Product News

Census + Google Analytics: Sync data to custom dimensions for revenue attribution

Katy Yuan
Katy Yuan April 14, 2022

Katy is a Product Marketing Manager at Census who loves diving into startups, SaaS technology, and modern data platforms. When she's not working, you can find her playing pickleball or Ultimate Frisbee.

Ask 10 different people and you’ll get 10 different answers:

  • What campaign brings us the best leads?
  • Where do new users drop off in the signup process?
  • Which marketing channel brings the most revenue?

Integrating metrics across marketing tools often feels like a duct-taped solution. Each platform manages a different stage of the customer journey, resulting in disjointed customer experiences externally, and a lot of pain internally.

Today we’re excited to announce our integration with Google Analytics! By using the data warehouse as your source of truth, you can define metrics and create models with company-wide data context, and sync those custom dimensions in GA to determine which visitor actions influence your revenue.

👉 For an in-depth guide, listen to the Operational Analytics for Marketing live session where we discuss modeling, scoring, and continuity across marketing metrics.

🚀 What can I do with Census + Google Analytics?

Operational Analytics using reverse ETL helps both data teams and marketing teams unify and sync metrics across all their marketing tools.

1. Evaluate marketing channel effectiveness

🙋 Answer questions like: “Do paid or organic channels have higher quality traffic?”

Our very own Growth Manager, Trevor Fox, uses the Google Analytics integration to evaluate the volume of high-quality traffic a given channel is bringing in. He first enriches visitor domains with Clearbit (a Census customer!) and assigns an account quality score (high/mid/low). Then, he maps that account-based scoring back to traffic sources in GA.

This helps him evaluate our ROI per marketing channel (website, social ads, search ads, etc.) and determine which channels bring in higher proportions of qualified company traffic.

👉 For more details, check out this article by Trevor: Bringing late-stage sales signals into Google Analytics with Census

2. Attribute user properties to revenue

🙋 Answer questions like: “Which ads bring in the most free trial signups?”

Google Analytics captures millions of events including impressions, clicks, and conversions, but it doesn’t help you figure out which actions lead to revenue.

Especially for companies with longer sales cycles, early marketing actions can be hard to attribute to later sales outcomes.

By enriching website visitors with all the data context in your warehouse, you can identify the top prospect actions that correlate with revenue. Combine server-side or offline conversions such as product usage and chatbot activity with website actions like content consumption to continuously refine criteria that indicate high conversion potential.

3. Iterate faster and run big experiments

🙋 Answer questions like: “If I know blog readers from eCommerce companies have high conversion intent, how much revenue will I influence by tripling my Google Ads budget?”

Now that you have a better understanding of your best performing growth levers and marketing channels, you can double down and test your hypotheses at the top of the funnel.

Use Census Segments, our visual audience builder, to quickly build complex segmentation logic without SQL. For example, you can run ads for “only high scoring companies who have been to my product page”, or create lookalike audiences based on top converting customers. Your audiences will always be fresh – new users who match your audience criteria are automatically synced to all your tools.

Even without a perfect attribution or event stream, you can trust your funnel because every metric is a reflection of revenue.

🙌 Benefits of Operational Analytics for marketing

Census’s warehouse-centric approach means experiment analysis and evaluation is consistent across all your tools, because they have the same source model.

For example, you can link account scoring in HubSpot, traffic qualification in Google Analytics, and qualified conversions in Google Ads to get a full picture of the top-of-funnel journey.

OA enables you to design better metrics, apply these metrics appropriately to all the tools in your stack, and improve ROI using all the data in your warehouse.

Interested? Get a demo of Census for marketing operations 🎉

👩🏻‍💻 What is Google Analytics?

Google Analytics is a free web analytics tool that provides statistics and analytical tools to analyze website traffic and SEO efforts. Given that the website is the central hub of many companies’ digital presences, Google Analytics provides a holistic view of digital marketing effectiveness.

🤝 Census + Google: Better Together

We recently wrote about using Looker Looks as models in Census. Census and Google work closely together to help mutual customers accelerate action from data with reverse ETL and Operational Analytics.

Census integrates with multiple Google products that power your business. Supercharge your entire Google stack with Census:

Check out all of our other connectors.

