Automating FB/IG lead capture with AI?

leadgen

I work with a company that sells electronics - smartphones, TVs, home appliances, that sort of thing - and we've been drowning in DMs and comments from potential buyers. The dream is to build an AI system that automatically replies, saves their info into a CRM, segments them by what they're asking about, and then sends follow-up offers. Basically, make the whole lead gen loop run on autopilot.

Started looking into the stack and immediately hit a wall. The "make it remember conversations" part? Absolute nightmare. Most basic automation tools forget context the second the chat moves to a new message thread. I've seen people hack around it with n8n plus a vector database, but that sounds like a weekend project from hell.

And then there's Meta itself. Someone in the community pointed out that the hardest part isn't even the tech - it's getting the API to play nice. Rate limits hit fast when you're trying to scale, and the platform doesn't exactly roll out the red carpet for automated lead collection.

Right now I'm torn between ManyChat, Zapier, Make, n8n, or diving straight into the Meta API. What I really need to figure out:

Best combo for auto-saving and tagging leads?
How to keep AI context alive across multiple customer conversations?
CRM that actually plays well with this setup?
Any real-world workflows that survived contact with Meta's API limits?

If anyone's built something similar - especially for high-volume product inquiries - I'd love to hear what worked and what burned you.

sleepermode

Honestly, the conversation memory aspect is the biggest headache. Most basic automation tools - think ManyChat or simple webhook chains - have no concept of context across messages. to maintain a coherent thread you'll need either custom logic with a vector database for embedding history, or a platform that natively handles conversation threading (some of the newer CRMs are adding this). I've built something similar using n8n + Pinecone to store message embeddings and retrieve relevant context per user - it's doable but far from trivial. Expect to spend serious time tuning the retrieval logic to avoid hallucinating past details.

sleepermode

Honestly, the hardest part isn't building the pipeline - it's getting Meta to play ball. I've been down this exact road and their API rate limits become a real bottleneck once you push more than a few hundred conversations a day. Zapier paired with Make (formerly Integromat) works for small volumes, but n8n gives you way finer control when you need to handle webhook retries and custom rate limiting yourself.

funnelhacker

Honestly, the ROI on building your own memory layer from scratch is garbage unless you're moving thousands of leads a month. You'll burn 90% of your dev hours debugging context drift instead of closing deals. I've seen teams spend four weeks on a vector DB setup and still have the bot pitch phones to someone who just asked about washing machines - that's a negative campaign ROAS.

If you're scaling fast, start with something that already handles threading and basic recall - ManyChat or HubSpot workflows. Bolt on vector memory only when forgetfulness costs you real revenue. Otherwise you're optimising the wrong metric.