If you've been using a general-purpose AI tool for marketing (like ChatGPT, Claude, Gemini, Copilot, or others), you've probably done a lot of unspoken work to make it useful.
You've corrected its tone a hundred times. You've explained what your customers actually care about. You've fed it product details, past campaigns, the angle on the launch you're planning, the competitor you're trying to outflank. You've taught it which words your brand never uses, and which phrases land every time.
That accumulated context is the difference between AI output you can ship and AI output you have to rewrite. It's also the single biggest reason people don't switch tools, even when a better one shows up, because starting over feels like losing months of work.
This is a guide to doing it the other way: exporting everything you've taught your current AI, then bringing it with you.
What "context" actually means for marketing
Most AI tools store memory as a generic grab-bag: your name, your job title, a few interests, a handful of preferences. That's fine for a chat assistant. It's not enough for a marketing partner.
For marketing, the context that matters is more specific. There's brand voice or guidelines (the tone, vocabulary, phrases you use, words you avoid, formatting rules, etc.). Audience and Ideal Customer Profile (personas, segments, the language your customers actually use, the pain points that keep them up at night etc.). Business basics covers what your company does, what you sell, and how you position it. Channels and assets means where you publish and the recurring formats you reuse. Campaigns and past work equates to what you've shipped, what worked, what flopped, drafts you've reused. Goals and metrics are the KPIs that matter, current targets, the numbers leadership keeps asking about. People and projects could be teammates, agencies, freelancers, or recurring initiatives. Compliance and constraints covers regulated language, banned topics, and legal disclaimers. And then the long tail of stored notes that don't fit a category but still matter.
When that context is missing, AI output drifts toward generic. When it's present, the same model can write a campaign brief that reads like it came from someone on your team.
The trick: ask the AI to export itself
The fastest way to capture all of that is to ask the tool you've been using to dump it for you. Modern AIs with memory features will, if you prompt them clearly, return a structured export of everything they've learned about you. This works by preserving your exact phrasing, organized by category, in a single block you can copy.
A good extraction prompt does a few things at once. It tells the AI you're switching and need a full export. It asks for every memory verbatim, not summarized. It gives the AI the full list of categories to look for, so the structured ones (brand voice, audience, campaigns, KPIs, compliance) don't get skipped. And it asks the AI to confirm at the end whether the export is complete or if more remains, because these tools sometimes return partial sets and call it done.
We've written and tuned the exact prompt for marketing context. Grab it from the Fynch import page: one click, copies to clipboard. Run it in a fresh chat in whichever tool you've been using, and you'll get back a single code block with everything.
A note on each tool. ChatGPT pulls from its "Saved memories" plus learned context across chats. This is usually the most thorough export. Claude returns its memory plus context from recent conversations. Gemini's memory is shorter but covers the basics. None are perfect; if you spot gaps after the first run, follow up with "anything missed?" and run it again.
What to do with the export
Once you have the block, you're ready to import. In Fynch, you paste it into context settings and Fynch parses it into the things a marketing AI actually uses — your brand voice profile, audience and ICP, product and positioning, campaign history, and constraints. You review what came across, fix anything that's off, and start briefing.
If you end up trying a different tool, the same export still works as a starting point. Most platforms with a memory or system-instructions field will accept it. The structured, dated format is portable on purpose.
A few things worth knowing
You don't have to import everything. For example, if you only want your brand voice imported and would rather build the rest fresh, paste only the relevant section. Partial imports are fine.
You can re-import any time. If you keep using your old AI alongside your new one for a while, run the prompt again later and merge the new context in. Nothing is locked.
You can edit and curate. A good import flow shows you what was learned and lets you correct, delete, or rewrite. Your context shouldn't be a black box.
And if your current AI stored anything sensitive (like credentials, internal financials, customer PII, etc.), strip it out of the export before importing it anywhere. No marketing AI needs those things to do its job.
Try it on Fynch
The whole flow takes about a minute. Grab the prompt, run it in your current tool, paste the result into FynchAI, and your first brief already sounds like your brand.
