Customer journey analytics

Build a bespoke understanding of your customers’ behavior


There are many different paths a customer can take on their journey to making a purchasing decision or otherwise gain value from your offering. Along that journey your customers likely interact with various systems and channels, from websites and storefronts, to call centers and chatbots, to marketing emails and TV ads.

Building a complete picture of your customer’s journey is challenging. You need to integrate data from various different sources and systems. The lack of real-time information means that information is out of date by the time it can be acted upon. And you will find that much of your data is poor quality, requiring a lot of cleaning and modelling before it can prove useful.


Customers increasingly demand excellent user experiences on digital platforms, expecting personalized experiences and expecting marketing and recommendations to be highly relevant. Consumers expect the brands they interact with to have a coherent and end-to-end understanding of them as customers.

The brands that will win are those that are able to think holistically about their customer experience, making sure to unify and understand their customers’ behavior across disparate systems and channels. These brands can easily answer questions like:

  • What’s the best time to engage a particular customer?
  • What channels are best for engaging with a certain customer segment – or even individual customer?
  • Which types of customers are most likely to take a given path to purchase?

Why Snowplow

Data collected from digital products only becomes insightful or actionable when joined with other data sources, and when user identifiers across platforms and channels are stitched together.  

Snowplow can be configured to build a clear picture of a user’s journey through an organization’s platforms by:

  • Capturing user behavioral data across multiple channels
  • Preventing gaps in data caused by ad-blockers and ITP
  • Modeling rich data into useful tables to provide actionable insights


Discover how to power your customer journey analytics with behavioral data

Customer stories

How businesses are leveraging Snowplow for customer journey analytics

  • PEBMED image

    PEBMED case study

    How PEBMED uses their event-level data to get a granular understanding of their users’ behavior

  • Animoto case study

    Animoto case study

    How Animoto uses event tracking data to understand and optimize the user journey

  • Tourlane case study image

    Tourlane case study

    How Tourlane connected their data dots to gain a single customer view

  • Tripaneer case study image

    Tripaneer case study

    How Tripaneer uses their event-level data to map their multi-level channel customer journey

Find out how you can optimize your customer journey analytics