Marketing Attribution Model Comparator
Compare attribution models and analyze multi-touch conversion paths. Enter values for instant results with step-by-step formulas.
Formula
Model-specific formulas: Last-Click: 100% to final touch; Linear: Equal split; U-Shaped: 40% first + 40% last + 20% middle
Worked Examples
Example 1: SaaS Customer Journey
Problem: Touchpoints: 1) Google Search (awareness), 2) Blog Post Read, 3) Email Newsletter Click, 4) Demo Request. Conversion: $5,000 ACV. Compare models.
Solution: Last-Click Attribution:\n100% to Demo Request\nImplication: Search, blog, email get 0%\nAll budget would go to demo optimization\n\nLinear Attribution:\n25% to each touchpoint ($1,250 each)\nImplication: Equal credit to awareness and conversion\n\nU-Shaped Attribution:\n40% Google Search: $2,000\n10% Blog: $500\n10% Email: $500\n40% Demo: $2,000\nImplication: Recognizes search brought them in, demo closed them\n\nRecommendation: U-shaped balances acquisition and conversion.\nLinear undervalues search (found company) and demo (drove decision).
Result: U-shaped recommended | $2K to search + demo | $500 to middle touches
Example 2: E-commerce Multi-Touch
Problem: Touchpoints: 1) Instagram Ad, 2) Website Browse, 3) Cart Abandon Email, 4) Direct Visit (Purchase). AOV: $200. 1,000 conversions.
Solution: Last-Click:\n100% to Direct Visit = $200,000\nInstagram ad gets $0 (despite initiating)\n\nFirst-Click:\n100% to Instagram = $200,000\nEmail that recovered cart gets $0\n\nTime-Decay (exponential):\n10% Instagram: $20,000\n20% Browse: $40,000\n30% Email: $60,000\n40% Direct: $80,000\nWeights recent touches\n\nPosition-Based:\n40% Instagram: $80,000\n10% Browse: $20,000\n20% Email: $40,000\n30% Direct: $60,000\n\nChoice depends on goal:\n- Scaling top-funnel? First or Position-Based\n- Optimizing conversion? Time-Decay or Last-Click
Result: No single right answer | Position-based balances acquisition + conversion
Example 3: Cross-Channel Campaign
Problem: Touchpoints: 1) TV Ad (not tracked digitally), 2) Branded Search, 3) Website, 4) Purchase. $10,000 order. How does TV get credit?
Solution: Problem: TV isn't in digital attribution\n\nLast-Click:\nBranded search gets 100% = $10,000\nTV gets $0\n\nBUT: Branded search likely caused by TV ad\nLast-click severely undervalues TV\n\nMarketing Mix Modeling (MMM) approach:\nCorrelate TV spend with branded search lift\nEstimate TV influenced 80% of branded searches\nAttribute: $8,000 to TV, $2,000 to search\n\nKey insight: Digital attribution misses offline touches.\nNeed incrementality testing (hold-out markets) or MMM to measure TV impact.\n\nMany companies over-optimize digital by using last-click without accounting for offline drivers.
Result: Digital attribution misses TV | Last-click attributes $0 to TV | Need MMM or incrementality
Frequently Asked Questions
What is marketing attribution?
Attribution assigns credit for conversions across customer touchpoints. A customer might see a Facebook ad, Google search, email, then convert. Which channel gets credit? Attribution models distribute credit differently: last-click gives 100% to final touch; linear splits evenly; U-shaped emphasizes first and last.
What is last-click attribution?
Last-click gives 100% credit to the final touchpoint before conversion. Simplest model, default in many tools. Problem: ignores everything that brought customer to that point. Overvalues bottom-funnel (search, retargeting), undervalues awareness (display, content). Easy to game.
What is first-click attribution?
First-click gives 100% credit to initial touchpoint. Emphasizes awareness and acquisition. Problem: ignores nurturing and conversion touches. Overvalues top-funnel, undervalues sales enablement. Useful for understanding acquisition channels but incomplete for optimization.
What is linear attribution?
Linear splits credit equally across all touchpoints. Simple and fair. If customer has 5 touches, each gets 20%. Problem: treats awareness touch equally with conversion touch. May overvalue mid-funnel activities that don't drive outcomes.
What is time-decay attribution?
Time-decay gives more credit to recent touchpoints. Assumption: touches closer to conversion matter more. Typical: exponential decay with 7-day half-life. More sophisticated than last-click but simpler than data-driven. Good default for multi-touch attribution.
What is U-shaped or position-based attribution?
U-shaped gives most credit to first touch (e.g., 40%) and last touch (e.g., 40%), splitting remainder across middle touches (20%). Recognizes that acquisition and conversion are most critical. Position-based is similar but may weight last touch higher (e.g., 40/30/30 split).