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Integrations

Sync data from
Google BigQuery to Salesforce

Connect your data from Google BigQuery to Salesforce with Hightouch. No APIs, no months-long implementations, and and no CSV files. Just your data synced forever.

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Google BigQuery.
Hightouch sync.
Salesforce.

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Integrate your data in 3 easy steps

  1. 01

    Add your source and destination

    Connect to 15+ data sources, like Google BigQuery, and 125+ destinations, like Salesforce.

    Google BigQuery.

    Connect

    Connector beam.
    Salesforce.

    Log in

  2. 02

    Define your model

    Use SQL or select an existing dbt or Looker model.

    Define your model
  3. 03

    Sync your data

    Define how fields from your model map to Salesforce, and start syncing.

    Google BigQuery.
    Connector beam.
    Salesforce.
    Google BigQuery.

    email

    Connector beam.
    Salesforce.

    email

    Google BigQuery.

    name

    Connector beam.
    Salesforce.

    name

    Google BigQuery.

    total_orders

    Connector beam.
    Salesforce.

    all_orders

    Google BigQuery.

    last_login

    Connector beam.
    Salesforce.

    last_login

Model your Google BigQuery data using any of these methods

  • dbt Model Selector

    Semi-opaque, open dropdown with three example dbt model names such as 'dbt.model.name.1'.

    Sync directly with your dbt models saved in a git.

  • Looker

    Semi-opaque open dropdown with three example Look names such as 'look.1'.

    Query using looks. Hightouch turns your look into SQL and will pull from your source.

  • SQL Editor

    Empty SQL editor.

    Create and Edit SQL from your browser. Hightouch supports SQL native to Google BigQuery.

  • Table Selector

    Semi-opaque open dropdown with three example table names such as 'schema.table.name.1'.

    Select available tables and sheets from Google BigQuery and sync using existing views without having to write SQL.

  • Audiences

    Visual query builder reading 'All rows that...' with a button labeled 'select a property'.

    For less technical users, pass traits and audiences from Google BigQuery using our visual segmentation builder.

Where can you sync your Google BigQuery data in Salesforce

  • Account

    Represents an individual account, which is an organization or person involved with your business (such as customers, competitors, and partners). Use the account object to query and manage accounts in your org.

    Hightouch docsSalesforce API
  • Contact

    Represents a contact, which is a person associated with an account. Use the contact object to manage to manage individual people who are associated with an account.

  • Lead

    Represents a prospect or lead. Use the lead object to manage leads in your org.

  • Opportunity

    Represents an opportunity, which is a sale or pending deal. Use the opportunity object to to manage information about a sale or pending deal.

  • Campaign Member

    Represents the association between a campaign and either a lead or a contact. Use the campaignMember object to manage campaign members in your org.

  • Task

    Represents a business activity such as making a phone call. Use the task object to manage to-do items for your org.

  • Case

    Represents a case, which is a customer issue or problem. Use the case object to manage customer cases for your org.

  • Asset

    Represents an item of commercial value, such as a product sold by your company or a competitor, that a customer has purchased. Use the asset object to manage assets for your org.

  • User

    Represents a user in the organization. Use this object to query information about users and to provision and modify users in your organization. Unlike other objects, the records in the User table represent actual users—not data owned by users.

  • Custom Salesforce Objects

    We support custom Salesforce objects to ensure our integration supports all your organization’s unique workstreams.

Does this integration support in-warehouse planning?

Yes, if you integerate Google BigQuery and Salesforce using Hightouch, in-warehouse planning is supported.

Great, but what is in-warehouse planning?

Between every sync, Hightouch notices any and all changes in your data model. This allows you to only send updated results to your destination (in this case Salesforce). With the baseline setup, Hightouch picks out only the rows that need to be synced by querying every row in your data model before diffing using Hightouch’s infrastructure.

The issue here is this can be slow for large models.

Warehouse Planning allows Hightouch to do this diff directly in your warehouse. Read more on how this works here.

Why is it valuable to sync Google BigQuery data to Salesforce?

Salesforce is the backbone of your sales org. It's where you manage all of your contacts, accounts, and deals. The problem is that most of your CRM data has to be manually input by individual sales reps, so it doesn't show you an accurate 360-degree view of your customer. You only have access to basic information and historical interactions.

All of your Salesforce data, in addition to the rich behavioral data captured through your app/website already, exists in Google BigQuery. Most of the time, this includes core metrics your data team has defined around lifetime value, workspaces, subscriptions, playlists, average order value, last login date, etc. There's a high chance you're probably even consuming this data in a dashboard, and your sales reps can't answer key questions like:

  • Which accounts have the highest lifetime value?
  • Which users have the highest utilization in our product?
  • When did user X last log in to the app?
  • Which leads/accounts should I be prioritizing?
  • Which accounts are at risk of churning?
  • What is the average order value of account X?

Your sales team doesn't want to hop back and forth between your various SaaS tools to answer these questions. They want to take action in Salesforce, and that means enriching your CRM with data directly from your warehouse.

Why should you use reverse ETL to connect Google BigQuery and Salesforce data?

