RTB House

What Stevin gets out of RTB House

RTB House runs entirely on its own deep-learning models for retargeting with dynamic product ads, and on that specialism it often performs well. The honest story is that the hood is shut: you get strong results reported, but little grip on how, and on how much of it is genuinely extra. With retargeting that is a familiar trap, because it easily claims conversions that were coming anyway. We see advertisers stall on this: the performance is not compared with other channels, and the claimed value is rarely tested against what would have happened without those ads. The platform optimizes in its own black box. Stevin runs as a layer on top, reads the results through the API and puts them in your total picture, so you see where the channel overlaps with the rest. A person judges, Stevin keeps it honest.

What you pair it with

Choosing RTB House means trusting a model you do not set yourself, so most of the steering is in how you judge the channel next to your other sources. Count on a connection with your tracking and reporting, otherwise the claimed value floats free. The data is available through the API. The hard question is whether those conversions were genuinely extra or double-count with your other retargeting and with search. Without something that lays that side by side, you sail blind on a dashboard that always brings good news.

Common mistakes

• →Not laying the results next to other channels, so no idea about double-counting.
• →Trusting the black box without testing what was genuinely extra.
• →Taking retargeting revenue at face value while part of it was happening anyway.
• →Steering on a dashboard that structurally brings good news without context.