App marketers should always be on the lookout for ways to optimize campaigns and measure success. A crucial part of the effort is attribution – the process of assigning credit for a conversion to a particular touchpoint. By identifying and analyzing the source of an install or purchase, you can figure out the effectiveness of different marketing actions and decide on the next steps.
There are various types of mobile attribution models, but two of the most widely used are last-touch and multi-touch. Hence, in this blog post, we will delve deeper into these two and their respective pros and cons. Keep on reading to have a better understanding of which attribution model is best suited for your app marketing needs.
The last-touch model, as the name suggests, gives all the credit to the very last touchpoint the user interacted with before converting. For instance, if a user had clicked on a TikTok Ads and then installed your app, the last-touch model would identify TikTok as the channel that is responsible for generating the specific install.
Like any other single-touch model, the last-touch model is straightforward. Even if a user had seen seven ads before converting, last-touch attribution will determine that only the seventh one deserves the conversion credit. Such simplicity and clarity make it easy to implement the model and allow app marketers to understand which touchpoints are driving the most conversions. Consequently, the last-touch model is recognized as the industry standard.
The multi-touch model, on the other hand, assumes that all touchpoints play some role in convincing the user to convert. It thus takes various advertisements and ad networks throughout the user journey into consideration.
In rule-based multi-touch attribution, the credit is allocated according to a predetermined set of rules. Some of the most common include the following:
Rule-based models are intuitive but subjective, as it is the marketer who decides how to assign the credit. As an alternative, algorithmic attribution analysis uses statistical modeling and machine learning techniques to guarantee higher objectivity. You can apply concepts of Markov chains, the Shapley value, and incrementality to conduct data-driven analysis.
Of course, such complexity implies that building an algorithm-based model requires a greater investment in time, money, and labor. Nonetheless, multi-touch remains in demand as it provides a more complete and accurate picture of the user journey as well as the value of specific sources.
In fact, working with a mobile measurement partner like Airbridge could be a more cost-effective option than going in-house. Visit our website to find out how you can benefit from our technology, experiences, and expertise to achieve the most accurate and unbiased results and drive success.
The last-touch and multi-touch attribution models have their own advantages and disadvantages. Here are some key characteristics you should take into account.
Choosing between last-touch attribution and multi-touch attribution depends on a variety of factors, including the nature of your business, your marketing goals, and the channels you use. Because there is no one-size-fits-all solution, app businesses must carefully identify which approach would best suit their needs.
Here are some recommendations for businesses looking to optimize their attribution strategy:
In fact, Airbridge is here to provide app marketers with a unified measurement stack encompassing last-touch attribution, multi-touch attribution, and marketing mix modeling. Having mastered various approaches to mobile measurement, we are capable of offering the most holistic and accurate view of your marketing performance.
If you are looking for a mobile marketing partner that will help you create a robust attribution strategy and optimize your marketing efforts, get started with us today!