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Cross-Channel Attribution Truth Engine for Ad Spend
A SaaS platform that ingests data from major ad platforms, e-commerce backends, and analytics tools to resolve conflicting attribution claims and present a single source of truth. The AI-powered engine explains discrepancies using transparent attribution rules shown alongside every answer, eliminating manual spreadsheet reconciliation.
Why this matters
You manage ad campaigns across Google, Meta, and TikTok, and every week you face the same frustration: each platform claims credit for the same sales. Your boss asks what's really driving revenue, and you spend hours exporting data from five dashboards into spreadsheets to reconcile conflicting numbers. When conversions drop, you can't tell if it's a real performance issue, a tracking glitch, or a checkout problem. Existing tools show you data in silos — none explains why the numbers disagree or which one to trust. You need a single source of truth that not only unifies the data but explains the attribution logic behind every number.
- · Built for Performance marketing managers at mid-market e-commerce brands and digital advertising agencies who manage $50K+/month in ad spend across 3+ platforms.
- · Most likely monetization: SaaS subscription.
The Pain · Narrative
You manage ad campaigns across Google, Meta, and TikTok, and every week you face the same frustration: each platform claims credit for the same sales. Your boss asks what's really driving revenue, and you spend hours exporting data from five dashboards into spreadsheets to reconcile conflicting numbers. When conversions drop, you can't tell if it's a real performance issue, a tracking glitch, or a checkout problem. Existing tools show you data in silos — none explains why the numbers disagree or which one to trust. You need a single source of truth that not only unifies the data but explains the attribution logic behind every number.
Score Breakdown
Market Signal
Go-to-Market
Performance marketing managers at mid-market e-commerce brands spending $50K-$500K/month across Google Ads, Meta, and TikTok
~100K globally accessible within 12 months
Product Hunt launch followed by r/marketing and r/PPC organic engagement
$149/month for up to 5 connected platforms
25 paying users within 30 days of launch with <5% churn
MVP Scope · 1–2 weeks
- Build OAuth2 connectors for Google Ads, Meta Ads, and Shopify APIs
- Design normalized data schema for campaign, spend, and conversion entities
- Create basic rule engine to detect overlapping attribution claims
- Build simple web UI showing side-by-side platform claims vs. source-of-truth
- Write 5 example natural-language queries and test with Claude API
- Implement attribution discrepancy explanation generator using LLM
- Add GA4 and TikTok Ads connectors
- Build dashboard showing reconciliation results with attribution rule annotations
- Create exportable PDF/CSV reconciliation reports
- Set up landing page with waitlist and pricing page
Differentiation
Why This Might Fail
Self-rebuttal — the most important trust signal
- 1Ad platforms may restrict third-party API access or change attribution models faster than the product can adapt, breaking the core value proposition
- 2Mid-market teams may already have internal BI tools (Looker, Tableau) and prefer to build attribution logic in-house rather than pay for another SaaS
- 3Attribution truth is inherently subjective — no single methodology satisfies all stakeholders, so the product may face constant pushback on its conclusions
Evidence Summary
How AI synthesized this insight — no verbatim quotes
Approximately 5 commenters raised attribution conflict as a core pain point, asking how to determine true sale origins when platforms claim overlapping credit. Users specifically want attribution rules displayed alongside answers to explain discrepancies. One user highlighted the challenge of distinguishing genuine performance drops from tracking issues. The frequency and specificity of these questions indicate this is not a niche concern but a fundamental workflow gap in multi-channel marketing.
Action Plan
Validate this opportunity before writing code
Recommended Next Step
Build
Strong demand signals detected. Real pain, real willingness to pay — start building an MVP.
Landing Page Copy Kit
Ready-to-paste copy based on real Reddit community language — no editing required
Headline
Cross-Channel Attribution Truth Engine for Ad Spend
Sub-headline
A SaaS platform that ingests data from major ad platforms, e-commerce backends, and analytics tools to resolve conflicting attribution claims and present a single source of truth. The AI-powered engine explains discrepancies using transparent attribution rules shown alongside every answer, eliminating manual spreadsheet reconciliation.
Who It's For
For Performance marketing managers at mid-market e-commerce brands and digital advertising agencies who manage $50K+/month in ad spend across 3+ platforms
Feature List
✓ Unified data ingestion from Google Ads, Meta, TikTok, GA4, Shopify ✓ Attribution conflict detection with rule-based explanations ✓ Natural language query interface for cross-channel questions ✓ Automated discrepancy reports showing platform vs. source-of-truth differences ✓ Exportable reconciliation reports for stakeholder sharing
Where to Validate
Share your landing page in r/Product Hunt · analytics — that's exactly where these pain points were discovered.
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