Multi-Touch Attribution
AnalyticsAlso: MTA · Multi-Channel Attribution
Quick definition
Multi-touch attribution (MTA) is a method of assigning conversion credit across multiple marketing touchpoints in a customer journey, rather than giving all credit to one channel. MTA acknowledges that most customers interact with several ads, emails or organic results before converting.
A customer touches all four, then converts.
Credit distributed
Last-click hands all credit to the final touch. The display and email work that warmed the customer up disappears from the report.
How it varies across Australia
Most Australian businesses still report on last-click attribution because it's the default in Google Ads and Meta Ads. The gap between what last-click reports and what multi-touch attribution surfaces tends to widen as media mixes grow more complex. Businesses running three or more paid channels are usually the first to feel the pain of single-touch reporting.
See attribution patterns across Australian industries →The main MTA models
Equal credit to every touchpoint in the journey.
More credit to touchpoints closer to conversion.
Most credit to the first and last touch, less to the middle.
Model trained on your own conversion data to assign credit algorithmically.
What it actually means
Think of three friends who each told you about a band. The first mention planted the seed. The second deepened the interest. The third reminded you the day before the concert. Last-click attribution pays only the third friend. Multi-touch attribution (MTA) tries to pay all three in some proportion.
MTA is the umbrella term for any attribution approach that distributes credit across more than one touchpoint in a conversion path. The word 'model' describes the rules for how credit is split. Linear splits evenly. Time-decay weights toward recency. Position-based loads the first and last touch. Data-driven uses statistical patterns from your actual conversion data.
None of these models is correct. Each one is a different assumption about which touchpoints cause conversion versus which ones accompany it. The choice of model shapes budget decisions, channel valuations and team incentives. That's why the model choice is a strategic decision, not a technical one.
For teams running paid search alongside paid social, display, email and organic, MTA is the only way to avoid systematically underfunding upper-funnel channels that last-click attribution can't see.
The model you pick doesn't reveal the truth. It reveals a version of the truth you chose to believe.
How it shows up
MTA shows up in the gap between what a single-touch report says and what a full-path report says. A display channel contributing nothing under last-click might show meaningful assisted conversions under linear or time-decay. A branded search campaign that looks dominant under last-click might take a smaller share under position-based.
The most useful MTA output isn't a single number per channel. It's the comparison across models. When a channel looks strong under every model, the evidence for its contribution is robust. When it only looks good under the model that favours it, that's worth scrutinising.
The Australian context
iOS privacy changes and the gradual deprecation of third-party cookies have made MTA harder to run reliably in Australia, as they have everywhere. The customer journeys MTA models are built on depend on cross-site tracking that is now incomplete. Australian businesses that relied heavily on pixel-based MTA tools have seen their path data thin out over the past few years.
The practical response is to treat MTA as a directional signal rather than a precise measurement. Combine it with media mix modelling for larger budgets and with incrementality testing where possible. No attribution model survives privacy changes intact. The ones that acknowledge their own gaps are more honest than the ones that paper over them.
Where people get this wrong
Related terms
Common questions
What is the difference between multi-touch attribution and last-click attribution?
Last-click gives all conversion credit to the final touchpoint before the sale. Multi-touch attribution distributes credit across the full journey. Last-click is simpler and widely used as a default. MTA gives a more complete picture of which channels contributed, at the cost of more setup and more data.
Which multi-touch attribution model should I use?
Start with linear or position-based and compare the outputs against your last-click report. If the differences are large, they point to channels that last-click is systematically over- or under-valuing. Data-driven is worth using once you have reliable conversion volume and a tool that supports it.
Does multi-touch attribution still work after iOS privacy changes?
Partially. Cross-device and cross-site path data is thinner than it was. MTA still works within environments where tracking is intact, like email clicks and CRM-logged interactions. Treat it as a directional signal and supplement with incrementality testing where budget allows.
How is multi-touch attribution different from media mix modelling?
MTA is user-level and path-based. It looks at individual conversion journeys. Media mix modelling is aggregate and statistical. It uses overall spend and outcome data to estimate channel contribution. Both have gaps. Used together, they give a more complete picture than either alone.
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About New Rebellion
New Rebellion is a marketing intelligence consultancy. We build tools, score Australian businesses on how their marketing actually performs, and publish Debrief every day. This dictionary is part of how we work in the open.
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