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How to Connect Bigquery to Hubspot Marketing Automation

Usha Vadapalli
October 13, 2023

Product usage data can be valuable pieces of your product-led growth puzzle. PLG businesses can understand a lot about their customers by tracking their product behavior. Being able to integrate a data warehouse like Google BigQuery with a marketing automation tool like HubSpot can decode not only customer behavior but also guide your product-led growth strategy with unparalleled clarity.

Product Data in Marketing Automation

Integrating the data warehouse with your marketing automation tool has so many use cases like:

Comprehensive customer insights:

Such insights help refine the product strategy, improve user experience, and tailor marketing campaigns to specific customer segments. For instance, if certain features lead to higher user engagement and customer satisfaction, the company can focus marketing efforts on promoting these features.

You can also identify the right opportunities to pitch an upgrade or expansion based on the product activity and firmographic information.

Churn prediction and customer retention:

By analyzing user engagement data from the product and combining it with account (company size, etc.) and data (email open rates, etc.), a PLG company can create machine learning models in BigQuery to predict churn. They can identify patterns that indicate a customer is likely to churn and take proactive measures to retain them.

Personalized communication:

Segmenting users based on their product usage patterns and behaviors can be the first step to personalize customer communication effectively. For example, active users can receive emails about advanced features or best practices, while inactive users might receive re-engagement campaigns.

When users receive relevant, timely, and personalized messages, they are more likely to continue using the product, upgrade to premium plans, or recommend the product to others.

Product development and feedback loops:

Analyzing customer feedback, feature requests, and support tickets alongside data on how users interact with the product facilitates data-driven product development.

By understanding the challenges users face (through support data) and how they use the product (through usage data), the company can prioritize feature development and enhancements that directly address customer needs, leading to higher customer satisfaction and loyalty.

How to Connect BigQuery with HubSpot?

Step 1: Create a BigQuery dataset and table:

  • In the Google Cloud Console, create a BigQuery dataset to store your product usage data.
  • Inside the dataset, create a table with the appropriate schema to match the exported data.

Step 2: Automate data transfer to HubSpot:

  • HubSpot provides an API that allows you to automate data transfer. Use HubSpot API to send data from BigQuery to HubSpot.
  • Write a script in a programming language like Python or use a middleware service like Zapier to fetch data from BigQuery and send it to HubSpot using HubSpot API endpoints.

Step 3: Map data to HubSpot properties:

Ensure that the data you send to HubSpot is mapped correctly to HubSpot properties. For example, if you're sending user engagement data, map it to relevant contact properties in HubSpot.

Before you connect BigQuery and HubSpot

  • Integrating BigQuery with HubSpot using custom scripts has its limitations. One key drawback is the dependency on technical resources. Writing and maintaining code demands technical expertise.
  • Another limitation lies in data inconsistency and inaccuracy. Integrations with third-party tools, especially custom ones, are prone to discrepancies in data formats or unexpected transformations, leading to inconsistencies. Mismanaged data can result in incorrect analytics, impacting business decisions negatively.
  • Data latency is another concern. In dynamic marketing scenarios, real-time data is crucial, and integration lags might lead to outdated insights, hindering agile decision-making.
  • There's also the challenge of scalability. As data volumes increase, custom scripts might struggle to handle the load efficiently, potentially causing bottlenecks. Scaling up these integrations to match the growing data needs can be technically challenging and might require significant effort and resources.

Inflection as an alternative

If you're a PLG company using BigQuery, connecting it with Inflection is a smart alternative.

Inflection.io offers a straightforward integration with BigQuery, meaning you don't need to be a tech expert to make it work. You can import loads of data quickly, saving you time and effort. Plus, creating personalized emails becomes a breeze with Inflection, helping you connect better with your audience.

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BigQuery holds a wealth of historical data, providing valuable insights. Inflection can combine product data from data warehouses like BigQuery with CRM info, giving you a full picture of user behavior. It's all about simplifying data integration and making your marketing efforts more effective.

Request a demo now and see how the Inflection and BigQuery combination can boost your PLG initiatives.