What is multi-touch attribution (MTA)?
In marketing, multi-touch attribution (MTA), or multi-channel attribution, assesses the significance of each touchpoint on a user’s journey to conversion and assigns credit accordingly. This analytics model allows marketers to assess the level of impact each channel has in facilitating installs, and at what point of the funnel. Multi-touch attribution data allows marketers to understand which channels to advertise with for brand awareness, or use as assisting channels, and which to use as conversion channels. It also provides information about which channels work effectively together in a cohesive campaign.
A multi-touch attribution model may be chosen by a marketer because a user’s journey to getting an app on their phone isn’t as simple as seeing an ad, clicking, and then installing. It often takes multiple touchpoints before the conversion.
How does multi-touch attribution work?
This attribution model works by tracking and analyzing the various interactions a user has with an app prior to install, such as clicks on ads, website visits, social media engagement, and email interactions. There are several models of multi-touch attribution that can be used:
- Linear: All touchpoints receive equal credit.
- Time decay: Touchpoints that occur closer to install receive more credit.
- U-shaped: The first and last touchpoints are each given 40% credit, while the remaining 20% is divided across the middle touchpoints.
- W-shaped: The first, middle (lead-creation), and last touchpoints each receive 30% of the credit, while the remaining 10% is divided across additional touchpoints.
Depending on the model a marketer chooses, multi-touch attribution assigns credit to each touchpoint based on its role in the conversion process. This helps marketers gain a comprehensive understanding of the customer's path to conversion and helps them make informed decisions about which marketing channels and strategies are most effective in driving desired outcomes at each stage of the marketing funnel.
Multi-touch vs. other attribution models
Multi-touch is just one method of attribution modeling that marketers can leverage for robust insights. In the current mobile marketing ecosystem, models that favor aggregated data over individual device-ID measurement are gaining significant traction. Let’s look at multi-touch compared to a few other popular approaches.
Last-touch attribution vs. multi-touch attribution
The current industry standard among “traditional” attribution models (and therefore the one that Adjust uses by default) is last-click, or last-touch attribution. This means that the last ad the user clicked on gets 100% of the credit and consequent payment.
Multi-touch attribution, on the other hand, awards either equal or weighted credit to the channels a user comes across within the attribution window. The distribution of credit varies depending on which of the multi-touch attribution models is selected.
Media mix modeling vs. multi-touch attribution
Media mix modeling (MMM) takes a top-down perspective, relying on historical data at regular intervals such as business quarters or annually. It assesses the impact of, and interaction between, media spend, seasonality, app store ranking, press coverage, and attribution figures.
In contrast, multi-touch attribution analysis employs a bottom-up approach, tracking real-time consumer engagement across digital channels, offering granular insights and real-time assessments.
Incrementality vs. multi-touch attribution
Incrementality measurement focuses on assessing if a specific marketing campaign has an impact on KPIs, and if so to which (positive or negative) extent. This is done by comparing a group exposed to the campaign with a control group that wasn't exposed. Multi-touch attribution is used to assess which touchpoints in a campaign worked together to lead to an install.
Essentially, each method can be used to answer the following questions:
- Incrementality: Does this campaign have a positive or negative impact on my KPIs? How much of an impact does it have if so? Is this return worth the investment?
- Multi-touch attribution: Which channels involved in this campaign have contributed to a particular user’s install? What did that journey look like?
What are the benefits of multi-touch attribution?
Benefits of multi-touch attribution for publishers: Multi-touch attribution provides credit to publishers across the marketing ecosystem. By rewarding multiple channels for their role in securing the install instead of simply paying one partner, this attribution model helps distribute advertising budgets in a fairer way.
Benefits of multi-touch attribution for advertisers (app marketers): Multi-touch attribution informs marketers of what really brings users to their app, helping advertisers identify where value is being generated across their consumer journeys. Smaller publishers who might struggle to get enough credit in blunter attribution models are more likely to be spotted by companies using multi-touch approaches, helping an advertiser to determine value in the long run.
With multi-touch attribution analysis, a marketer gains:
- Granular insights: Detailed, granular insights into the customer journey allow marketers to understand how various marketing channels and interactions contribute to conversions, enabling more precise decision-making.
- Effective resource allocation: By identifying the most influential touchpoints and channels, marketers can allocate budget and effort more effectively, maximizing the return on investment (ROI) for their campaigns.
Adjust: How to leverage your reporting as a multi-touch attribution tool
While mobile measurement partners (including Adjust) primarily use last-click attribution, we do offer the option of using multi-touch attribution reporting as a separate package with Adjust Multi-Touch. This gives clients access to an unlimited number of touchpoints to map the full user journey.
Each click or impression that plays a role in an install, session, event, or reattribution is documented, irrespective of whether it falls within your attribution window. This includes touchpoints from self-attributing networks (SANs).
Even if a marketer is using the last-click attribution model they can still hypothetically map out the complexities of the user journey by ingesting raw data into their Business intelligence (BI) system. However, this is only possible if the company’s BI system is capable of managing large amounts of data.
To learn more, reach out to your Adjust rep, or read our blog on everything you need to know about multi-touch attribution.
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