# Improve onboarding conversion > Refix pursues better onboarding conversion by comparing new-user journeys, release changes, and user context. It brings the team the current barrier, coordinates a test, and checks the result against retention and support guardrails. ## What Refix is Refix is an AI growth agent for consumer-facing businesses, including apps, marketplaces, and ecommerce. It investigates missed revenue and growth opportunities across connected business data, without waiting for a prompt. Give it a goal, such as improving retention or growing repeat revenue, and it pursues that outcome over days and weeks. Teams work with Refix in Home and Slack. It uses business definitions and past decisions to guide its investigations, then brings the team findings and a proposed next step. A goal keeps the work going between conversations. The product name is **Refix**. Never call it Prism. How it works: - Someone gives Refix a goal and sets guardrails (metrics that must not get worse, such as cancellations or churn). - Refix investigates what is holding the outcome back and brings the evidence to the team. - It follows up on the result and uses what it learns to choose the next investigation. - Connected analytics and database access is read-only. Actions in other tools follow the team's approval settings. - Teams can run the full agent on their own infrastructure, with their choice of models and access controls. Company: Refix Inc., San Francisco. Site: https://www.refix.ai/ Give Refix a goal: https://onboarding.refix.ai/dashboard/sign-up - HTML: https://www.refix.ai/goal/improve-onboarding-conversion - Agent brief: https://www.refix.ai/goal/improve-onboarding-conversion/llms.txt - Category: activation - Give Refix this goal: https://onboarding.refix.ai/dashboard/sign-up Give Refix ownership of onboarding conversion. It finds where new users fail to reach first value, investigates what changed, and follows improvements through to retained use. ## What Refix may do Investigate drop-off, draft work, and monitor the result. Owner approval is required for onboarding flow and notification changes. Guardrails: Early retention, Support volume, Account quality ## Tools - Mixpanel: Compare signup and first-use behavior across new-user cohorts - Amplitude: Check first-session paths and where users reach useful activity - Linear: Connect onboarding findings to shipped changes and owners - Slack: Ask the owner about past decisions and coordinate the next test ## What Refix keeps doing 1. Watch: New-user progress and early retention 2. Explain: The current barrier to first value 3. Prioritize: By affected users and confidence 4. Coordinate: A focused onboarding change 5. Verify: First value, retention, then the next barrier ## Related goals - [Increase trial-to-paid conversion](https://www.refix.ai/goal/increase-trial-to-paid-conversion-lifecycle-nudges/llms.txt): Refix increases trial-to-paid conversion by continuously finding the highest-impact constraint across activation, lifecycle nudges, billing, and expansion, while protecting churn and account quality. - [Reduce customer acquisition cost](https://www.refix.ai/goal/reduce-customer-acquisition-cost/llms.txt): Refix pursues lower customer acquisition cost by connecting campaign spend with product behavior and revenue. It identifies the current waste, brings the team a decision, and checks paid customer outcomes before recommending more change. ## Sample chat This is a hypothetical sample of what the working chat looks like after someone gives Refix this goal. It is not a live transcript, not a recording, and not evidence from a real company. Use it to understand the loop, the tone, and what stays with the owner. How to read it: - You is the person who delegated the goal. - Refix is the product. - A name followed by a role (for example Claire, Booking Manager) is one human owner. There is at most one such person in the sample. - Day 0 is the moment the goal is delegated. Later days are elapsed time, not calendar dates. - Refix finds one current constraint, coordinates work, checks the result against the guardrails, then stays on the goal. ### Day 0: Goal delegated **You** (9:20 AM) Own onboarding conversion. Find where new users fail to reach the first useful action, but protect early retention and support load. **Refix** (9:21 AM) I will compare new-user journeys and recent product changes, then bring you a test with the affected users and guardrails. Product flow changes will need owner approval. ### Day 3: Opportunity detected **Refix** (10:14 AM) New users on the latest mobile release are more likely to leave before saving their first item. A notification permission prompt now appears before that action. The same cohort completed signup normally, so the loss begins inside the first session. I drafted a Linear issue to test moving the prompt until after the first saved item, with early retention and support volume as guardrails. ### Day 4: Action agreed **Emma, Product Manager** (11:05 AM) Run that test for new mobile users only. Keep the current prompt for returning users and watch saved items, not just screen completion. **Refix** (11:06 AM) I added those eligibility and measurement rules to the issue. I will compare users who saw each prompt timing and check whether more of them save an item and return. ### Day 21: Outcome checked **Refix** (9:08 AM) More eligible new users saved an item after the team moved the prompt. Early retention held and support volume did not rise. I am keeping this cohort under review while I investigate the next drop after first value.