If you’re like most of the marketing and agency leaders we speak with, you struggle with reaching your target audience effectively and efficiently. Budgets continue to tighten, forcing marketers to do more with less. At the same time, behaviors have become increasingly fragmented.
Modern digital marketing tactics promise to help business leaders address these age old challenges once and for all. But these solutions frequently fall short of expectation, often failing to deliver the access they purport to provide. Significant portions of advertising budgets are thus wasted on eyeballs the advertiser never intended to target.
In our experience, the problem starts with the tactics that data providers rely on to build these audiences. Most are built on the assumption that behaviors imply intent. Audience membership (i.e. preferences, intentions, attitudes, etc.) is thus determined exclusively by subjective judgement of behavior and digital consumption. In other words, what people do entirely determines how they are classified. While such judgements are sometimes correct, they are often not.
To do this, we deterministically match (i.e. 1:1 match) online behavior with attitudes and intentions that advertisers want to target. Via machine learning, we use this 1:1 match to identify the digital signals that are most indicative of a specified attitude or intention. We then scale our solution to the wild in order to connect advertisers to consumers that exhibit the behaviors our analysis tells us are indicative of the attitude or intention the advertiser desires.
Our high-performing audiences can be activated directly through Engine Media, or programmatically via data infused PMP’s directly integrated with your DSP of choice or by accessing our inventory in many of the leading DMP’s. If the audience you need isn’t already built, we can develop one on a custom basis in usually less than 2 weeks using either a study you are already running or one we build together from scratch.
Additional ‘First Party’ activation services we offer, include: