Data and BI integrations
Data integrations that hand your BI team the join it cannot make itself
The attributed dataset streams into your own BigQuery, so every tool that reads BigQuery reads the click behind the revenue.
View integrationGoogle BigQuery
Clicks, conversions and leads streaming into your own dataset.
View integrationLooker Studio
Reads the exported BigQuery dataset, or a Sheet, natively.
View integrationPower BI
Reads the exported BigQuery dataset with its own connector.
View integrationTableau
Reads the exported BigQuery dataset, live or as an extract.
Snowflake
SoonThe same export into Snowflake, on the roadmap.
Beyond the warehouse
Not every team wants a dataset. The same data leaves four other ways.
The export exists for the team that owns a warehouse and a BI layer. If yours does not, nothing here is a prerequisite: the reports, the API and Atlas work without one.
Ask Atlas
Ask a question in plain language and get the answer from the same rows, without SQL and without a BI licence.
MCP connection
Claude, ChatGPT and Cursor query the workspace directly, so an analyst asks where they already work.
Open API
Read every click, lead and conversion out of LeadJourney over the API, webhooks and Zapier, or stream it into your own BigQuery dataset with the warehouse export.
Setup
Three steps, whatever you connect
The same path for every tool on this page. No developer, no server to run, no tag manager archaeology. 21 minutes end to end.
- 15 minutes
Add the tracking script
One snippet in the site header. WordPress, Webflow, Wix and every page builder in between, then every form on the site reports its true source.
- 210 minutes
Connect your accounts
Sign in to your ad accounts and your CRM. Spend and campaign structure come in, and the lead stages you care about start flowing back.
- 36 minutes
Send the revenue back
Closed deals go to Meta, Google, LinkedIn and Microsoft as offline conversions, so the platforms optimise on revenue instead of form fills.
Questions
What data teams ask before switching the export on
The four that come up whenever a BI team is in the room.
Which warehouses can LeadJourney export to?
Google BigQuery today: clicks, conversions and leads stream into a dataset you own. Snowflake is on the roadmap and is marked that way on the pricing page rather than sold as live.
Do you have a Looker Studio, Power BI or Tableau connector?
No connector, and none is needed. All three read BigQuery natively, so once the export is running they point at your dataset the way they point at any other BigQuery table. That is the whole reason the export lands there.
Is the export on every plan?
It is on the Scale and Enterprise plans, alongside API access. Every plan can read the same data through the Zapier app, webhooks and the MCP connection.
Do I need a data team to use LeadJourney?
No, and that is the point of the rest of the platform. The reports, the dashboards and Atlas answer the same questions without a warehouse in the way; the export is for the teams that already have one. No code and no server setup, and most accounts are reporting inside 21 minutes.
Your data, in your stack
Put the attributed dataset where your BI team already works
Connect your ad accounts and your CRM, switch the BigQuery export on, and the rows that explain your revenue land next to everything else you query. 95%+ accuracy, first-party required.
