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Single customer view

Understand the customer journey from start to finish

Less than 10% of companies manage to create an accurate 360-degree view of customers – according to Gartner.

On top of this, just 5% can use this single customer view to systemically grow their businesses. Despite this, successfully achieving a complete view of your customers can have profound effects across the business.

This is an overview of this use case, but we also have a technical guide about identifying customers with Snowplow.

What is a single customer view?

Each user leaves a unique footprint when they interact with your digital ecosystem in the form of a behavioral event. Once collected, these events need to be ordered and attributed to an individual user in order to understand the customer journey.

A single customer view means collecting data from all your platforms, devices, and channels and unifying this data at a user level.

For behavioral data, this generally looks like this:

This data would generally be enhanced in a central storage location, such as a data lake or warehouse, to include other data sources, including financial data, CRM data, and so on. 

Here’s an example of similar data before modeling and after modeling to a session level.

The benefits of a single customer view

Getting a customer 360 is often the starting point for other use cases, as effectively attributing digital events to users is necessary in order to create a well-understood data set.

A single customer view can facilitate:

In terms of the business outcomes, the benefits are hardly quantifiable – how much is it worth for a business to understand their customer touchpoints from beginning to end?

The challenges with creating a single customer view

1. Consent and tracking restrictions

Restrictions such as Apple’s ITP as well as cookie blockers mean that browsers can restrict your tracking to days, rather than years. This makes creating a single customer view for longer buyer journeys can be very challenging.

2. Technical challenges

For data teams, unifying users across devices and touchpoints is not an easy task, it can mean using advanced techniques such as probabilistic methods to estimate user identity. This can be outside the scope of less data-mature companies. 

3. Data structures

The data from your data sources needs to share a common, well-structured format, so your data team doesn’t waste precious time cleaning and preparing data. 

This presents a challenge as many data tools do not validate data before it reaches your destination, meaning what arrives needs to be prepared for usage – reducing time to value. 

According to a recent report, data teams can spend over 65 days a year cleaning data.

Read the full report: The State of Behavioral Data 2022

“Now we turn to Snowplow for about 90% of our use cases; it is a really structured part of the feature development process. ”


Using Snowplow for customer journey analytics

Snowplow offers all the relevant pieces to help you deliver hyper-relevance to your users by fully understanding the customer journey. 

What makes Snowplow ideal for helping you visualize your entire customer journey is:

  • Capturing the full story: first-party and server-side tracking circumvent ITP restrictions to offer a complete view of user activity (at the time of writing for up to 400 days). 
  • Cross-device user stitching: capture the journey even when users change between phones, tablets, laptops, and IoT. 
  • Real-time data: get the data to your warehouse in seconds, allowing you to automate actions and achieve hyper-relevance
  • Complete ownership:  we never store your data and Snowplow’s infrastructure is deployed within your own cloud environment (“private SaaS”). This allows you to operate in a compliant and fully private way.
  • Ultra granular and accurate data: with a range of user identifiers, access to your raw, event-level data, and the ability to ingest third-party data from multiple sources, a complete, end-to-end customer journey can be constructed.
  • Flexibility – freedom to customize tracking to capture exactly what makes sense in your context, allowing for more experimentation and personalization.

Ready to start creating rich, first-party data?