Accuracy, Granularity & QA: Singular Fuels Zynga’s Marketing Stack

Change is unavoidable in mobile advertising. Not only do new ad channels frequently emerge to deliver disproportionate value to early adopters who quickly integrate data-optimized spend tracking, but ad channels often make changes to the data they send to advertisers, causing integrations to break or marketers to miss out on optimizations enabled by granular analytics.

Zynga, one of the world’s largest mobile advertisers, found itself at a crossroads in early 2016. Even with a world-class engineering team, Zynga knew developing an in-house solution that automated ad spend reporting was no trivial task.

Building the APIs to aggregate spend data isn’t too difficult with the right engineers behind it,” says Malachi Rose, Zynga’s Director of User Acquisition. “It is definitely an up-front investment that only makes sense for a large-scale business to take on. However, it is very expensive in terms of time to maintain integrations and constantly work with partners to fix issues with both API and data accuracy.

There are significant efficiencies gained by having a partner like Singular that does this full-time as their specialization and is constantly investing resources into making it better,” says Rose.

Zynga connected its internal reporting to Singular’s API in a matter of days. The UA team found that Singular enabled greater data accuracy via automated QA processes that catch errors in spend data and proactively correct them.

It’s fairly infrequent that we have to ‘fix’ data these days.

Additionally, Singular unlocked a deeper level of data granularity for the UA team.

We were able to track key metrics before, but it was more difficult to slice the views at the most granular level, like at the ad group or keyword. Singular allows us to look at things like retention at a granular level. It’s given our UA managers another arrow in their quiver to address campaign optimization decisions.

Challenges

Zynga turned to Singular to complement its internal reporting and solve for data engineering challenges including:

• Data Accuracy: How to map the right costs to the right partner or app to enable proper Return on Ad Spend (ROAS) analysis
• Deep Granularity: How to get from partner to campaign to ad-level cost
• Sophisticated QA: How to catch errors and automate the resolution
• Full Coverage: How to ingest data from hundreds of ever-changing ad networks

Results

Zynga is now focused on Cohorted ROAS, CPI, LTV, Spend and Cohorted Retention as KPIs for its campaigns. The UA team was able to track these metrics before, but Singular has made it easier to slice the views at the most granular level and expose trends and insights across all dimensions available to Zynga including:

• Campaign
• Ad Group
• Country
• Keyword
• OS
• Channel Type

Each dimension presents a unique potential opportunity to change our strategy in ways that may benefit our metrics.

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