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How customer decisioning actually works.

Markin is an autonomous growth-science team for large B2C businesses. It investigates why revenue per customer is stuck, forms its own hypotheses across marketing, product, pricing and technical health, chooses the next best action for each customer, launches it through the systems the business already runs, and proves every one against a randomised holdout.

Decisioning tools choose between the actions your team already built. Markin decides what to build.

Questions people ask

Is Markin a replacement for Braze?
No. Braze is an engagement platform: it builds, personalises and delivers journeys, and BrazeAI Decisioning Studio chooses the best message, channel and timing inside them. Markin sits above that. It decides which commercial opportunity is worth pursuing for each customer in the first place, including opportunities that are not messages at all, such as a pricing change, an onboarding fix or a payment failure. When the answer is a message, Markin launches it through Braze.
How is Markin different from AI decisioning inside an engagement platform?
AI decisioning selects between actions a marketer already created, inside the channels that platform owns. Markin authors the hypotheses itself and is not limited to the campaign surface: marketing, product, pricing and technical health are all in scope. It then executes inside the systems already in place and reads every decision against a randomised holdout, which is how a data science team works rather than how an optimiser works.
Is Markin a CDP?
No. A CDP unifies and distributes customer data. Markin consumes that data and decides what to do with it. Markin has no ambition to be your source of truth, and it does not require you to replace one. If a CDP or a warehouse already holds customer context, Markin reads from it.
Does Markin replace my data science or growth team?
No. Markin removes the arithmetic constraint on how many hypotheses can be tested, not the judgement about which constraints, economics and risks matter. Teams using Markin move from producing analyses to setting guardrails, interpreting results and deciding what gets scaled.