How to Connect BigQuery and Marketo

Google BigQuery is a popular choice among data warehouses for product-led growth (PLG) companies. More flexibility in query processing for analytics and also scalability of storage and processing features make BigQuery a great data warehouse option in the modern PLG tech stack.  

Adobe Marketo Engage is a marketing automation platform widely used by enterprises. Connecting BigQuery and Marketo helps marketers track, analyze, and report leads and contacts better with centralized marketing data. It also opens new gateways to opportunities arising from data integration with other sources like CRM with product analytics.  

Unfortunately, there is no direct way to transfer data from Google Big Query to Marketo. Here’s how you can use CSV files to establish the connection:

From BigQuery to Marketo

You can export data from BigQuery in CSV format using Google Cloud Console.

Exporting from BigQuery:

1. Sign in to your BigQuery account and go to the Google Cloud console.
2. Navigate to the Explorer panel.
3. Select the table you want to export and click Export in the Details panel.
4. Choose Export to Cloud Storage and the Export table to Google Cloud Storage pop-up window is displayed.

5. Choose your destination (bucket, folder, file) to export the desired data.
6. Go to Export Format and select CSV from the drop-down list.
7. Choose None for the Compression field, and click Export.

Note: Alternatively you can also use bq extract command in the bq command-line tool, or by querying the data you want to export using Python, Ruby, C#, Java, etc.

Importing to Marketo:

1. Sign into your Marketo account and go to the Members tab.

2. Click on Import Members and choose the CSV file you just exported.

3. Verify the details and click Next.

4. Verify the import preview and match the columns to the corresponding Marketo fields and click Next.

Note: Select the Ignore option in the drop-down if you do not want to import certain fields.

5. Choose the Member Status from the drop-down and click Import.

From Marketo to BigQuery

Marketo provides two types of REST APIs, Marketo personal records and associated object types for users who want to export data programmatically.

For a detailed step-by-step process on how to use set this up, visit the article on How to Connect Segment and Marketo or Marketo's developer documentation.

Marketo returns data in JSON format. Associate a predefined data type and create a table to receive it. Construct a schema for your data tables.

Alternatively, you can use third-party tools and services like Hevo, Stitch, Zapier, etc, to connect BigQuery and Marketo.

Before you Connect BigQuery to Marketo

The goal for a PLG business behind connecting BigQuery and Marketo is to make their product and analytical data actionable. Integrating product activity data with marketing activity and firmographic information ensures product-led communication to the customers with the right message at the right time.

Marketo falls short in orchestrating marketing campaigns for PLG use cases in several areas.

1. API Limitation

PLG companies generate a large volume of product event data every day. Marketo’s limitations on the API calls (50K/day on the most expensive plan) is a bottleneck that does not enable seeing the whole picture of a user and their product behavior.

With this limitation, you will face a trade-off between choosing which data to flow to Marketo, limiting your ability to fully understand your users, or paying more than initially planned to accommodate the large volume of data.

2. Batch Processing

One workaround teams usually employ to overcome the API limit of Marketo is by sending the required data at a lower frequency. Marketo exchanges data in batches and that could lead to duplication problems. In the absence of a robust deduping process or real-time exchange of data you might still end up dealing with a large number of duplicate contacts.

The same problem persists when you use reverse ETL tools to connect BigQuery and Marketo. Most of the popular reverse ETL tools in market batch-process data and you could end up running your campaigns based on stale information.

3. Custom Objects for Product Events

To use product data events in Marketo, you need to create custom objects or data fields which need a certain level of technical proficiency, and the duration of the process can vary based on the number of product events you need for running product-led campaigns.

Committing resources with coding skills to facilitate data synchronization in Marketo might even be too expensive for PLG companies with lean teams.

The limit Marketo has on the number of custom objects you can create in each pricing tier is noteworthy. You are allowed to create only 10 custom objects maximum in most cases.

Inflection and BigQuery

Inflection is the first growth automation platform purpose-built for PLG and hence a better alternative for running product-led campaigns if you are a BigQuery user.

Inflection automates your personalized PLG communications powered by product activity and CRM data. It combines the power of product, marketing, and account information to show you a unified view of your customers.

BigQuery can be your single source of truth for running all your customer communications. The data sitting dormant in your database can become actionable with Inflection.

With backend infrastructure that supports millions of product activity events and large contact databases typical for a PLG company, Inflection is the scalable automation platform in a PLG tech stack.

Watch Inflection live.