Every channel says it is working. Only one of them is telling the truth. Marketing mix modelling shows the real, causal return of every channel you run, not the return each platform claims for itself.
Automated Workflows moves the budget before the number ever reaches a meeting.
Channel reallocation, live. The true return of every channel, ranked, with the case for moving budget already built.
This is the rhythm of a single week, running underneath every channel you already use.
A channel deck pulled by hand from five dashboards, defended in a meeting nobody enjoys. A spreadsheet reallocation someone has to justify on a call, working from a hunch instead of a number. A fraud report that lands after the invoice is already paid, when the money is already gone. Automated Workflows removes all three: the model runs continuously, the reallocation case is built before the meeting exists, and fraud protection blocks the spend at the point of waste rather than reporting it weeks later.
Last-click attribution tells you which channel happened to be there at the end. It does not tell you which channel actually caused the result. Marketing mix modelling shows which channels are truly driving revenue, not merely correlated with it, and controlled, in-market testing confirms the real, causal lift behind that finding, not a guess based on whichever platform got the last click before conversion.
By the time the reallocation case reaches your channel lead, it has already survived the argument you would otherwise have in the room. Illustrative example: a gap like one channel’s true incremental ROAS running at 1.4x against another’s 2.3x is exactly the kind of finding last-click reporting alone would never surface.
Every pound of ad spend passes through layered, multi-signal fraud protection before it is placed, while it delivers, and after it clears, so invalid spend gets caught and blocked rather than flagged in a report that arrives after the invoice does.
For example: around $30,000 a day of fraudulent spend is caught and blocked before it is ever paid (illustrative example). That is money that stays in the budget instead of leaving it.
A dashboard that shows a problem is not the same as a system that recommends the fix. Every underperforming channel, every fatigued placement, every likely-to-churn segment gets scored, ranked, and turned into a specific recommended move, ready for the team to approve and act on.
This is the real substance behind the “AI at work” language used across the platform: a ranked action list.
If your team runs multiple brands, regions, or business units on the same platform, performance benchmarks build automatically across every one of them. What one brand’s campaign proves about a channel, an audience, or a creative pattern strengthens the baseline every other brand measures against, without anyone running a separate analysis to make it happen.
For an in-house team managing more than a single brand, this compounding effect is easy to miss until you are the third brand benefiting from the first one’s mistake.
Spend, conversions, and traffic get a rolling 14-day forward look for every campaign you run, refreshed continuously as the week’s decisions land.
When Thursday’s reallocation happens, Friday’s forecast already reflects it, so the plan you walk into next Monday with is never more than a few days stale.
Every advertising and messaging channel on the platform is wired end to end, not a partial integration bolted on for a logo wall: 15 advertising channels and 5 messaging channels, twenty in total, each with full publish, status, actions, and reporting built in from day one. Alongside them sits a connector library of 79 platforms spanning the CRM tools, commerce systems, and messaging channels marketing teams already run. Nothing on this list is a partial build waiting on a follow-up release.
Book a working session. Bring your own channel mix, and we will show you what the true incremental return looks like, this week, on your own numbers.
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