Before comparing media buying platforms, check that they work at the same layer. DSPs and ad platforms are execution layers: they buy inventory inside the environments they’re connected to. An autonomous decision layer works above them and decides across all of them. Putting both in the same feature matrix mixes two different jobs, and leads to a shortlist that answers the wrong question.
Execution layer vs decision layer in media buying
Media buying technology works at two layers: the execution layer, which buys inside a platform, and the decision layer, which decides how budget and bids should be distributed across platforms.
| Execution layer | Decision layer | |
| Examples | DSPs, ad platforms, smart bidding | Autonomous decision intelligence |
| What it does | Buys inventory and bids inside its environment | Decides allocation and bids across environments |
| What it sees | Its own auctions and signals | Signals from every connected channel |
| Relationship | Receives decisions and executes them | Sends decisions to the execution layer |
The two layers aren’t substitutes. A decision layer needs execution layers underneath it to act.
Why feature matrices mix up the layers
Feature matrices mix up the layers because both answer “yes” to many of the same questions, even though they mean different things.
“Does it bid in real time?” Both can. “Does it use AI?” Both can. “Does it optimize toward a KPI?” Both can, one inside a platform and the other across them. A matrix built on these questions makes an execution layer and a decision layer look like alternatives, when one sits on top of the other. The result is a comparison of implementations before anyone has decided which job needs doing.
How to compare providers within each layer
Once you know which layer you’re buying, the criteria change.
For the execution layer, the relevant questions are about inventory access, formats, auction quality and reporting within the platform. For the decision layer, they’re about how far decisions reach across channels, how many signals inform each decision, how often the system actually re-evaluates, whether you can audit specific decisions afterwards, and who answers for the outcome. Before either comparison, it helps to confirm which model fits your organization, as covered in how to choose a media buying model.
Where Mainkore sits: not a DSP
Mainkore isn’t a DSP. It’s autonomous advertising decision intelligence that works above DSPs and ad platforms and decides across them.
It works with DSPs such as Adform, DV360, The Trade Desk and Zemanta, and with platforms such as Meta, TikTok and YouTube, evaluating 200+ variables per decision and sending those decisions to the execution layer. That’s why comparing Mainkore with a DSP feature by feature asks the wrong question: the useful comparison is how decisions are made across your platforms and who answers for the result. The difference from programmatic buying is developed in autonomous AI vs programmatic advertising.
FAQ
No. Mainkore is autonomous advertising decision intelligence. It works above DSPs and ad platforms, decides across them and relies on them to execute.
A DSP buys inventory and bids inside the environments it’s connected to. An autonomous decision layer decides how budget and bids should be distributed across several DSPs and platforms at once.
Which layer each option works at, and which operating model your organization needs. Only then compare providers within the same layer.
Our media buying models guide. compares models, not brands, for exactly this reason. Want to see where Mainkore would sit in your stack? Talk to us.
Mainkore. The layer that decides, above the ones that execute.