Try Census for free today or join our Slack community for data practitioners!

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For years, working with high-quality data in real time was an elusive goal for data teams. Two hurdles blocked real-time data activation on Snowflake from becoming a reality: Lack of low-latency data flows and transformation pipelines The compute cost of running queries at high frequency in order to provide real-time insights Today, we’re solving both of those challenges by partnering with Snowflake to support our real-time Live Syncs, which can be 100 times faster and 100 times cheaper to operate than traditional Reverse ETL. You can create a Live Sync using any Snowflake table (including Dynamic Tables) as a source, and sync data to over 200 business tools within seconds. We’re proud to offer the fastest Reverse ETL platform on the planet, and the only one capable of real-time activation with Snowflake. 👉 Luke Ambrosetti discusses Live Sync architecture in-depth on Snowflake’s Medium blog here. Real-Time Composable CDP with Snowflake Developed alongside Snowflake’s product team, we’re excited to enable the fastest-ever data activation on Snowflake. Today marks a massive paradigm shift in how quickly companies can leverage their first-party data to stay ahead of their competition. In the past, businesses had to implement their real-time use cases outside their Data Cloud by building a separate fast path, through hosted custom infrastructure and event buses, or piles of if-this-then-that no-code hacks — all with painful limitations such as lack of scalability, data silos, and low adaptability. Census Live Syncs were born to tear down the latency barrier that previously prevented companies from centralizing these integrations with all of their others. Census Live Syncs and Snowflake now combine to offer real-time CDP capabilities without having to abandon the Data Cloud. This Composable CDP approach transforms the Data Cloud infrastructure that companies already have into an engine that drives business growth and revenue, delivering huge cost savings and data-driven decisions without complex engineering. Together we’re enabling marketing and business teams to interact with customers at the moment of intent, deliver the most personalized recommendations, and update AI models with the freshest insights. Doing the Math: 100x Faster and 100x Cheaper There are two primary ways to use Census Live Syncs — through Snowflake Dynamic Tables, or directly through Snowflake Streams. Near real time: Dynamic Tables have a target lag of minimum 1 minute (as of March 2024). Real time: Live Syncs can operate off a Snowflake Stream directly to achieve true real-time activation in single-digit seconds. Using a real-world example, one of our customers was looking for real-time activation to personalize in-app content immediately. They replaced their previous hourly process with Census Live Syncs, achieving an end-to-end latency of <1 minute. They observed that Live Syncs are 144 times cheaper and 150 times faster than their previous Reverse ETL process. It’s rare to offer customers multiple orders of magnitude of improvement as part of a product release, but we did the math. Continuous Syncs (traditional Reverse ETL) Census Live Syncs Improvement Cost 24 hours = 24 Snowflake credits. 24 * $2 * 30 = $1440/month ⅙ of a credit per day. ⅙ * $2 * 30 = $10/month 144x Speed Transformation hourly job + 15 minutes for ETL = 75 minutes on average 30 seconds on average 150x Cost The previous method of lowest latency Reverse ETL, called Continuous Syncs, required a Snowflake compute platform to be live 24/7 in order to continuously detect changes. This was expensive and also wasteful for datasets that don’t change often. Assuming that one Snowflake credit is on average $2, traditional Reverse ETL costs 24 credits * $2 * 30 days = $1440 per month. Using Snowflake’s Streams to detect changes offers a huge saving in credits to detect changes, just 1/6th of a single credit in equivalent cost, lowering the cost to $10 per month. Speed Real-time activation also requires ETL and transformation workflows to be low latency. In this example, our customer needed real-time activation of an event that occurs 10 times per day. First, we reduced their ETL processing time to 1 second with our HTTP Request source. On the activation side, Live Syncs activate data with subsecond latency. 1 second HTTP Live Sync + 1 minute Dynamic Table refresh + 1 second Census Snowflake Live Sync = 1 minute end-to-end latency. This process can be even faster when using Live Syncs with a Snowflake Stream. For this customer, using Census Live Syncs on Snowflake was 144x cheaper and 150x faster than their previous Reverse ETL process How Live Syncs work It’s easy to set up a real-time workflow with Snowflake as a source in three steps: