Growth Marketing & Multi-Touch Analytics Lab

Multi-Touch Attribution Model Lab

Compare First-Touch, Last-Touch, Linear, Time-Decay, and Position-Based multi-touch attribution models to optimize channel ROAS in a free marketing lab.

Attribution Model Channel Comparison MTA Theory FAQ

Marketing Channel Presets

Load benchmark multi-channel campaigns.

Step 1: Configure Total Revenue & Channel Touchpoints

Multi-Channel Customer Journey Inputs

Total sales revenue to be allocated across touchpoints.
Total Media Spend
$47,000
Across 4 media channels
Attributed Revenue
$150,000
Total converted portfolio revenue
Blended Portfolio ROAS
3.19x ROAS
Blended media efficiency ratio
Attribution Comparison
5 Models Evaluated
MTA vs Last-Touch Comparison

Multi-Touch Attribution Revenue & ROAS Comparison Table

Channel & Spend First-Touch (FTA) Last-Touch (LTA) Linear (Equal) Time-Decay Position-Based (U-Shaped) Strategic Diagnosis

Marketing Attribution Principles

Why Last-Touch Attribution Fails

Traditional advertising platforms and analytics default to Last-Touch Attribution (LTA), creating dangerous blindspots for growth marketing leaders:

  • The TOFU Starvation Trap: Channels that build initial demand (Meta video, influencers, SEO blogs) appear to have low ROAS under Last-Touch, leading managers to defund them.
  • The Brand Search Illusion: Branded search ads often report 15x ROAS simply because customers search the brand name at the moment of purchase, claiming credit for upstream awareness.
  • Position-Based Balance: The U-Shaped (40/20/40) model rewards both the creator of demand (first touch) and the closer (last touch), while giving credit to middle nurture emails.

Measure customer acquisition payback in the CAC Payback Lab.

Mathematical Attribution Models

Multi-Touch Attribution formulas

First-Touch Weight = First Touches ÷ Total First Touches

Last-Touch Weight = Last Touches ÷ Total Last Touches

Linear Weight = Total Channel Touches ÷ Total Customer Touches

U-Shaped Weight = 0.40(First) + 0.20(Mid) + 0.40(Last)

Channel Attributed ROAS = Attributed Revenue ÷ Channel Media Spend

Optimize conversion funnel steps in the Conversion Funnel Lab.

FAQ

Multi-touch attribution & media mix questions

What is multi-touch attribution (MTA)?

Multi-touch attribution is an analytics methodology that assigns fractional conversion credit across all marketing touchpoints in a customer's journey, rather than giving 100% credit to only the first or last click.

Why is Last-Touch Attribution (LTA) often misleading?

Last-Touch attribution gives 100% credit to the final click (e.g. brand search or email retargeting), drastically undervaluing top-of-funnel discovery channels like social ads, content marketing, or PR that originally introduced the customer.

What is Position-Based (U-Shaped) attribution?

Position-Based attribution awards 40% credit to the first touch (creation of awareness), 40% to the lead conversion touch, and distributes the remaining 20% evenly across middle nurturing touchpoints.

What is the difference between MTA and Media Mix Modeling (MMM)?

MTA uses user-level digital tracking events to assign credit, while MMM uses macro econometric regression on aggregate spend and sales data to estimate incremental channel lift without relying on cookies or identifiers.

How does attribution bias affect media budget allocation?

Relying solely on last-touch attribution leads teams to over-invest in brand search and retargeting while starving top-of-funnel channels, causing top-line customer acquisition volume to dry up over time.

Can I export the attribution comparison to CSV?

Yes. You can export complete multi-model revenue distributions, CPA, and ROAS calculations as a UTF-8 CSV spreadsheet with formula injection defense.

Continue Exploring Marketing & Demand Tools

Explore our Marketing Hub, calculate CAC payback in the CAC Payback Lab, optimize conversions in the Conversion Funnel Lab, evaluate retention in Customer LTV Lab, or run campaigns in RFM Segmentation Lab.