Digital Analytics, the Data Application to Understand & Analyze Customer Behavior
Build a complete and compliant understanding of customer behavior and campaign performance, in real-time directly from your warehouse or lake with our Digital Analytics Data Application.
User & Marketing Insights
User & Marketing Analytics, Powered From Your Warehouse
Access all the reports you’re familiar with from Google Analytics, but powered from your own data warehouse or lake.
Understand how your users are being acquired and effectiveness of your different channels.
Measure engagement metrics over time and understand what customers are interacting with
See how and where users and customers are retained in your website, app or platform.
Funnel Builder
Understanding the Path to Conversion
Create custom funnels to analyze user progress and optimize conversion rates directly from your warehouse or lake. You can also use it to gain a deeper understanding of user counts, conversion rates, abandonment and completions at every stage of the funnel.
Use pre-built funnels out-of-the-box or create your own funnels
Auto generate SQL in an optimized way for cost-effective querying of your data from your warehouse
Save your funnel to share with other team members or alternatively download SQL query for future investigation
Marketing Attribution & Optimization
Accurately Measure ROI & ROAS
Effectively refine your marketing spend by identifying which channels are converting new and existing customer most effectively.
Track for up to 2 years for accurate attribution of spend
First-party server set cookie and out-of-the-box identity resolution
First-touch, linear, positional and last-touch attribution methods
Video & Media Analytics
Enhance Viewer Engagement & Retention
Gain deeper insights into your video and audio content performance by capturing comprehensive engagement metrics. Understand how your audience interacts with your content across platforms to improve recommendations, ad targeting, and overall user experience.
Capture in-depth viewer engagement metrics such as real-time play rates and watch times.
Analyze cross-platform content effectiveness by segment, content features (e.g., length, genre), and viewer satisfaction.
Leverage detailed engagement data to improve content recommendations, ad placement, and user retention.
Why Power Your Digital Analytics With Snowplow?
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Scale your analytics further
Scale your analytics further with access to consistent structured and rich AI and BI-ready customer data that powers your data apps to build your own data applications and insight.
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Respect customers privacy
Have complete ownership and control over where your data is processed and what data is collected from each customer with Private SaaS Deployment model and out-of-the-box real-time PII pseudonymization, cookieless or anonymous tracking
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Complete cross-channel view of behavior
Avoid the growing impact of browser limitations on cookie lifetime such as Apple Intelligent Tracking (ITP). Power your analysis with accurate cross-channel tracking and identity resolution with up to a 400 days cookie lifetime.
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Control, transparency, and ownership
Our data models and SQL queries, which power our data applications, are source-available. This means you can understand how the insights are calculated and use them as a starting point for your own data applications.
Frequently Asked Questions
Snowplow defaults to using UTM parameters, but it can be configured to use any custom parameters as well.
Out of the box, Snowplow defines sessions client-side based on a 30-minute timeout. The client-side sessionization behavior can be configured, such as changing the timeout or resetting the session if the user comes in from a marketing campaign. Because the event-level data is in the customer’s own Snowflake instance, it’s also possible to bring your own custom sessionization logic.
There are several reasons – with the Snowflake GA4 connector, the data path is long, expensive due to egress costs, and has latency issues which prevents building real-time applications. The pipeline is also opaque. With Snowplow, data lands in the customer’s Snowflake in real-time, the data is richer and easier to work with using Snowplow’s data modeling.
DPG Media and Strava are two great examples. DPG uses Snowplow for all their behavioral data collection powering various ML use cases and analytics on Snowflake. Strava has instrumented their app with Snowplow allowing product managers to access data created by other PMs and build a single customer view.
Like Google and Adobe, Snowplow acts as a data processor while their customers are data controllers. Snowplow provides customers broad tools to meet their obligations like anonymous tracking for non-consenting users, data pseudonymization and obfuscation, tracking metadata for data collected under different privacy policies. Snowplow takes measures to ensure they are compliant by not touching customer data, allowing encryption keys, and following technical and organizational design patterns for data security.