How to Get Access to Your Influ2 Data in BigQuery

Last updated: July 30, 2026

Getting your Influ2 data into BigQuery means your analytics team can query Influ2 program performance directly — joining it with CRM data, building custom dashboards, or feeding it into attribution models. Influ2 handles the setup for you, so all you need to do is ask your CSM and plug in the credentials on your end. Here’s how it works.

Before you start

You’ll need to be in touch with your CSM. They’ll kick off the dataset creation on Influ2’s side.
Your data or analytics team should be ready to receive Google Cloud service account credentials.
Decide in advance whether the default dataset will cover your reporting needs, or whether you’ll need custom metrics (more on this below).

What Influ2 takes care of

Your BigQuery dataset lives in Influ2’s infrastructure, so there’s nothing to configure on the Google Cloud side from your team. Influ2 will:

Create a dedicated BigQuery dataset for your account.
Set up a service account with read access to that dataset.
Share the service account credentials and a link to the dataset with your CSM.

You'll receive everything you need to start querying — no permissions, scopes, or dataset naming work required on your side.

Steps

Reach out to your CSM. Let them know you’d like to enable BigQuery data sync, and mention whether you want the default dataset or have specific metric customizations in mind.
Review the default dataset structure. Influ2 exports raw advertising statistics grouped by date, target, cohort, stage, and content. If you’d like a sample of the exact columns and row format before you commit, your CSM can share one on request.
Decide if you need customization. If the default grouping and metrics cover your reporting, skip ahead. If you need additional metrics — for example, custom engagement breakdowns or fields tied to a specific attribution model — send your CSM a description of what you need and why.
Receive the service account and dataset link once setup is complete. Your CSM will hand these over directly.
Hand the credentials to your data team to connect BigQuery to your reporting tool of choice (Looker, Tableau, Power BI, dbt, a notebook, etc.).

What you'll see

Once you’re in, your team can query the dataset like any other BigQuery source. You’ll see tables populated with campaign-level raw statistics, refreshed daily.

Sync frequency — the dataset updates daily, so your reporting reflects activity from the previous day.
Historical data and corrections — data can be updated for the last 7 days. If an impression, click, or other event is revised upstream within that window, the correction flows through to BigQuery. Data older than 7 days is considered final.
Data scope — by default, the dataset contains raw statistics (impressions, clicks, and visits) grouped by date, target, cohort, stage, and content. If you need targets, signals, opportunity or revenue attribution, or other data objects added to the export, that falls under customization — flag it with your CSM.

Dataset example

Here’s what a few rows of the default dataset look like:

date	target_id	cohort_id	stage	content_id	impressions	clicks	visits
2026-07-18	tgt_8f21ac	coh_2201	Awareness	cnt_5501	42	3	1
2026-07-18	tgt_a13c90	coh_2201	Consideration	cnt_5502	18	0	0
2026-07-19	tgt_8f21ac	coh_2201	Consideration	cnt_5502	55	5	2

Each row represents one target’s activity against one piece of content, on one day, at whatever stage they were in at the time. To get campaign-level totals — impressions, clicks, or CTR — sum across the rows you care about (for example, by cohort or by content).

List of available fields

Field	Type	What it means
date	Date	The day the row’s activity happened. Use this to build daily, weekly, or monthly trends.
target_id	String	The unique ID for the contact this row belongs to. Join this against your CRM contact ID to attribute activity to a specific person.
cohort_id	String	The audience group the target belonged to on that date. Use this to roll up performance by account list or segment.
stage	String	The program or journey stage the target was in on that date. Use this to see how engagement shifts as targets move through your funnel.
content_id	String	The specific ad or creative the target was shown. Use this to compare performance across creative variations.
impressions	Integer	How many times the content was shown to that target that day.
clicks	Integer	How many times that target clicked the content that day. Divide by impressions (where impressions are meaningful — typically 200+) to get CTR.
visits	Integer	How many website visits from that target were attributed to that content that day.

Customizing the dataset

The default dataset is designed to cover most reporting use cases, but Influ2 supports custom exports when a client needs something specific. Common reasons to customize:

You need metrics that aren’t in the default grouping (for example, engagement rolled up at the account level using custom parent/child logic).
You’re building an attribution model that requires joining Influ2 data with specific CRM fields.
You need additional columns surfaced in the raw statistics table.

To request customization: send your CSM a clear description of what metrics or fields you need and the report they'll feed into. Influ2's team will scope the work and confirm what's feasible before building the custom export.

Keep in mind

There’s no self-serve setup. Every BigQuery dataset is provisioned by Influ2, so start with your CSM.
Credentials are tied to a single service account per client. Store them securely and share only with the team members who need query access.
The 7-day update window applies to corrections only. Once data is older than 7 days in BigQuery, treat it as stable for reporting.