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 The lack of real-time information means that information is out of date by the time it can be acted upon.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?
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
How businesses are leveraging Snowplow for customer journey analytics
PEBMED case study
How PEBMED uses their event-level data to get a granular understanding of their users’ behavior
Animoto case study
How Animoto uses event tracking data to understand and optimize the user journey
Tourlane case study
How Tourlane connected their data dots to gain a single customer view
Tripaneer case study
How Tripaneer uses their event-level data to map their multi-level channel customer journey
Related use cases and content
Single customer view
Deliver personalized experiences by developing a single customer view
Assemble the web analytics that makes sense for your website
Mobile app analytics
Understand how users are behaving across all your mobile apps and games
Developing a single customer view with Snowplow
Stitch user identifiers across platforms and channels to effectively use your data set
How Snowplow compares to packaged analytics vendors
Understand the difference between Snowplow and packaged analytics tools so you can make the right decision for your business.
Data quality starts with data collection
With high-quality data, attribution models are accurate, it’s easy to track and understand user behavior, and customer experiences can be optimized
A guide to better data quality
Discover how you can collect complete, accurate data.