11 Jun

Human Demand On The Power Of Data

The Application Developers Alliance is a non-profit global membership organization that supports developers as creators, innovators, and entrepreneurs. As an active corporate member for nearly two years, I have contributed to working groups, industry papers and events. Recently, I sat down with Mike Schwartz to participate in the “Voices of the Industry” podcast series by DevsBuild.it.

DevsBuild.It is an app industry search engine created by the Application Developers Alliance to help developers build apps and businesses. DevsBuild.It aggregates content, services, and events to meet the needs of developers as creators, innovators, and entrepreneurs.

The episode focuses on how developers can leverage the power of mobile data as a monetization strategy. Publishers invest significant time and money in the development of an application, but struggle to ensure the Lifetime Value (LTV) of a user exceeds the Customer Acquisition Costs (CAC).

The following is an overview of the topics covered in the talk:

Mobile advertising technology is continuously evolving and consumer adoption of mobile is quickly dwarfing traditional desktop consumption. As a result, a significant shift of ad dollars in digital is being allocated to the channel. Unbeknownst to the majority of developers, mobile data generated by user interaction within apps can be leveraged to build significant, residual revenue streams.

While mobile continues to mature, there are two main factors inhibiting its growth: i) market education, and ii) accurate ROI calculations for conversions accounting for multi-touch attribution. While market education is a hurdle faced by many industries, the technical challenge advertisers face trying to show the efficacy of an ad is the true key to continued investment.

Marketers must attempt to connect paid media investment across multiple channels to build an accurate depiction of a campaign’s performance. To do so, the siloed performance reports must be reconciled by matching identifiers from i) mobile, ii) desktop, and iii) social channels – which is no small undertaking. The key is deterministic data.

Deterministic data – or PII – is difficult to scale as it is protected by both i) the consumer, and ii) the publisher. However, it is the only accurate means to connect actions across channels and properly attribute marketing spend to the conversion. As a result of privacy concerns, the industry has developed various inferred methods to connect users across devices. Statistical identifiers (a.k.a. fingerprinting) and probabilistic modeling of relationships between static device IDs are two of the more popular methodologies to develop these cross device bridges.

Both methods rely on certain mobile data attributes – ranging from device IDs, IP addresses, user agent data, etc. – being collected over time and leveraged to develop either a statistical ID for the individual device, or to form a relationship with an associated confidence score between two static device IDs.

There is no industry standard solution currently accepted and adopted, and device-bridging methodologies face numerous challenges with both industry self-regulation organizations as well as legislation in the coming years.

Regardless, mobile publishers have the unique opportunity to collect the various data points necessary for both mechanisms to perform starting now – including device ID matched to PII (if applicable permissions and disclosures are included in the application). This information is not only a valuable means to generate a return on their mobile investment, but is should be a valuable asset to the app owner as well.

Understanding in-app data can enable a publisher to optimize user experience, tweak user acquisition strategies, and much more. For example, user acquisition is typically broken down into two unique periods: i) launch, and ii) post “significant” adoption. Prior to having a significant number of users, a publisher must rely on third party data to be leveraged in a DSP or network. Once a publisher has a significant user base, she should enlist the expertise of a managed DSP buy, where the vendor has the capability to build profiles by analyzing your current users, and build look-a-like modeling for targeting and audience extension.

It is my experience that over 95% of mobile developers do not currently collect or house their own user data. This is a missed opportunity to not only improve user experience and decrease CAC, but a means to establish ancillary revenue streams for data licensing.

It’s a marketers dream to be relevant, timely, and in-context when delivering a paid media placement to a potential customer/user. Data is the currency that enables advertisers the ability to complement a user’s experience and not interrupt it.