Striking a balance between automation and control

I am a product of my experiences and the knowledge I carry benefits tenfold while I am seated in a position to build and automate to my heart’s content. I’ve managed ad monetization down to the campaign level through ad trafficking and built a monetization strategy from scratch for a portfolio of diverse mobile apps. In these experiences, I’ve learned to pay attention to the details, finding nuances that can mean ad implementation failure or success. Now I get to help monetization managers focus on the bigger picture – monetizing using tools built for the job. 

 

 

 

My framework for product architecture is based on transparency and automation – the two things I really wish I saw more of as a monetization manager prior to joining Digital Turbine as a product manager for FairBid. While granular control is ideal, the workload that comes with it is not. I’m thinking about how to lighten the load for monetization managers while surfacing enough data through our platform to build trust with publishers to validate that the automations are working in their best interest. 

 

Bidding from web to mobile and the journey ahead

While working at EPOM/MGID and Genesis Tech, I worked in a mature programmatic environment on the web and saw the early work that went into bringing programmatic into the in-app mobile space. Integrations with DSPs require a lot of time to test and perfect and I know first-hand that it takes an entire team to not only get the integration working but also build relationships and tech with those DSPs to create better ad rendering experiences to scale.

 

With an entire team dedicated to Marketplace improvements, I have the freedom with FairBid to focus on new mediated network partnerships. Programmatic bidding is still “new” to the in-app mobile space – experienced programmatic demand sources are still navigating the limitations offered by the mobile environment and non-programmatic demand sources are working at a breakneck pace to figure out how to buy programmatically while maintaining if not surpassing their performance when buying on a CPA/CPI basis. On top of learning how to bid programmatically in mobile, the industry has dealt with some major curveballs in the last year (hello iOS 14) – these roadblocks make it more difficult to reach a fully automated and efficient ecosystem. I am determined to make it happen through knowledge sharing and setting realistic expectations both internally and externally. Bidding definitely lightens the workload around ad optimization but getting it right takes experience and time. 

 

Managing (what felt like millions of) waterfalls 

At Goodgame Studios, I walked into a company with a strong portfolio of games but ad monetization had been a low priority compared to live ops required to make a great midcore game. This meant that different apps had different ad implementations – centralizing a strategy was very important in reducing the friction I encountered when looking to optimize ad revenue. Even after standardizing the ad integrations going into the different apps, a common frustration was the work involved in maintaining and optimizing the ad stack to continue to grow ad contribution to top-line revenue. 

 

Every few days, I would calculate CPMs per app, per country group per instance, then reset each of the line items to reflect historical CPMs from the most recent 14 days’ performance. While it would have been easier to calculate across the entire portfolio, the differences in player distribution for each app made their performance unique. The only way to maximize my yield was to break these calculations down more granularly. I easily spent 70% of those days working through excel spreadsheets to get those waterfalls just right and hope that those adjustments would result in revenue gains until the next reset. 

 

Why was I insistent on doing this work myself? Aside from not having the technology immediately integrated, there was also a notion of control I had by doing this work myself. Platforms offer automation features but don’t always tell you how the algorithms work – this is sold as a “secret sauce” or “proprietary calculation” that cannot be shared. Building an in-house solution to give publisher’s the insights that they need, beyond the black box, can be a complex and pricey undertaking. Solutions providing the insights while automating many of the tasks can free up time and resources to focus on the main task at hand: creating a great app.

 

 

Until we get to a place where bidding is widely available from all demand sources (including performance demand) and proves to outperform the sequential waterfall setup, waterfall management is here to stay. I’ve picked up a few tips and tricks to help manage this without going insane: 

 

  • Create high, mid, and low tiers for each waterfall network 
  • Create this trifecta of instances for each major country or regional group 
  • Update and optimize at least twice weekly
  • Always test and  measure different ad monetization settings 
  • Check in on your ad delivery to make sure it’s playing out as intended 

 

As a product manager for FairBid, I’m able to focus building the solution I lacked from mediation platforms before – transparency into the black box, giving monetization managers to take their hands off the wheel for repetitive tasks

 

What does this mean today?  

Bidding still has a long way to go to have the highest yield on in-app mobile. Networks have the challenge of building a respectable bidding platform while still maintaining SDK adoption for their performance-based non-bidding SDKs until they are confident in the switch in buy methods. In the meantime, waterfall optimization is here to stay and mediation platforms need to support the flexibility and transparency required for monetization managers to feel comfortable taking a step towards automation (auto CPM options, latency reducing mechanisms, A/B testing with automated variant traffic splits, and more). The supporting teams offered by the mediation platform also need to have a strong understanding of waterfall optimization strategies as well as how the industry is realistically moving towards bidding to make sound recommendations. 

 

Keep an eye out for more features from FairBid to make waterfall setup, management, and optimization even easier in the coming months.

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