What is customer journey analytics?
Customer journey analytics, also called end-to-end customer journey analytics, is the practice of analyzing every touchpoint that a customer interacts with across multiple channels and over long stretches of time. It’s a data-driven approach to discovering, analyzing, and influencing the customer journey.
By focusing on the customer’s point of view, organizations can better understand what their customers need in the present and future, as well as enhance the customer experience.
With customer journey analytics, organizations can segment customers based on behaviors, psychographics, and demographics such as age or gender. That way, companies can better develop personalized, multi-channel customer experiences that meet the needs of their diverse consumer base. According to a recent study from IMB, the changes brought on by Covid-19 has pushed companies to spend more time designing personalized customer journeys.
By focusing on each type of customer’s individual needs, organizations can more rapidly understand factors such as churn/bounce rates, conversion, customer acquisition, and other key performance indicators (KPIs). Organizations can thus analyze millions of data points to reveal crucial moments of customer friction, optimize the user/customer experience, and achieve desired business outcomes such as increasing revenue, driving conversion rates, and reducing churn.
With customer journey analytics, scaling is especially important. Organizations should be able to look at the bigger, end-to-end picture, as well as small & micro journeys.
The newest generation of customer journey analytics tools make it easier for teams to clean and aggregate data without making countless complex SQL queries. The newest technologies leverage AI and machine learning to help teams make data-driven decisions.
Customer journey analytics for mobile
Customer journey analytics for mobile is becoming increasingly important as well. More companies are interested in learning how people interact with their apps, the demographics of their users, how they onboard and navigate through the happy, and how they engage with native features that are not available on traditional desktop websites.
Companies are especially interested in knowing where customers are downloading their app (app store vs. website), when customers are downloading the app, what prompts people to drop off or leave the app, and retention rates.
B2B customer journey analytics
While the B2C market pioneered the shift to the focus on the customer, B2B companies are also taking advantage of customer journey analytics. B2B organizations tend to work with bigger deals as well as deeper, longer relationships, with more individualization and complex supply chains.
Customer journey analytics in the B2B context help organizations to better tailor their service offerings based on sector, size, and other factors.
What are some customer journey analytics use cases?
Some common customer journey analytics use cases include:
- Comparing orders made on mobile app vs web
- Learning which elements prompt visitors to bounce from the site
- Tracking the customer experiences from ad to conversion, including marketing attribution (i.e., tracking which person or team gets credit for each micro conversion)
- Monitoring traffic in real-time during a major promotion
- Identifying how Millenials and Gen Z interact with a website vs. how older cohorts interact with a website
- Performing psychographic or attitudinal research that helps to understand user’s needs, wants, goals, interests, and other factors
- Conducting panel-based research and competitive analysis by tracking customers across sites and platforms outside of your company’s digital ecosystem
Customer journey analytics makes it easier to answers questions like:
- How many users take a path?
- What steps/elements lead to a conversion?
- What elements are overlooked or not used?
- When do users tend to convert?
- What are the best channels for conversion?
- What types of customers take which paths?
- Which elements are adding value?
Who uses customer journey analytics use cases?
A number of stakeholders use customer journey analytics, including customer experience analysts, customer support specialists, marketing professionals, UX designers, developers, and IT/Ops teams.
What’s the difference between customer journey analytics and customer journey mapping?
Customer journey analytics is not to be confused with customer journey mapping, which is a set of illustrations or visuals that depict the steps that a user must take to complete a goal. Journey mapping tells a visual story of a user’s journey by compiling a series of desired user actions into a digestible chronology.
Like customer journey analytics, customer journey mapping helps teams to step into their customer’s shoes. However, journey maps are more subjective, since they’re based on UX research, such as A/B tests, surveys, and competitor analysis. After all, personas are fictional characters that represent how different subsections of a customer base will interact with a service, product, or brand. With the help of personas, teams are better able to empathize with users’ needs, behaviors, and experiences.
Customer journey analytics tools, software, and platforms
Some common tools and software that companies use to track and analyze customer journey analytics include: