App Analytics in Depth: How Data Matching Creates Unprecedented Value for Marketers

By John Koetsier July 19, 2017

A big part of my role here at Singular is helping to articulate how our unique approach to data management creates tremendous incremental value for app analytics and marketing — value that marketers cannot get from any other company.

For those who are unfamiliar with our methodology for collecting and processing iOS and Android data for app analytics, let me outline the four components of our approach:

  • Extraction: How we capture all of the relevant marketing data from each client’s many partners and platforms, and bring it to their respective instances of our unified app analytics platform.
  • Enrichment: How we collaborate with clients to ensure that, even if their partners haven’t in the past been able to deliver data at the level of granularity they need for ROI and other analysis, we can use unique tagging rules and business processes to make it possible going forward.
  • Combining: How Singular standardizes taxonomy and matches Android and iOS marketing effectiveness with user experience app data across partners and platforms to deliver ROI and other business insights at any level of granularity.,
  • Loading: Our proprietary process for importing the data to our analytics database and making it available through advanced, flexible reporting and customizable dashboards. Thus allowing for quick and easy analysis of actionable insights.

I’ve told this four-part data management and enrichment story to dozens of enterprise app developer and app publisher marketing teams, and the discussions nearly always go the same. We move quickly through the app data extraction, enrichment and loading components; these are telegraphic concepts that can be understood in the context of app analytics without a lot of explanation. But combining? That takes a few minutes longer.

Why? Fundamentally, it’s about something that gets very little discussion in the industry — the need to get mobile app data organized, united and segmented right in order to get insight out of it.

Combining Mobile App Analytics Data

Brand leaders must work with a variety of partners and platforms to deliver marketing campaigns and grow their Android and iOS app businesses. Because it’s expensive and complicated to work with so many end points to attract and engage users, marketers are clamoring for better tools that streamline management, app analytics, and reporting.

Mobile application marketers must have a way to combine data from all these sources in a single platform to fully understand their businesses and users. Specifically, they must:

  • Measure the app marketing ROI for all their media investments, at any level of granularity
  • Determine how to optimize their marketing campaigns and other programs so they can attract and engage more iOS and Android app users and deliver optimized data-driven marketing

It’s challenging to construct metaphorical “pipes” to route data from all sources into your analytic tool. But “pipes” aren’t enough. You also need to ensure that the mobile app data flowing through those pipes is combined with data from other sources. In ways that make sense and offer marketers the sort of insights and granularity that they need.

For data to be correctly combined, you need to:

  • Collect the same data on both the network “side” (spend) and the tracker “side” (cost/revenue)
  • Create consistency in organization between upper funnel and lower funnel data

The challenge is that no two sources organize and categorize data in the same way. Across the hundreds of networks available to marketers, there is no standard set of dimensions or naming conventions. This makes it difficult for marketers to identify true ROI with granularity, and to compare performance side-by-side.

Collecting Complete and Consistent Data

Media networks, push notification platforms, and other toolsets for mobile app marketing organize data so that it can be examined at some level of detail. Whether that be at the app, source, publisher, operating system (OS), campaign, creative execution, or keyword level. However, since not all platforms provide every data dimension, marketers need a partner who will:

  • Work with each network to make that data available. Every day, we are working with networks to provide consistent levels of granularity so we can provide ROI at the level marketers need in order to make the most effective campaign optimizations
  • Pull data from various text-based fields and customize to create conventions that complete missing data. Without proper naming conventions, it becomes impossible to identify every detail of the campaign for every source
  • Use heuristic rules to complete missing data. With proprietary technology, we identify each part of the various text-based fields to auto-complete the missing data not provided by the source as a default. For example, in many cases networks do not provide country level data, but it is important for the customer to see performance by country when determining market expansion. We are able to extract this information in other ways to complete the missing information in the report
  • Use custom rules to identify dimensions of data specific to your business. No two businesses are alike. Each has its own app names and nomenclature for distinct aspects of its business. We work with our customers to identify those specific business terms in order to accurately reflect this data in the reporting dashboard

Creating Consistency in Data Organization

Once the data is collected from each network and data provider, it then needs to be standardized. The structures used by media partners and trackers for reporting cost, revenue, and other information vary. Therefore matching to a consistent convention can be a challenge.

By understanding the data provided through each integration, and aligning it to Singular’s standardized data structure and taxonomy, we ensure that we can match all ad performance datasets — like clicks, installs, purchases — to the marketing investments that drove them.

In fact, we work with more than 1,000 partners to codify and adapt to the way that they parse and deliver data to our platform and our clients.


Summary: It’s About a Lot More Than the Pipes

Lots of companies are working on ways of building the mobile data “pipes.” They are feverishly trying to build out the infrastructure to get app performance, marketing results, and media investment information from multiple sources and synthesize it into a single app analytics platform. At Singular, we’ve been doing that for years, and understand all too well why companies often talk about what a struggle this can be.

But even when other analytic solutions eventually reach the stage when they can mimic our mobile app data intake infrastructure, they still won’t be able to match what we do. That’s because we focus just as much attention on what goes through the pipes as in the infrastructure itself. By ensuring that all of the different data sets are organized, combinable, and connectable to other data sets, at the appropriate levels of granularity, we ensure that marketers can squeeze all of the insights from their data.

Find out how the world’s best marketers, including Lyft, Yelp, Zynga, Walmart and Postmates, use Singular to expose deep ROI insights to increase marketing performance at

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