our stack for activating and converting trials

Reddit r/AI_Agents News

Summary

A B2B SaaS company explains their stack for converting trial users, using an AI agent (Aimdoc AI) to handle inbound and trial setup, combined with a single human email and automated feedback loops that ship fixes before trial ends.

One of the biggest issues b2b saas companeis have is making the most out of existing website traffic and activating new trials. the core problem is that b2b buyers today have an increased preference for trying your product without a demo from a sales rep. companies with a sales led motion think this is a simple as slapping a sign up on the existing product. this never works. you end up driving trial sign ups that never activate. you'll end up comparing yourself to other b2b saas companies with PLG DNA. you can't take a product that was traditionally sold via a sales led process and make it product led overnight. in fact, it might simply never work unless you make it the top priority at your company for multiple successive quarters. it is a lot of work. this isn't realistic for many companies. we've managed to unlock the incremental revenue without rebuilding our entire product and GTM motion from scratch. here is how: AI agent that handle holds the customer through the inbound funnel (Aimdoc AI) this is the core of what allows us to provide a great buyer experience on our website and in our product once a trial is started. the AI will answer questions from anonymous visitors on our website, tells us what company they're at, qualifies them and can funnel them to a demo if they want it or to a trial if they want to self serve Once they're in a trial, it uses the product in front of them to setup the trial based on it's training and what it knows about the user At least one human touchpoint for us, this is one human written email at a key point in the trial. our reps look at the data coming through the agent platform Aimdoc (their company, page views, clicks, questions they asked the AI, use cases they shared to the AI, where they got stuck, etc.) and relationship data in the CRM, and use it to craft one, very well timed email Claude (of course) We have a few really good daily tasks that help us quickly iterate on trial feedback. We have a daily task that takes data from email, sessions from Aimdoc and Slack channels with customers and we extract issues or areas where customers or new trials get stuck (uses MCP servers for slack and aimdoc). We have Claude review Linear, see if an existing ticket exists, if it doesn't it will create one. If it is a bug, our coding agent will pick it up and create a PR with a fix. This allows us to ship fixes and enhancements immediately. So new trial accounts will sometimes run into something or suggest an improvement, and see the fix shipped before their trial ends. other SaaS companies, how are you handling this?
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