A growing number of app marketers have started using Multi-Touch Attribution (MTA) in order to better understand the true impact that advertising sources have on their marketing campaigns. Previous attribution models tended to use Last-Touch Attribution, in which only the last advertising source to “touch” the user was credited with having driven an install. But Multi-Touch Attribution gives at least partial credit to every ad source that a user might have seen, enabling marketers to measure campaign performance more accurately.
And yet, there isn’t any one-size-fits-all approach for Multi-Touch Attribution. A marketer can choose to assign “credit” to an ad source in a number of different ways, depending on factors such as how recently they might have seen the ad source, how many impressions the source delivered, and so on. The marketer’s method of assigning credit in MTA will have an impact on how they ultimately decide to allocate budgets.
Research indicates that the chosen method for Multi-Touch Attribution will affect the overall return on investment for any given marketing campaign. If this is true, you can improve your ROI simply by choosing the right MTA model and customizing your data accordingly.
To do this, you must get programmatic access to your ad and app interactions, such as through your own data warehousing solutions or an infrastructure such as Tenjin’s DataVault. Data scientists can take this information to find the best way to accurately attribute LTV to different parts of the customer journey.
Most marketers will start off with some set of commonly used methods for attribution -- usually done by some third party tool. This can help a marketer as a first pass in excel, but the limitations of cookie-cutter models will never perfectly match the specific requirements your business may have.
As a result, serious marketers who spend ad dollars at scale will employ data scientists to customize and iterate on attribution models by testing new methods for performance improvements in ROI. By customizing your MTA model and realizing performance improvements in ad campaigns, you can quickly justify the amount of work that goes into hiring a data guru.
To this point, Tenjin now allows you to programmatically access the clicks, impressions and events in a customer's journey through DataVault. That way you can build your own attribution models, whether you’re an app marketer or a data scientist. By using DataVault, you're now able to see all of your user interactions before conversion and programmatically build your own attribution model so that you can improve ROI performance.
To get started, you’ll first need access to DataVault if you don’t have it already. Contact your Tenjin account manager to request it, or email us at email@example.com.