Conventionally moving data from Snowflake to Salesforce meant downloading ad hoc CSV files and uploading them manually or forcing your data team to integrate with the Salesforce API and build and maintain custom pipelines. In reality, CSVs are not scalable, and in-house data pipelines and custom scripts break constantly.

Other point-to-point solutions create a weave complex web of pipelines to and from various SaaS applications and customer data platforms (CDPs), forcing you to pay for another layer of storage in addition to your data warehouses.

Reverse ETL solutions like Hightouch query against Snowflake and sync that data directly to Salesforce. You don't have to worry about CSVs or APIs. You can leverage your existing tables, data models, and audience segments. All you have to do is define your data and map it to the appropriate columns in Salesforce. You can schedule your syncs to run manually or even trigger them to run sequentially based on criteria that you define.

Hightouch automatically diffs data between syncs to ensure your only ever syncing the freshest data, and if any rows fail, Hightouch will automatically retry them later. A live debugger lets you analyze your API payload requests/responses and failed runs in real-time.

How to integrate BigQuery and Salesforce

There are 5 main options on how to move data from BigQuery to Salesforce. Some of these options are more efficient and more secure while some are more manual and less secure. We've outlined your options below:

Option 1: Reverse ETL (Hightouch)

Reverse ETL is the easiest way to sync your data in BigQuery to Salesforce. With Reverse ETL tools like Hightouch, all you have to do is define your data in BigQuery using SQL or your own existing data models and then map that data to the appropriate columns in Salesforce. In addition to this, Hightouch never stores any of your data, so you can own your data pipelines from end to end.

Better yet, your marketing teams can even build custom audiences directly in the Hightouch UI using a simple drag and drop interface. On top of this, your data teams don’t have to worry about fulfilling ad-hoc requests, managing workflows, or fixing broken data pipelines.

Reverse ETL enables Operational Analytics and shifts the focus from simply understanding your data, to putting it to work in the tools that run business processes. Reverse ETL only takes a few minutes to implement and you can get started by following the steps below.

Step 1: Connect to Your Data Source

Data Source.png

Step 2: Connect Hightouch to Your Destination

Destination.png

Step 3: Create a data model or leverage an existing one

You can use SQL to define your data directly in the Hightouch UI or even leverage your existing data models.

Data Model.png
Audiences.jpg

Step 4: Choose Your Primary Key

With Hightouch you can map on any unique key, not just users and accounts.

primary key.png

Step 5: Create Your Sync

Once you have created your sync, you simply have to choose the appropriate columns and map them to the fields in your end destination.

column mappings.png

Step 6: Schedule Your Sync

Once your sync is created you can run it manually, define a set interval, or schedule it to run after a dbt job is completed.

Sync.png

The first integration with Hightouch is completely free so you can actually get started today. If you want to learn more about Reverse ETL, download our guide.

Option 2: Manual CSV Files

Downloading a specific BigQuery dataset as a CSV file and uploading that data directly to Salesforce is probably one of the easiest ways to move data, but it's not efficient. Data stored in this format gets stale really quickly and business teams can never truly rely on it. In an ideal world, you need an automatic daily flow of data from BigQuery to Salesforce.

When you are moving CSVs it requires your data team to fulfill ad-hoc data retrievals every time your sales or marketing team has a request. This is no minimal effort and time begins to add up pretty quickly when you do this over and over again on a daily basis. In addition to this, you also have to ensure that the columns in your file match those that exist in Salesforce, otherwise, you risk ruining all of your existing data because there is no undo button.

Option 2: Custom Integrations

Depending on the scale of your company, you could build your own data pipeline to move data from BigQuery to Salesforce. There are a couple of challenges with this approach. Firstly, building in-house is both time-consuming and resource-intensive and it pulls away from the time your engineers could be spending doing their actual jobs.

Secondly, the APIs for BigQuery and Salesforce are constantly changing, meaning that you have to check for upstream or downstream changes to ensure your pipeline continues working. Depending on your needs, building in-house might make sense, but if you are planning on sending data to additional SaaS applications in the future, it's simply not scalable

Option 3: iPaaS (Integration Platform as a Service)

Workflow tools like Tray and Workato can be a good option for moving data back and forth between SaaS applications. These tools let you build intuitive workflows that trigger actions when specific events happen.

However, when you are moving data from your warehouse to a destination like Hubspot, the workflows within these tools quickly become complex because they are not designed to combine data in the same way that a warehouse is. You will find yourself having to write custom code in order to get your workflows to function, and you will quickly notice that you have more if/then statements and dependencies within each step than you can possibly count.

Option 4: CDPs (Customer Data Platform)

CDPs provide a number of built-in features, but they essentially help you consolidate all of your customer data into a centralized 3rd-party platform so that it can be sent to other SaaS tools like Salesforce. However, CDPs create another source of truth in addition to your warehouse.

They also take your data out of your own cloud environment which can create problems around compliance depending on the industry that you work in. Additionally, from a time-to-value standpoint, CDPs are probably the slowest option, with the average implementation time taking anywhere from six months to a year.

