How to Pass User Data from Google Analytics Into Salesforce Sales Cloud: Post 2 of 4

Google Analytics Salesforce Integration

This article will explain the three methods for passing user behavior (pages viewed, videos played, documents downloaded, etc.) from Google Analytics into your Salesforce Sales Cloud records. This is the second post in my 4-part series about sharing data between Google Analytics and Salesforce, so be sure to check out post #1 about the benefits and limitations of the standard integrations provided by Google and Salesforce.

Before we jump into the solution, let me quickly describe the problem that we are solving.

The Problem We Are Trying to Solve: Google Analytics Salesforce Integration

Any company that has installed Google Analytics (which is just about every company with a website) is already collecting an enormous amount of behavioral data about their website users. This Google Analytics user data includes which pages a user views, what they are clicking on, how recently and frequently have they visited, etc. This information could be extremely valuable to a salesperson who needs to understand questions like these:

  • Which product is this a lead interested in purchasing?
  • How long has it been since this person last visited the site?
  • Has this person viewed our promotional content (such as one-pagers or videos)?
  • What search terms have they been entering?
  • Which help articles have they been reading?
Salesforce integration ideal state. Search Discovery can now integrate Google Analytics with Salesforce.
Here’s the ideal state. Wouldn’t it be great if you could see something like this in Sales Cloud?

Unfortunately, however, this type of information is not passed into Sales Cloud with the standard integration (as I explained in post #1 of this series). These standard integrations between Google Analytics and Salesforce are intended to benefit marketers (who are concerned with groups of people), and not necessarily sales teams (who manage relationships with individual leads).

At this point, you might be thinking, “This shouldn’t be a difficult problem to solve.” Well…

Why This is a Difficult Problem to Solve

While it’s not impossible, very few companies are doing this today because the following two challenges have been difficult to overcome (until recently):

  1. You need access to the raw hit-level data that Google Analytics captures to do this (you cannot access the behavior of an individual user with the Google Analytics reporting APIs alone).
  2. You need to build or buy an application that can automate the data transfer process to push this data into Salesforce.

The only way to get around these two challenges is to use the Collect Tracking Code, which is JavaScript that you can add to a website to fire behavioral data directly to Salesforce. This is a non-starter for most companies because it means re-tagging your website or application to copy the same information it sends to Google Analytics and fire it into Salesforce. 

This is inefficient and introduces a whole host of other new challenges. If you are already capturing the data you need in Google Analytics, it is better to overcome these two challenges than attempt to skirt around them.

Now for some good news: Google and Salesforce have both launched new products in the past year that make data more accessible and transferable between systems. As a result, these two challenges have recently become significantly less difficult to overcome.

What’s New for Google Analytics Salesforce Integration in 2021?

There are three products that are relevant to discuss here. Two of these are brand new, and one has been around for a few years:

  • Salesforce Data Pipelines (read more)
    Data Pipelines was released in 2021, with the explicit purpose of making it easier for you to import data directly into your Salesforce objects. If you purchase this product you do not need to buy a 3rd-party tool or build a custom application that interacts with the Salesforce APIs (solves challenge #2 above).

  • Google Analytics 4 (read more)
    Google Analytics 4 was released in October 2020. GA4 does a lot of new things, but most importantly it allows you to gain access to your raw (event-level) data through the integration with BigQuery (read more), which solves challenge #1 above.

    Prior to the release of Google Analytics 4, this data transfer service was only available to customers who paid >=$150K for Google Analytics 360 (NOTE: we expect that Google will eventually cap the amount of data you can transfer for free).

  • Tableau CRM [formerly known as Einstein Analytics] (read more)
    Tableau CRM is not new in 2021, but I’m adding it to this list because it’s an excellent tool for solving this problem. This is because Tableau CRM provides similar functionality to Salesforce Data Pipelines described above, but it also allows you to create data visualizations and embed them in your records. Tableau CRM is not required to pull GA data into Sales Cloud, but it simplifies and supercharges the integration.

How to Pass Google Analytics User Data into Sales Cloud

There are three methods for importing your data into Sales Cloud that we use at Search Discovery, and the method that is right for you will depend on the Salesforce products that you have available. Before we discuss the three methods, I will share what needs to be done to prepare your Google Analytics data.

Preparing Your Google Analytics Data

First of all, the “garbage in, garbage out” rule applies here. If you do not trust the data you are capturing in Google Analytics, you should address that issue before embarking on this process.

Secondly, the official integration between Google Analytics and the Salesforce Sales Cloud is a prerequisite for this to work. This is how you pass the user identifiers that are used by Google Analytics into your Salesforce lead records, and this will be the join key that you use to merge the two sources.

