SaaS

FrictionHunter

warningProblem

"What's something founders think will grow their buisness... But usually doesn't?"

psychologyPotential Solution

An AI-based process optimization platform that analyzes bottlenecks in the customer journey, automatically identifying response times, follow-up quality, and churn during the onboarding phase for businesses.

groupTarget Audience

SaaS founders, sales teams, and small-scale digital service agencies suffering from customer churn and looking to increase operational efficiency.

paymentsRevenue Model

Three-tiered subscription model: Starter (for individuals/small teams), Growth (for medium-sized businesses), and Enterprise (for customized integrations and API access).

Action Plan

CRM integration with automated response time and follow-up analytics

Funnel visualization showing stages where users drop off most frequently during onboarding processes

AI engine that analyzes customer interaction texts and provides a 'comprehensibility' score

Weekly automated reporting system listing friction points and solution recommendations

Scoring

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Source: entrepreneuropen_in_new

AI Prompt

Build a full-stack SaaS application using Next.js 14 (App Router), Tailwind CSS, and Shadcn UI. The core functionality is a 'Friction Analysis Dashboard'. Implement a Drizzle ORM schema with PostgreSQL for 'Companies', 'Interactions' (emails/support tickets), and 'FunnelSteps'. Create API routes under /api/v1/ to handle CRUD operations for logging interaction data and tracking user onboarding progress. Build a central dashboard that calculates 'Average Response Time' and 'Drop-off Rate' per onboarding step using custom aggregate functions. Include a middleware-protected auth system using NextAuth.js. Ensure the UI includes a data-visualization component (using Recharts) to display funnel drop-offs. The app must have a modular directory structure: app/ (routes), components/ (reusable UI), lib/ (drizzle db config), and hooks/ (data fetching). Add a 'Friction Report' generator that queries the DB for outliers in response times and generates a text-based summary for the user.