AI Stack for Multi-Channel Paid Media

Google Ads + LinkedIn Ads + Meta Ads APIs → Claude → Unified Google Sheets dashboard + Slack
Matt Danese
Senior Demand Generation Manager. These stacks are built and used in production — not generated for a listicle.

Running Google, LinkedIn, and Meta simultaneously means managing three different interfaces, three different attribution models, and three different reporting cadences. The result is a fragmented view where nobody has a clear picture of how the channels interact, where budget is most efficiently deployed, or which platform is driving the highest-quality pipeline. This stack collapses the complexity: pull standardized performance data from all three platforms, run it through Claude for cross-channel analysis, and output a unified Sheets dashboard with a Slack summary you can share before your next standup.

The Stack

Input
Google Ads API LinkedIn Ads API Meta Ads API
AI
Claude
Output
Unified Google Sheets dashboard Slack summary

The Prompt

This stack is built around the Attribution Audit Diagnostic Prompt. Here's the abbreviated version — the full prompt with all variables and usage notes is on its own page.

Claude Prompt — Abbreviated
You are a B2B paid media analyst running a cross-channel audit.

Review the performance data from Google Ads, LinkedIn Ads, and Meta Ads below.
For each channel, calculate: total spend, CPL, MQL volume, pipeline contribution, and ROAS.
Identify where channel overlap is inflating conversion counts.
Rank channels by pipeline efficiency — not just CPL — and flag where budget reallocation
would improve overall program ROI.
[ ... continued — see full prompt ]

The Workflow

  1. Pull standardized weekly data from all three platforms

    Export spend, impressions, clicks, CPL, and pipeline contribution from Google Ads, LinkedIn Ads, and Meta Ads for the same 7-day window. Use consistent date ranges and attribution windows.

  2. Normalize the data into a unified format

    Standardize column names and attribution models across platforms before pasting into Claude. Different platforms define 'conversion' differently — reconcile before the analysis, not after.

  3. Run through the Attribution Audit Diagnostic prompt

    Paste the normalized dataset with cross-channel framing. Flag any known attribution overlap — for example, the same lead converting on both LinkedIn and Google in the same week.

  4. Review Claude's cross-channel efficiency analysis

    Claude identifies channel overlap, budget inefficiency by platform, which audiences are duplicating across platforms, and where pipeline per dollar is highest.

  5. Build the unified dashboard and post to Slack

    Paste Claude's output into a shared Google Sheets dashboard with one tab per platform and a summary tab. Post the Slack summary before Monday's channel review.

What This Replaces

Related Stacks

New stacks drop weekly.

Each one includes the tools, the Claude prompt, and the workflow logic. Free — built for in-house B2B demand gen managers.

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