bigquery

Deeper Salesforce and GA360 Insights with BigQuery and Google Cloud

Companies can benefit from integrating CRM data with other data sources to build one powerful data warehouse. Once done, the possibilities are endless, but first you need to have the right tool and sources to build such data warehouse. With BigQuery, as one of the most powerful serverless data warehouses in the market, we can benefit from including Salesforce Sales Cloud data in BigQuery and then using it with Ads Data Hub or joining with other tools that have native exports/data transfer services such as Google Analytics 360, Firebase, or Campaign Manager. While this post is specifically addressing exporting Salesforce data, the methodology described here applies to most CRM systems or any other platform that offers an API for extracting data.

Why export Salesforce data into BigQuery?

Salesforce and Google Analytics 360 already offer critical integrations, so why do we still want to export Salesforce data into BigQuery (alongside the automated export to BigQuery that is routinely activated for Google Analytics 360)?

Salesforce Sales Cloud and Marketing Cloud Integration with Google Analytics 360
Exporting your Salesforce and Google Analytics 360 data to BigQuery will offer many additional opportunities for insight and action, but make sure to also take advantage of the exciting capabilities of the direct native integration between Salesforce and Google Analytics 360.

The benefits of the Sales and Marketing Cloud integrations with GA 360 include:

viewing offline Opportunity stage and Lead status changes as Google Analytics events
report won Opportunities as Google Analytics ecommerce transactions
model attribution for the original traffic sources that contributed to the offline conversion
create Custom Funnels based on offline and online activity to identify drop off points
remarket based on online and offline activity, also taking advantage of Similar Audiences in Display & Video 360 and Google Ads to target additional prospects
segment your email lists based on online activity, such as completion step 4 of a 5-step conversion process viewing 50% of your company video

For more about this integration, sign up for the Google Solution Guide Library to download the Analytics 360 Saleforce Cloud Solution Guide and other helpful guides.

The high-level answer is that the size, speed, and scalability of BigQuery opens a whole lot of possibilities for integration, advanced analysis, and optimization based on your Salesforce data on its own, and even more possibilities when you’re also exporting joinable Google Analytics 360 data to BigQuery.

The specific answer for you depends on your needs. What do you need to understand customers’ behavior? Is there a specific product or discount most new acquisitions go for? Why is the retention rate higher in some locations than others? and so on.

Here are some use cases:

Visualization: BigQuery integrates with several powerful dashboarding tools for advanced analytics and richer insights. By joining Salesforce data with GA data in BigQuery, you can tie up events or goal completion from GA with leads and opportunities from Salesforce.
Targeted marketing: analyze the market to understand customer trends, predict needs, and optimize promotional efforts.
Understand customers’ behavior: using CRM with sales data, you can monitor how their products are performing online and accordingly improve their sales or marketing strategies.
High retention rates: by understanding and predicting potential abandonments or customer inactivity, you can provide better retention offers in a more timely manner.
Advanced modeling: using CRM data, you can build various models – like customer segmentation, loyalty and inactivity – for better targeting.
Preserving data: exporting to BigQuery will help save historical data for later analysis. And avoid losing any fields that are updated or deleted from Salesforce.

To learn more about how Cardinal Path can help you take full advantage of Salesforce, Google Analytics, Campaign Manager, and other enterprise data sets for advanced analysis on Google Cloud Platform, contact us today

Mahmoud Taha

Data Engineering Team Lead Mahmoud is all about facing challenges, the harder the challenge the sweeter the victory. After receiving his Bachelor degree in Computer Science and a diploma in Software Development he worked as a software developer. Later switching careers to the Business Intelligence and Data Analysis field in which he found his passion working with data, analysis and revealing hidden insights to help companies make better business decisions.