Multi-Touch Attribution (MTA)

A marketing measurement method that gives weight to every touchpoint along a customer’s journey. Gives credit to each advertisement used to push a customer to the buying decision.

What is Multi-Touch Attribution?

Multi-touch attribution (MTA) is the measurement that distributes credit of a sale to the multiple advertisements encountered by a customer before the conversion was made. There are a variety of ways to decide how much weight to give each touchpoint, but every method requires cookies to track which touchpoints a particular customer encountered. This means that cookies are needed to make MTA an effective way of measuring campaign performance.

How will multi-touch attribution change in a cookieless world?

Without cookies, it will be extremely difficult to continue to use an MTA model to analyze customer interactions. Advertisers will be unable to know exactly what each customer journey looks like, making the model mostly ineffective. Multi-touch attribution will still be useful within walled garden ecosystems, however. Examples include Google, Facebook, and Amazon, wherein advertisers can still track the customer journey within those specific ecosystems using other tracking information.

A keyboard where every key has a popular online logo or icon on it instead of letters or numbers.

What is the difference between incrementality testing and multi-touch attribution?

Incrementality testing uses an experimental approach to discovering where advertising dollars do the most work. Where MTA relies on a clear picture of customer touchpoints, incrementality testing uses experimentation to find out the impact that specific advertising strategies have on sales outcomes. The approach is similar to traditional A/B testing in that marketers check the effects of their advertisements using a test/control methodology to find out which advertisements drive higher sales and which ones have little or no effect. Incrementality testing works without a need for cookies, which makes it important as privacy regulations continue to limit their use.

Incrementality testing also solves the problem of being unable to know which touchpoints have causal relationships with customers and which ones may or may not have had a real effect. An ad served on a website that a customer visited after seeing one on another website but before a purchase was made may not have necessarily caused a sale to happen, and it’s extremely difficult to say for certain which ads were the real trigger. Incrementality testing focuses on finding causal relationships, which makes it easier to pinpoint exactly which advertisements are effective.

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