Push lead info from your warehouse into Salesforce CRM to enable executives to go after the right accounts

Push product data to enable account managers to know what actions are being taken in the app

Reduce churn by syncing health scores and churn events to Salesforce CRM for account managers to track

Why sync data from
Google BigQuery to Salesforce?

Salesforce is the single source of truth for your sales team, but it only shows one view of your customer. In reality, all of your product usage data, event data, and custom audiences live in BigQuery. To truly have a 360-degree view of your customer, your sales team needs access to this information. With the proper data in their hands, your sales team can remove the guesswork and start targeting your highest value leads.

Google BigQuery.

About Google BigQuery

BigQuery is a fully-managed enterprise data warehouse that helps you manage and analyze your data with built-in features like machine learning, geospatial analysis, and business intelligence.

Learn more about Google BigQuery
Salesforce.

About Salesforce

Salesforce is a cloud computing service as a software (SaaS) company that specializes in customer relationship management (CRM). Salesforce's services allow businesses to use cloud technology to better connect with customers, partners and potential customers.

Learn more about Salesforce

Other Google BigQuery Integrations

Google BigQuery to Zapier

Hightouch Playbooks: Best practices to leverage reverse ETL

  • Manage Omnichannel Split Testing across Facebook and SFMC.

    Manage Omnichannel Split Testing across Facebook and SFMC

    This playbook will show you how to manage multivariate testing across Facebook and Salesforce Marketing Cloud with Hightouch Audiences.

  • Create Facebook Lookalike Audiences from High Value Users.

    Create Facebook Lookalike Audiences from High Value Users

    In this playbook, you will learn how to use Hightouch to sync an audience of high-value customers to Facebook to generate lookalike audiences.

  • Sync Nested Object Data to Braze.

    Sync Nested Object Data to Braze

    This playbook will help you understand how and why you should be leveraging nested object arrays in Braze to deeply personalize your omnichannel marketing campaigns.

Read more about Salesforce

  • How to Enrich Salesforce Data in 6 Steps.

    How to Enrich Salesforce Data in 6 Steps

    Learn How Hightouch can help you enrich your Salesforce data in 6 easy steps.

  • Why Salesforce Shouldn't be Your Source of Truth.

    Why Salesforce Shouldn't be Your Source of Truth

    Learn how Salesforce creates data silos and why the data warehouse should be your source of truth instead.

  • The Definitive Guide to Pushing Data from Your EDW to Salesforce CRM.

    The Definitive Guide to Pushing Data from Your EDW to Salesforce CRM

    With the growing adoption of CRMs in large and small organizations, serving customer data to sales teams is a true competitive advantage. This guide outlines multiple ways for pushing data to Salesforce from your EDW.

  • How We Migrated to Salesforce in 4 Hours using Hightouch.

    How We Migrated to Salesforce in 4 Hours using Hightouch

    CRM migrations are painful, but they shouldn't be. Learn how you can migrate your CRM in under four hours.

  • How to send data from Redshift to Salesforce.

    How to send data from Redshift to Salesforce

    Learn how you can move data from Redshift to Salesforce in 6 easy steps

  • How to Move Data from Snowflake to Salesforce.

    How to Move Data from Snowflake to Salesforce

    Learn six different ways you can move data from Snowflake to Salesforce.

Read more about Hightouch

  • What is Reverse ETL? The Definitive Guide .

    What is Reverse ETL? The Definitive Guide

    Learn everything there is to know about Reverse ETL, how it fits into the modern data stack, and why it's different than ETL.

  • What is Operational Analytics & Why You Should Use It.

    What is Operational Analytics & Why You Should Use It

    Operational Analytics shifts the focus from simply understanding data to taking action on it in the tools that run business processes. Instead of using dashboards to make decisions, Operational Analytics is focused on turning insights into action – automatically.

  • dbt Cloud: 4 Reasons for Data Teams to Embrace it.

    dbt Cloud: 4 Reasons for Data Teams to Embrace it

    The biggest benefit that dbt Cloud offers to data teams and analytics engineers? Freedom from distractions, and the ability to focus where you can add unique value making sense of your company's data.

Activate data to any of your marketing and advertising tools

Austin Hay.

This might be one of the greatest inventions for technical marketers since the advent of legacy CDPs back in 2015.

Austin Hay

Austin Hay

Head of Marketing Technology

Ramp

Your data is always secure

Unlike other SaaS tools, Hightouch never stores any of your data.
SOC 2 Type 2 compliant.

SOC 2 Type 2 compliant

Your data stays secure, available, and confidential. To see our report, .

GDPR compliant.

GDPR compliant

If you’re in the EU, your data is only processed on EU data centers.

HIPAA compliant.

HIPAA compliant

Healthcare companies like ThirtyMadison, Chapter Health, and Headway trust Hightouch.

CCPA compliant.

CCPA compliant

To see our DPA (Data Processing Addendum), .

52%

increase in return on ad spend

20%

improvement in email engagement

60%

lift in customer acquisition

Ready to activate your data?

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