfaction score, mention volume, NPS
- Trends in topics related to this part of the journey
Our ultimate guide to customer journey mapping can help you to draft your first customer journey map or optimise one you have already.
How do you use customer journey analytics with customer journey mapping?
As we’ve already explained, customer journey analytics is the process of gathering as much information as you can from every part of the journey and analysing the journey for pain points and successes.
Understanding which parts of the journey function as planned and which obstacles are in the way of your customers’ progress means you can take action to ensure they complete their journey as you intend.
Benefits of customer journey analytics
There are several benefits to completing customer journey analytics. From better understanding your customers’ behaviour to a better ROI for your customer experience, customer journey analytics gives you better insights and a more informed strategy for improvement.
Your brand becomes more customer-centric
Understanding the customer journey allows your company to be more customer-centric. It allows you to closely evaluate the activities, expectations, thoughts, and feelings of your customers. You learn what they like and dislike, how to move them through your buying cycle, and how to satisfy and retain them. When journey mapping is complemented with customer journey analytics it helps you understand the priority for your customer experience initiatives.
Your business becomes more unified
In addition, with the right focus, customer journey mapping and customer journey analytics break down internal silos. They empower you to streamline services across departments. Not only that, but they help to align everyone by providing a common understanding of the customer experience. Employees get greater visibility into what happens upstream and downstream of their interactions with customers, letting everybody provide a more consistent, high-quality experience.
You can find track issues as they happen
With a sophisticated customer journey analytics platform, you can pinpoint issues in real-time. You can test new approaches and see their influence on your customer experience and bottom line with analytics that update as quickly as you need them.
You see direct and indirect feedback in one place
Explicit feedback – for example, the information you gather through surveys – is easier to pinpoint to specific interactions customers have with your brand. The customer has an experience and directly after, you request input.
Implicit feedback is more complex to understand. This type of data might include operational data such as sales numbers, or it might cover social mentions, what your customers say on the phone to your care centre, third-party reviews, and more.
Understanding how your audience thinks, feels, and acts in response to customer interactions without directly asking them might seem impossible, but with tools such as conversation analytics, you’re able to link your customer journey to this type of customer data.
See how Qualtrics CustomerXM enables customer journey analytics
An example of using customer journey analytics
Customer journey analytics can be used to understand the impact of sub-journeys limited to single processes – such as opening a new account – or the entire digital customer journey.
Below is an example of how you can use customer journey analytics to chart the success of each journey.
Resolving a customer satisfaction issue for a specific sub-journey
Let’s take a printer business that provides hardware to its customers. The brand has realised that the repair sub-journey is currently leading to low Net Promoter Scores (NPS) and a higher cost to serve per customer.
First, the brand needs to chart the customer journey. It looks like the below:
- A customer has an issue with their printing device
- They call the customer care centre to schedule a repair
- The service agents arrive at their place of residence
- The repair is made
However, there are other ways this journey might unfold. For example:
- A customer has an issue with their printing device
- They call the customer care centre to schedule a repair
- The service agents arrive at their place of residence but the customer is not present
- The repair cannot occur, so the customer has to call again to reschedule the repair
- The repair is made at a later date when the customer is present
Overlaying the NPS scores on this latter journey, the company realises that the NPS score drops when the customer has to reschedule the repair. Asking the customer to go through the same process once again to rebook their appointment is causing customers to feel less satisfied with their experience.
Using natural language processing (NLU), the team can also see that there is a more negative sentiment expressed in the open text question they have added to the NPS survey. With the additional calls to the care centre, the cost to serve each customer also increases.
The resulting action
The brand decides it’s best to provide other means to customers to book their appointments at a time to suit them. Offering customers a self-service booking system that they can access via their mobile on an app or through the website gives the customers more control over when their appointment occurs. Adding a facility to reschedule any booked appointments for a more convenient time and accentuating this with push or text notifications when the repair team is on their way can help to see if this reduces the instances of missed repairs and reduces the impact on the customer care centre.
With customer journey analytics in place, the brand team can see if this improves NPS scores at the same points in the customer journey, and measure in financial terms the impact of actions taken for improved customer experience.
How to use customer journey analytics
Customer journey analytics provides the insight you need to successfully manage your customer’s journey. From lowering customer churn to helping you predict customer behaviour, putting a customer journey analytics solution in place will help you to leverage your customer behavioural data for financial success.
But how do you start using customer journey analytics? Below is the outline of the actions you’ll need to take.
1. Map your customer journeys and aggregate data
First, you need to create a customer journey and aggregate the customer data that you already have. Good customer journey analytics tools will be able to do this for you, cutting down the time your team needs to spend sourcing data from third-party locations, customer service chat logs, and survey results.
Competent customer journey analytics software will also be able to track data in real-time, allowing you to build a comprehensive map that reacts to current customer behaviour. It should also be able to draw data from numerous sources, helping you to break down traditional business silos and understanding customer interactions from all business angles: sales, marketing, and more.
Learn the five competencies for customer journey mapping
2. Analyse your customer behaviour and data
Once you have your customer journeys mapped out and your data collected, you can link specific interactions to particular customer behaviour, survey results, social media comments, and more. You’ll need a customer journey analytics solution to be able to link all of this data together in an efficient way.
3. Take action informed by data-led insights
Customer journey analytics provides you with the ability to see cause and effect, as well as providing you with concrete steps to change specific interactions or the entire customer journey. When customers react badly to specific processes or interactions, you can test how changes in your customer journeys affect their future decisions.
Not only that, but you can coordinate your teams across your business to work on customer satisfaction with their experience, based on the data you’ve analysed. For example, if customers are led to purchase through your marketing but aren’t happy with their purchase, they will deal with your marketing, sales, and customer care teams. Understanding what specifically caused a problem for them means you can inform each team of actions they can take to improve.
How customer journey analytics can improve your customer experience
Brands often hit a wall when trying to measure customer experience. Charting your customers’ often nebulous sentiment and which actions have an impact on customer experience can be difficult without the right tools to hand.
Understanding the return on investment for specific actions taken for customer experience is difficult for a number of reasons:
- Data is siloed or overwhelming
- Business departments work separately with a lack of oversight
- Actions aren’t based on data
- There isn’t a way to track the impact of actions on customer experience
Qualtrics CustomerXM allows you to see the value of customer journeys with rich data analysis, provided through conversational analytics. With natural language understanding, Qualtrics is able to provide you unrivalled insights into customer emotions, sentiment, and more to paint a complete picture of friction points and their rationale. Powered by feedback from multiple areas of your business, you are able to create a plan of action with a tangible effect on your customer experience and business outcomes.
With a deeper understanding of customer behaviour, your brand is able to not only understand the return on investment of your actions but develop a customer experience that delivers results. Extending your customer lifetime value, increasing customer satisfaction, and reducing customer churn becomes easier when you understand the triggers for the behaviour.