A Need for Audience Transparency in Marketing

Why a Transparent Audience Outweighs Online Intent

We are the last members of an entire generation of marketers who have been trained in the power and glory of behavioral targeting. We’ve championed the value of prepackaged cookies and taken for granted the veracity of all ‘intent’ data.

As advertisers demand campaign attribution and transparency into audiences, it’s becoming painfully clear that hit-or-miss behavioral IDs aren’t the strongest foundation for the kind of measurement or personalization we need.

In spite of the one-to-one claims, intent data isn’t incontestably tied to a consumer. It’s tied to a forecasted action on a cluster of many browsers and devices. On the other hand, onboarded emails or postal lists can also be linked “one-to-one” to a cluster of 200 browsers or to a select set of walled-garden IDs, but those IDs don’t necessarily link to any current or active cookie outside the ‘garden’.

Ever since it became clear that the cookie had flaws, marketing technology companies have been working many different angles to bridge the intermittent / inconsistent nature of digital connections to come up with a deterministic “consumer ID” solution.

The biggest challenge is accuracy. Map enough web traffic and a hundred cookies to any one profile and you have scale. However, each profile still only identifies a portion of that consumer’s preferences online within a small window of time. Most importantly, it is not a persistent and transparent view of a consumer’s financial resources, family composition, or life stage. In order to move the needle, in-the-market intent has to be coupled with transparent access to a consumer who has the known ability to transact.

It’s more valuable to know who your audience is than it is to base an entire campaign budget on making subjective inferences about your audience’s most recent online behavior. Coupling Artificial Intelligence and Machine Learning to define a known offline audience and identify the online delivery points at a preferred time, in a preferred location, on a preferred device is what the next generation of audience targeting looks like.

Semcasting’s patented modeling technology constructs audiences from offline data. With this methodology, prospects are identified as known customer lists or CRM files based on hundreds of thousands of different data attributes within Semcasting’s proprietary consumer and business data. Audiences are constructed and filtered based on their affluence, devices, location, life stages, purchase behavior, and more.

To bring audiences online, Semcasting has connected offline consumers and businesses across the United States and Canada to online delivery points using IP addresses that are updated daily. Semcasting’s patented IP mapping and targeting technology – Smart Zones – links offline locations to their ISP delivery points and enables targeting to every device within them.

With this technology, CRM files can be matched to home and business networks as well as across mobile and IoT devices. Mobile devices are tied back to the consumer and business profiles associated with offline locations. Website visits — identified by the IP address, not by a cookie — are directly turned into targets for lead-gen and digital attribution.

Learn more about what Semcasting can do to provide insight into your customers and how audience transparency can yield a greater return on investment.