Customer journey mapping is not new, but the methods by which Customer Experience (CX) professionals are discovering optimal paths-to-purchase are getting much more sophisticated, thanks to the power of journey analytics.
What Is Journey Analytics?
Where traditional customer journey mapping methods have mostly been standalone exercises centered around channel behavior, journey analytics is an ongoing process that looks to real-time (or intervaled) data to provide insights across all customer touchpoints over time, which can then be leveraged to optimize the customer experience as a whole.
Forrester defines journey analytics as: An analytics practice that combines quantitative and qualitative data to analyze customer behaviors and motivations across touchpoints and over time to optimize customer interactions and predict future behavior.1
Using Journey Analytics to Influence Customer Behavior
No more relying on subjective customer interviews (if you can even get your customers to agree) or dissecting the journeys of a few ‘ideal’ customers. Journey analytics provides a scientific, unbiased approach that blends thousands, millions, even billions of data points across various sources and uses data science methods to surface the most significant triggers influencing customer behavior so that you can focus your optimization efforts where they matter most.
Journey Analytics Success Factors
While the benefits and opportunities that journey analytics can bring are plentiful, these methods require a thoughtful approach, investment in the right technologies, and an ongoing commitment to optimization. Important considerations include:
- Data Aggregation: In order to get a truly holistic view of the customer, you must be able to connect data across all systems (i.e. Marketing Automation, CRM, Help Desk, Accounting, etc.)
- Modeling: Advanced analytics software, like LityxIQ, can help you transform your data into valuable insights.
- Test & Measure: Once you begin gathering insights, you can start to test optimization methods within your customer journey to support your findings. Be sure to consistently monitor, measure, and adjust.
- Automation: Incorporating predictive analytics into your process allows you to close the insights-to-action gap and increase velocity with your journey analytics program.
Journey analytics depends on the right people just as much as the right technologies. When you align key stakeholders around data-driven CX, your organization is sure to reap the benefits.
Want to learn more about how to get started with journey analytics?
1 See the Forrester report “The Seven Top Questions About Journey Analytics.”
