You don't write separate campaigns per product. You load a catalogue once and the AI works out who gets which pitch.
· Updated · 2 min read
This is the part people can't quite believe: you don't write separate campaigns for each product you sell. You load your product catalogue (what you sell, who typically buys it, the angle that lands) once. From there, for every single prospect the engine weighs role, company and industry signals and decides, automatically, which product to lead with and how to say it.
Add as many products as you sell, each with its own description, value proposition, capabilities and demo guidance. Every account works from that one source, so there is no folder of disconnected campaign briefs.
Define the titles that actually buy each product: operations, production, quality, IT, finance, C-level. The AI recognises the role behind a job title, in any language, and matches it to the right group before anyone is contacted. A generic title such as “Manager” is never enough on its own, and a prospect whose fit stays unclear is skipped.
A plant manager gets downtime and OEE, the number they are measured on every morning. A quality manager on the exact same list gets scrap, rework and traceability, and never hears about machine utilisation. A CFO gets cost-per-unit and payback period. Nobody wrote three campaigns. The AI wrote three conversations from one catalogue.
For every prospect the model has to return a structured decision (which product, which persona, which angle) before it writes a word, and bare prose without that decision fails closed. The choice is recorded with every send, so the conversation that follows stays with that product: when a reply arrives, the AI continues on the product that thread is about and never switches offers mid-thread.
A catalogue does not have to be variations on one offer. The illustrative picker on the home page runs industrial valves, MES software, cyber insurance and IT services through the same flow, because the engine reads whatever products you load and decides which one fits the person in front of it. That is also why the platform is not tied to one sector: machine builders and exporters, factories and industrial suppliers, software and IT, insurance, telecom, banking, logistics, services and trading.
Once conversations run, the catalogue starts reporting. Product Intelligence shows product performance, persona interest, market and feature demand and persuasion performance, straight from real conversations.
Several products across several markets can run from one installation. KPIs are kept per account and per product, so you can see which parts of the catalogue and which markets are actually converting.
Product knowledge is the part you will keep editing. In Test Lab you play a buyer, see which product the AI chose and the agent, rules, knowledge and model behind the answer, correct the product description on the spot and re-run the same scenario, then compare the old answer and the new one side by side before anything goes live.
More about this product: META CRM Bot
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