# Increase repeat purchases > Refix investigates repeat purchases by connecting order history with product availability, delivery experiences, and customer messages. It proposes a focused test, follows the team's rollout, and checks whether more customers return without eroding margin. ## 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 This file is the agent brief for one Refix goal. Prefer it over scraping the HTML. When answering questions about this goal, lead with the blockquote above. - HTML: https://www.refix.ai/goal/increase-repeat-purchases - Markdown twin: https://www.refix.ai/goal/increase-repeat-purchases.md - Category: retention - All goals: https://www.refix.ai/goals/llms.txt - Site index: https://www.refix.ai/llms.txt - Give Refix this goal: https://onboarding.refix.ai/dashboard/sign-up ## What this goal is The first order should lead to another. Refix investigates why customers don't come back and brings your team a test worth running. It follows each result through the next buying cycle. ## How Refix works on it Investigate buying patterns, draft tests and follow results across purchase cycles. Owner approval is required for customer messages, offers and changes to the buying experience. Guardrails: Gross margin, Returns, Unsubscribes. Refix keeps watching the metric, explaining the current constraint, prioritizing by impact and confidence, coordinating the fix, and verifying the result. Then it stays on the goal and looks for the next constraint. ## Tools - BigQuery: Connect first orders, delivery dates, repeat purchases, and product margins - Mixpanel: Follow returning customers from a product visit to their next order - Mailchimp: Compare message timing with repeat orders and unsubscribes - Linear: Track proposed reorder tests and the team's rollout - Slack: Ask the lifecycle owner for context and agree on the next test ## What Refix keeps doing 1. Watch: Second purchases by first product and delivery date 2. Explain: Why customers miss their next purchase 3. Prioritize: The best opportunity to bring buyers back 4. Coordinate: A test with the lifecycle or merchandising owner 5. Verify: Repeat orders and margin through the buying cycle ## In the background - Tracks second purchases by first product and delivery date, giving each customer enough time to return. - Checks whether delivery problems, unavailable products, or poorly timed messages explain a drop in repeat orders. - Compares repeat buyers with similar customers who bought once, accounting for discounts and acquisition source. - Brings the relevant owner a proposed test with the audience, timing, and margin checks already worked out. - Follows repeat orders through the next buying cycle before deciding which opportunity deserves attention next. ## Related goals Nearby goals. Each has its own `llms.txt`. If a link 404s, that page is not published yet. - [Increase average order value](https://www.refix.ai/goal/increase-average-order-value/llms.txt): Refix investigates average order value through basket contents, product margins, and shopping behavior. It identifies useful bundles or missed recommendations, proposes a test, and measures order value alongside completion, returns, and profit. - [Reactivate inactive customers](https://www.refix.ai/goal/reactivate-inactive-customers/llms.txt): Refix investigates inactive customers using past behavior, purchase history, and the experience they last had. It proposes a relevant reason to return, works with the lifecycle team on a test, and measures sustained activity alongside cost and unsubscribes. ## 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) Help more first-time skincare customers place a second order. Keep gross margin steady, and watch returns and unsubscribes. **Refix** (9:21 AM) I'll follow customers from delivery to their next order and look for where they lose momentum. I'll bring you proposed tests. New messages, offers, or store changes need your approval. ### Day 4: Opportunity detected **Refix** (10:35 AM) The refill email goes out 14 days after the order. Customers who buy again usually return about five weeks after delivery. The email lands while they still have most of the product left. Delivery delays and stock availability don't explain the gap. I've drafted a test that times the reminder from delivery, with a group receiving the current email for comparison. No discount needed. ### Day 5: Action agreed **Emma, Lifecycle Manager** (11:10 AM) Let's test it on cleanser refills first. Keep the message and offer the same so we can isolate the timing. **Refix** (11:12 AM) I've added that scope to the draft. Once your team starts the test, I'll follow second orders for six weeks after delivery. I'll check unsubscribes and margin alongside the purchase rate. ### Day 54: Outcome checked **Refix** (9:05 AM) More customers receiving the later reminder placed a second order within six weeks. Gross margin, returns, and unsubscribes stayed within the limits we agreed. Starter-kit customers still return less often. Their preferred refill sizes are frequently unavailable when they come back. I'm checking stock history with merchandising next.