Cross-Channel Silos: Data Rich, Information Poor

laurenmoores“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Lauren Moores, vice president of analytics at Dstillery.

Silos. We use the term as a way to refer to systems, people, data or thoughts that do not interact with each other.

The mobile channel is not as siloed as it was a year ago, particularly as most of the discussion since then has focused on cross-screen capabilities: advertising, marketing, tracking and insights. Silos, however, still exist, particularly with cross-screen data.

Although not true for every marketer, it strikes me that cross-screen capability, in terms of both science and transactions, is yesterday’s issue. Cross-channel metrics are the current focus. We are capable of finding audiences, either deterministically or probabilistically, across different digital channels, and serving them advertising on different devices. But then what? How did that audience perform? What was the reach? Which combination of media, screen and creative worked? And are all necessary?

The two biggest hurdles to the adoption of cross-channel marketing are cross-channel attribution and path-to-purchase insights, according to eMarketer. Similar to the early days of online advertising, many marketers will not commit dollars to a channel that they cannot measure effectively, whether or not they know their audience is using multiple devices and screens. I still remember listening to a Sony marketing executive at an industry conference 10 years ago tell us that his executive team did not believe that online influenced offline. This was the same conference where the chief marketing officer of Samsung described passionately his strategy for buying up a majority of the online advertising available on top sites. Ultimately, we have been able to provide measurement in online to back up this strategy, but cross-channel is still in its early stages.

Consider the process of providing cross-channel insights from a combined desktop-mobile campaign. For typical online advertising, we have tags and cookies, as well as internal and third-party ad-serving reporting, which provide the ability to cull some idea of attribution and path-to-purchase for a marketer’s audience. Third-party, multitouch attribution also allows the marketer to go beyond last-click measurement.

But on the mobile side, it is trifurcated. For the mobile web, cookies exist on Android but not iOS devices. So only half of that domain is measurable. For mobile apps, each is its own mini-browser, with no cookie tracking. To collect data, an app needs a software development kit. Each one of these data streams is separate, requiring its own systems, science and knowledge to pull together cross-channel insights.

We use science to transact the cross-screen campaign, and until we achieve the Pareto optimal scenario of a cross-screen, cross-media identifier, we need to use science to provide the measurement metrics. Idiosyncratic data streams can still be difficult to mine for information, even if you already have the ability to transactionally handle a cross-screen campaign. I spoke with one marketer who told me that she was unable to get a simple cross-screen, post-campaign reach number from any of the providers that she has been working with – something that should be table stakes.

Three years since the introduction of cross-channel marketing, we continue to be deficient in our ability to interpret the data. It’s high time to resolve that issue. As digital marketing history has repeatedly shown, tomorrow’s issue will be here before we know it.

Follow Lauren Moores (@lolomoo), Dstillery (@dstillery) and AdExchanger (@adexchanger) on Twitter.

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