What is Triangulation in Marketing Measurement?
What is Triangulation in Marketing Measurement?
Triangulation in marketing measurement is the practice of using multiple attribution methods or data sources to validate and cross-check marketing performance. Rather than relying on a single model (like last-click or platform-reported ROAS), marketers compare multiple perspectives—such as survey data, platform analytics, and statistical modeling—to build a more accurate, trustworthy view of what’s working.
Why Triangulation Matters
No attribution method is perfect. Platform data can be biased. MMM takes too long. MTA relies on fragile click-paths. Survey data is self-reported. But together? They tell a much more complete story.
Triangulation allows marketers to:
Spot discrepancies between sources
Validate spend in hard-to-measure channels
Make confident budget decisions
Identify under- or over-attributed touchpoints
As attribution becomes harder due to privacy changes and fragmented user journeys, triangulation isn’t a luxury—it’s a necessity.
Common Inputs for Triangulation
Input Type | What It Provides | Strengths | Weaknesses |
|---|---|---|---|
Platform Analytics | Click-based conversion data (Meta, Google, etc) | Real-time, granular | Biased, walled gardens, last-click heavy |
Post-Purchase Surveys | Customer-reported channel insights | Direct signal, captures offline & untrackables | Relies on recall; needs sufficient volume |
Marketing Mix Modeling | Channel impact over time | Strategic, privacy-safe | Requires lots of data, slow |
Multi-Touch Attribution | Attribution across touchpoints | Reflects journey complexity | Incomplete journeys, dependent on cookies |
How to Triangulate Your Attribution Data
Collect from multiple sources – Don’t rely on just one tool.
Map trends, not exact matches – Expect divergence and look for directionally aligned signals.
Investigate outliers – If survey data says 20% podcast and platform says 0%, dig in.
Look for consistency over time – Use monthly or quarterly patterns to guide spend.
Refine your models – Use each method to inform and improve the others.
Why Fairing Helps
Fairing plays a central role in triangulation by delivering fast, direct customer feedback through post-purchase surveys. It's the only data source that can:
Reveal upper funnel and offline influence (podcasts, TV, influencers, WOM)
Challenge or validate what platforms are reporting
Add real context to modeled attribution like MMM or MTA
Fairing data acts as a gut-check and often reveals what traditional tools can't. It plugs critical holes in attribution coverage and helps marketers build a truer picture of what’s driving conversions.
Real-World Example
A health & wellness brand used survey data from Fairing alongside Google Analytics and MMM. When Meta claimed 50% of conversions, but only 30% of customers reported Meta as their discovery channel, the team adjusted their spend and improved blended CAC by 18%.
Final Thoughts
Triangulation isn’t about finding the perfect model—it’s about building confidence through consensus. In a world of messy data and missing signals, the smartest marketers aren’t betting on one source. They’re blending many.
Want to make smarter attribution decisions? Start triangulating with Fairing now.
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