Within every app, there’s a moment in the user journey when the user is likely to churn. App retargeting strategies are one of the best ways to retain these users and prevent churn at the app level.
The argument can be made that even if they have churned, it’s still possible to bring users back thanks to retargeting. But as the app industry continues to evolve and consent mechanisms change, it’s essential to diversify retargeting strategies to maintain high performance. If a user’s IDFA is no longer available, it’s impossible to find the user in order to retarget them.
Many publishers may feel that this reasoning isn’t relevant to their business because they don’t have enough apps in their portfolio. But gaming publishers may have to face even harder competition soon thanks to large corporations arriving in the gaming development space with a ton of data and/or money to invest such as Netflix and Applovin.
These new arrivals, combined with privacy developments on both Apple and Android, bring never-before-seen M&A activity that is impacting the entire gaming industry, driving up UA costs as new users become harder to acquire.
Cross-promotion can help shore up marketers’ ability to resist these challenges. Redirecting users from one app to another in the same portfolio is the most valuable solution for app marketers who want to boost user LTV across their entire suite of apps.
The classic way to run a cross-promotion campaign is for app marketers to use their own unsold inventory to promote other titles in their portfolio. There are a couple of different issues with this.
As it stands now, publishers have two options:
One, they use their own unsold inventory. However, in this case, it means they have fewer opportunities to display cross-promotion ads. And the users on which no one is bidding (the unsold inventory) are usually users that do not bring much value to them. The pros are that it doesn’t cost them anything. On the other hand, it doesn’t bring in any revenue for other apps, and paying users (the most valuable ones) usually do not see ads.
The second option is that they can compete with ad placements within their mediation. This means they’ll be able to access more ad placements. However, they lose monetization opportunities, and again, the highest LTV users usually do not see any ads. Finally, monetization and acquisition are managed by two different teams, both of which have opposite goals. Monetization teams seek to monetize ads; acquisition teams are seeking to maximize installs and get a number of “free” ad slots.
This mix of pros and cons presents a bit of a catch-22 for gaming publishers. Now that the biggest ad monetization companies also own game studios, they're consolidating the market and becoming the direct competitors of publishers who specialize only in gaming. While classic cross-promotion may not make the most financial sense, it's dangerous for these gaming publishers to let their new competitors have an opportunity to attract their best users by exposing these users to ads.
The second challenge is to build an effective targeting strategy and find a balance between who to target and when. Promoting another title in the same portfolio to a user that’s still loyal to the original app risks making the user switch too soon. This user may not have reached their full potential on the first app, meaning that the publisher may miss out on conversion opportunities and in-app revenue. On the other hand, publishers can’t target users that have already churned since they are no longer using the app. They will have missed the opportunity to maximize the portfolio-level LTV of these churned users. On top of this, the most valuable app users (those who contribute to the vast majority of in-app revenue) often are not exposed to ads. This means it’s not possible to reach them through mediation alone and prevent them from exiting your ecosystem.
Last but not least, publishers must make the right choice regarding the destination app they want to promote to increase the chance of triggering an install. Choosing an app that has no relevance to the user will cause the user to churn anyway, and potentially be a waste of resources as this ad space could have been sold to a different publisher.
When done right, cross-promotion has proven to be an efficient way to maximize the LTV of your users at the portfolio level, but it can be difficult to operate in-house. Striking the right balance between timing, types of users, which apps to promote, and which inventory to use is extremely complicated for most publishers to manage themselves. In addition, even if some publishers have the infrastructure in place to run classic cross-promotion campaigns (with a dedicated cross-promotion placement for instance), the lack of predictive intelligence makes these campaigns more of a gamble than a precise science.
At Adikteev we’ve thought a lot about how to “hack” cross-promotion. We’ve closely collaborated with our customers to determine what are the main pain points and challenges for publishers who want to operate a smart and efficient cross-promotion strategy. In our research, we concluded that it isn’t profitable to cannibalize existing inventory and compete to win an auction.
It was also clear that the industry needed a new segmentation approach to build an efficient targeting and recommendation engine to predict which portfolio titles would be the best to promote, and which users are likely to churn, making them good candidates for cross-promotion. We turned to our machine learning expertise to find solutions to these two roadblocks.
As mentioned before, one of the biggest pitfalls for marketers looking to run cross-promotion is the fact that they must bid on their own inventory and lose out on potential ad revenue. We found that the best way to avoid cannibalizing inventory is to create new inventory. By integrating a dedicated SDK, app marketers can now get full control of their cross-promotion campaigns without missing out on revenue from their existing ad space.
Using a dedicated SDK can provide app marketers with more specific features and benefits to boost cross-promotion performance. For instance, it offers much more latitude with ad format, design and size. The SDK we’ve developed at Adikteev embeds a new set of formats directly inspired by the UI and UX of the OS itself (iOS and Android) to improve the user experience and increase marketing performance.
As we detailed in our previous white paper about predictive analytics, it’s possible to develop a model that will evaluate the likelihood that a user will leave the app forever.
Here, the most important piece of the predictive cross-promotion puzzle is churn prediction. Without relying on device IDs, the churn prediction model analyzes the app audience at the user level and assigns a churn probability score and a possible return-to-app count for each user in the cohort. If the model finds a user with a high probability of churn, app marketers can deploy their cross-promotion engine to re-engage the user and keep them within their portfolio of apps.
The app affinity engine analyzes the information available in the user profile, like the frequency of interactions with other apps already installed and which ones are installed. Then, based on this information, the model selects the app from the portfolio that would be most suitable for this specific user.
The app affinity engine offers the possibility to engage in user-level acquisition campaigns by leveraging app marketers’ own inventory. In many apps, a very small number of users account for the majority of in-app revenue. It’s essential for app marketers to retain these few high-value users, and predictive cross-promotion campaigns are the best way to keep them within the app ecosystem.
Using these tools, marketers can retain their users by redirecting them to another app within their portfolio using their own inventory. In turn, this can help increase the lifetime value of retargeted users by decreasing their likelihood of churn and creating a closed loop, allowing users to circulate from one app to another without ever leaving the app studio’s portfolio.
Performance retargeting maximizes app-level user LTV by bringing back users after they have churned. However, if users don’t consent to share their device ID, it's impossible to recognize them and get them back. In light of this, preventing the churn of valuable users is more important than ever.
Rather than maximizing user LTV at the app level, cross-promotion is concerned with maximizing user LTV at the portfolio level. As reduced IDFA collection becomes a reality for app marketers, app-level user information is becoming less and less readily available. This means that portfolio-level LTV is more critical than ever. In addition, the SKADnetwork is extremely limited in its attribution capabilities, making measuring ROAS more difficult. Although unique device IDs will be harder to come by, engaging users in cross-promotion campaigns will create a closed circuit of users that continue to increase in value as they move from app to app. We believe that the future of retargeting lies in how well an app can boost this portfolio-level LTV among its users, and cross-promotion is essential to a good strategy.