Early on, Mintlify's co-founders performed the unscalable work of manually migrating new customers and even improving their grammar. This "extra mile" service, reinforced by Y Combinator's Paul Graham, was a key driver in sparking initial customer love and adoption.

GoProposal viewed high-touch, proactive onboarding as part of their acquisition cost. Before a trial user even entered their credit card, the team would manually set up their account with brand assets. This "shock and awe" approach wowed customers and dramatically increased conversion.

For years, Superhuman required every new user, including investors, to complete a personal onboarding session and provide a credit card upfront. This counterintuitive, high-touch process established value and created the product's most passionate advocates, with the highest NPS and lowest churn.

Instead of a simple trial, AirOps runs a 4-5 week paid pilot with a highly structured onboarding. This process, which includes calibrating the customer's brand voice, builds immense trust and ensures they "get to great," leading to an extremely high conversion rate to annual contracts.

For sophisticated AI tools requiring deep business context, a purely self-serve onboarding often fails. Plurium validates its PLG motion by initially using human consultants for setup to ensure data accuracy and gather context, then building those learnings into an automated, self-service flow over time.

Early enterprise customers won't invest time to become proficient with a complex data tool. Founders must join their meetings, operate the software for them, and surface insights to demonstrate value. This manual "data monkey" role is crucial for driving initial adoption.

Before writing code, manually perform the customer's workflow as a service. This unsexy approach ensures you deeply understand the process, enabling you to build a superior automated solution later. It's about fulfilling the task first, then building the software.

Initially building a tool for ML teams, they discovered the true pain point was creating AI-powered workflows for business users. This insight came from observing how first customers struggled with the infrastructure *around* their tool, not the tool itself.

Successful onboarding isn't measured by feature adoption or usage metrics. It's about helping the customer accomplish the specific project they bought your product for. The goal is to get them to the point where they've solved their problem and would feel it's 'weird to churn,' solidifying retention.