Data Panda brings your LinkedIn Ads data together with the data from the rest of your business. From one place, we turn it into dashboards, automations, AI workflows and custom apps your team uses every day.
LinkedIn Ads is the paid side of LinkedIn, reaching over a billion professionals through Sponsored Content, Message Ads, Dynamic Ads, Text Ads and Lead Gen Forms. The audience attributes that make it work for B2B, from job title to company and industry, are the same attributes that make the CPC three to ten times what Google charges.
The point of pulling LinkedIn Ads into a warehouse is that the cost per click is unforgiving. Measured on cost-per-MQL the campaigns tend to look passable. Measured on cost-per-closed-deal, the picture is usually very different. Next to CRM and accounting data, LinkedIn Ads spend lines up against the opportunities it produced, the contracts those opportunities signed and the invoices those contracts paid.
Spend matched to pipeline and invoiced revenue, per campaign and target audience.
Let the stack react to what LinkedIn attention produced downstream.
Use campaign history to score ABM fit and creative performance.
Internal tools on LinkedIn spend for the people who sign off on it.
A list of concrete reports, automations and AI features we have built on LinkedIn Ads data. Pick the one that matches your situation.
Which LinkedIn campaigns closed deals, not just generated MQLs?
Spend per campaign matched to closed-won Salesforce or HubSpot opportunities over twelve months. Separates the campaign whose leads signed contracts from the campaign whose leads only filled forms.
Are our target accounts engaging with our ads at all?
Target-account list matched against LinkedIn reach, frequency and engagement, with CRM outcome on the same line. Surfaces the ABM accounts that are receiving the impressions the plan promised and the ones that are not.
What does a LinkedIn-sourced customer cost us, and how long to payback?
Blended CAC from LinkedIn Ads spend against LTV from Stripe, NetSuite or Salesforce over the first twelve to twenty-four months. The payback curve per campaign becomes visible, not the per-lead cost that most agency reports stop at.
LinkedIn spend next to closed-won revenue and payback period, per campaign. Marketing-budget conversations move from cost-per-MQL to cost-per-signed-contract, which is the number the CFO can defend.
First-touch LinkedIn campaign on every CRM lead, with job title and company on the record. Sales stops asking where a lead came from and starts prioritising on fit and campaign outcome.
ABM target-account coverage, audience match rate and campaign pacing on one board. ABM execution stops leaning on agency screenshots and starts running against the CRM's own account list.
LinkedIn campaign, ad creative and Lead Gen Form data carry through to the HubSpot contact and deal. Marketing reports on closed-won revenue per campaign rather than on form fills, and finance has the full LinkedIn-to-cleared-revenue chain.
Target accounts and tiers from Salesforce push to LinkedIn as matched audiences. Engagement comes back per account, so ABM reporting lives on the Salesforce account timeline instead of in an agency's monthly deck.
Pipedrive deals carry the LinkedIn campaign, ad group and creative that brought the contact in, with cost tied back. Deal-source reports stop relying on rep-entered UTMs that were wrong half the time anyway.
LinkedIn click and campaign data joins GA4 session and event data in the warehouse to produce a multi-touch attribution picture. LinkedIn's role in longer B2B journeys becomes visible instead of being understated by last-click models.
These are the 8 tables we currently pull from LinkedIn Ads into your warehouse. Query them directly in SQL, join them to the rest of your stack, or build reports on top.
Missing a table you need? We can extend the sync. Tell us what is missing and we will build it for you.
You keep the reporting tool you already have. We connect it to the warehouse where your LinkedIn Ads data lives.
OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.
Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.
We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.
We set up the foundation. Your team builds on top.
Best fit Teams that already have a BI analyst or data engineer and want to own the build.
We build the whole thing, end to end.
Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.
You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.
Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.
No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.
Yes. Closed-won and pipeline-stage events from Salesforce, HubSpot or Pipedrive push back as offline conversions, keyed on the original LinkedIn click. Bidding optimises against signed contracts, not against form submissions, which usually rebalances spend within a few weeks.
Yes. Each ad account lands in its own schema with the account hierarchy preserved. Holding companies and agencies get per-brand and per-client isolation and a group-level view on top, without merging spend reports by hand.
We review your LinkedIn Ads setup and the systems around it. Together we pick the first thing worth building.