How to Pass Google Analytics User Data into Sales Cloud: Step one-prepare your Google Analytics data

Finally, all three methods listed below require access to your raw Google Analytics data into the Google Cloud Platform (BigQuery). If you do not know which version of Google Analytics you are using, I strongly suggest you hire an ace consultant to assist with this process. Otherwise, the instructions can be found here:

  • If you have purchased Google Analytics 360 and you are using the old version of Google Analytics (called Universal Analytics), then you simply follow THESE instructions to configure the data transfer. 
  • If you are using the new version of Google Analytics (called Google Analytics 4), then you can follow THESE instructions to configure the data transfer.

Your Google Analytics data will be fully prepared to integrate with Salesforce Sales Cloud when the following two tasks are complete: 1) GA identifiers are passing into Salesforce when forms are submitted on the website/app, and 2) good quality Analytics data is sitting in a BigQuery table in the Google Cloud Platform.

Once you check those two boxes you can choose one of the methods below to import your data into Salesforce.

Method 1: The Cloud Platform Approach

[Use this method if you have not purchased Salesforce Data Pipelines or Tableau CRM]

In Method 1, we need a way to push your Google Analytics data into a Salesforce object. There are several tools that you can use to accomplish this, but since your Google Analytics data is already sitting in a BigQuery table in the Google Cloud Platform (see “Preparing Your Google Analytics Data” above), then the simplest method is to use the tools available in Google Cloud.

To do this, you will follow these three steps (#1 and #2 are the same for all methods):

  1. Create a query that pulls the data that you would like to import to Salesforce into a flat table, and schedule this table to be updated daily after the prior day’s data is added to a BigQuery table.
  2. (optional) At this point, you may also choose to conduct analysis on this data before it is imported to Salesforce. For example, this is a great time to run a recommendations engine, propensity model, or clustering algorithm (we can help with any of these).
  3. Then, you will trigger a function that transfers the data to an object you’ve prepared in Salesforce using the Salesforce data management APIs.
  4. Once the data is in Salesforce, you can use Salesforce reporting to generate visuals and add them to your lead and opportunity records.

Method 1 is the most difficult to configure, because it requires a data engineer who is familiar with the tools available in the Google Cloud Platform. If you find this process intimidating then be sure to fill out the form below to hear how the team at Search Discovery can manage this for you.

Method 2: The Data Pipelines Approach

[Use this method if you have purchased Salesforce Data Pipelines but not Tableau CRM]

In Method 2, we will use Data Pipelines to transfer the Google Analytics data into a Salesforce object. This is a huge advantage over Method 1 because you don’t need a data engineer to build and maintain the function that transfers data between systems.

To do this, you will follow these three steps (#1 and #2 are the same for all methods):

  1. Create a query that pulls the data that you would like to import to Salesforce into a flat table, and schedule this table to be updated daily after the prior day’s data is added to a BigQuery table.
  2. (optional) At this point, you may also choose to conduct analysis on this data before it is imported to Salesforce. For example, this is a great time to run a recommendations engine, propensity model, or clustering algorithm (yup, we can still help with any of these).
  3. Then, you will use Data Pipelines to transfer the Google Analytics data sitting in BigQuery to an object you’ve prepared in Salesforce.
  4. Once the data is in Salesforce, you can use Salesforce reporting to generate visuals and add them to your lead and opportunity records.

Method 3: The Tableau CRM Approach

[Use this method if you have purchased Tableau CRM]

Method 3 is by far the most advanced because Tableau CRM can manage the data transfer process (just like Data Pipelines), and it can also be used to generate advanced reporting.

To do this, you will follow these three steps (#1 and #2 are the same for all methods):

  1. Create a query that pulls the data that you would like to import to Salesforce into a flat table, and schedule this table to be updated daily after the prior day’s data is added to a BigQuery table.
  2. (optional) At this point, you may also choose to conduct analysis on this data before it is imported to Salesforce. For example, this is a great time to run a recommendations engine, propensity model, or clustering algorithm (we can help!).
  3. Then, you will use Tableau CRM to transfer the Google Analytics data sitting in BigQuery to a Tableau CRM Dataset. From here you can set up a data flow to merge the Analytics data with your lead records.
  4. Once the data is in Tableau CRM, you can build reports and generate visuals that will be embedded back to your lead and opportunity records.

Summary

This post is intended to show you what is possible, and provide general guidance on how to think about integrating Google Analytics and Salesforce Sales Cloud. However, be sure to read post #3 when it becomes available, where I will discuss the benefits that this integration can unlock for your organization.

Additionally, if you felt discouraged by the complexity of this article, remember that the Analytics experts and Data Engineers at Search Discovery are here to help. This is what we do best!

We’re Google Analytics Salesforce integration experts. Power your sales team with new insights today!

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