Data drives the marketing industry. From a marketer’s perspective, data is time; data is money. Marketing dollars are trustingly thrown at data to build campaign strategies and targeted advertising across all marketing channels.
Despite the time, money and sophisticated technology shifting towards data mining, many marketers still can’t determine proper attribution across channels in a way that accurately measures their brand’s lift and consumer experience. At the root of this is a persistent lack complacency when it comes to properly matching data to an actual consumer in a way that allows advertisers to reach them with relevant and appropriately timed messages.
Unfortunately, for the most part, data targeting has been focused on scale over accuracy, resulting in an upside down model that benefits everyone but the advertiser. The result – the digital data and identity matching industry gets a bad rep by marketers for high cost and low returns. For consumers, the experience is forgettable at best and, at worst, full of skepticism about the source and quality of data fueling targeted ads. The problem is the glut of low fidelity data that has flooded the marketplace over the past decade in both identity resolution across device and data insights. Yet, advertiser priorities have not changed while accuracy is being scrutinized, verified and measured in more ways than ever before.
Today, accuracy in identity resolution and data targeting is a requirement for all marketers. But all this technology has focused so heavily on proxies rather than delivering individual-level targeting, because resolving to the right individual, onboarding data correctly and serving the right consumer relevant ads is not an easy proposition.
Here’s How Throtle Does it Differently
Identify Sources and Context
One key to building robust, accurate data is to know where the data comes from, including its timeliness and its context. Keep in mind the demographic and other online/offline behaviors, not just transactional data in a single moment in time. For example, we all shop for gifts, whether or not they are personally relevant to us. A consumer may at one point have shopped for a baby gift for an expectant friend. Five months later, that consumer has ended up on a mailing list for baby formula and incessantly receives free samples in the mail, although the consumer in point is not a mother nor expecting in the near future. You can see where the discrepancy lies and why knowing the source and context makes this data all the more accurate.
A Fully Deterministic Approach
Marketers must have a deterministic understanding and approach to their data to ensure accuracy. This means ensuring that a single consumer is accurately matched, with definitive proof, to an organization’s corresponding first-party data. This approach ensures that the person is a single user and not generalized under a household or group of consumers. Measuring every interaction across devices can be challenging, but attribute something to the right person and you can identify trends and patterns across all marketing channels. Without accuracy and deterministic matching at the individual level, cross-device attribution is impossible to obtain.
The Identity Graph
Creating this deterministic approach is easily accomplished through a consumer identity graph. An identity graph ensures that all first-party and third-party identifiers for a single consumer reside and are resolved in one place. This is imperative for marketers who want to accurately read consumer behavior and interactions across multiple touchpoints. If you look at everything separately, the picture is hazy and the 360 degree view of a consumer’s core identifiers are lost.
The Results of This Complexity
CONSUMERS: They want to see relevant, harmonized experiences across content. There will be those that complain that after browsing online for new living room furniture, they see cross-device ads from multiple couch vendors for the next three weeks. However, in a world where customer experience is the majority of the battle (according to Gartner and 89% of marketers), when a consumer experience is accurate and relevant, a brand elevates itself above the competition.
ADVERTISERS: Highly accurate targeting is required to reach the same consumer on different channels and devices. Targeting, attribution and defendable measurement can’t happen using inaccurate data; campaigns will produce better ROI because a marketer is able to determine which specific activities are producing the best results
In short, many of the old approaches to collecting accurate data no longer work. Ad and MarTech companies should be held to a higher standard and greater level transparency when it comes to the data that they source and provide.
Throtle is a 2nd generation data onboarding company focused on deterministic matching, identity resolution, and closed loop enablement. Our data centric onboarding approach guarantees the highest level of accuracy, scale, and responsiveness for our clients.