Quantcast

What Stevin gets out of Quantcast

Quantcast combines audience intelligence with programmatic and has a clear point now that third-party cookies are falling away: it builds audiences in ways that lean less on those cookies. For cookieless targeting that is relevant. The honest note is that audience models make a promise about the audience that you cannot see yourself, and that overlap between channels stays invisible as long as everything sits apart. We see advertisers stall on this: the targeting works, but the campaign data is not in the broader reporting and no one knows whether the same people are already being reached through other channels. The platform delivers reach, not the overview. Stevin runs as a layer on top, connects the campaign data to your reporting through the API and flags overlap between channels. A person sees the conclusion first, then comes a shift in budget.

What you pair it with

Choosing Quantcast makes sense if you want targeting to lean less on cookies, but you get an audience model you do not inspect yourself. Count on a connection with your broader reporting, otherwise the reach floats free of the rest. The data is available through the API. The real question is whether you are not already paying for the same people through other channels, because audience overlap is exactly what you do not see when the campaign runs in a silo. Without that overview you steer on reach instead of on added value.

Common mistakes

• →Trusting an audience model you cannot inspect yourself.
• →Leaving campaign data in a silo, so overlap with other channels stays invisible.
• →Paying for the same audience twice because no one lays the channels side by side.
• →Steering on reach instead of on what the channel genuinely adds.