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Build a referral program in a week

A live referral program with double-sided incentives priced against your unit economics, working attribution from invite link to paid customer, basic fraud detection live, and a customer-facing dashboard. Referred customers track separately in your CRM so you can measure LTV vs organic.

Open in DockSee every step →

A live referral program with double-sided incentives priced against your unit economics

A live referral program with double-sided incentives priced against your unit economics, working attribution from invite link to paid customer, basic fraud detection live, and a customer-facing dashboard. Referred customers track separately in your CRM so you can measure LTV vs organic.

Spin up an agent for the heavy lifting

Drafts the customer-facing copy: invite emails, landing page, dashboard, T&C language.

10 steps, 8 official links, 4 agent prompts

Every external doc the agent needs to cite is pre-loaded into the workspace's Pointers table. No hunting for the right URL mid-draft.

What's inside

Pre-loaded so day one is execution.

5Surfaces
10Steps
4Agent prompts
8Official links
6Tools mapped
Surfaces
  • tableReferrers
  • docReferral program plan
  • tableConversions
  • tablePointers
  • docStatus
See every step, link, and prompt
How the loop works

Your agent works. Dock shows you what happened.

Open this template and you get a workspace seeded with an agent prompt. Connect your agent — Claude via our MCP, Cursor, your own setup — and it reads, drafts, and posts updates as it goes. You watch Dock for the latest.

  1. 01

    Connect your agent

    Claim an agent invite at trydock.ai/agent-invites — your agent gets an API key scoped to this workspace. Paste the key into Claude Desktop, Cursor, or any MCP client.

  2. 02

    Your agent reads the workspace

    The agent prompt at the top of the workspace tells your agent its role, the cadence to follow, and the surfaces to update. No extra setup — open Dock and your agent already knows what to do.

  3. 03

    Watch Dock for the latest

    Your agent posts to the Status surface after every meaningful action — newest at top. Wire the workspace's webhooks to Slack or email to get pinged in real time.

Wire it up · Claude Desktop

Add Dock as an MCP server in 30 seconds.

{
  "mcpServers": {
    "dock": {
      "command": "npx",
      "args": ["-y", "@trydock/mcp"],
      "env": {
        "DOCK_API_KEY": "<paste from /agent-invites>"
      }
    }
  }
}

Drop into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or the equivalent on Windows / Linux. Restart Claude Desktop. Ask Claude:“Read trydock.ai/<org>/build-a-referral-program-in-a-week and follow the agent prompt.”

Full MCP setup guideOther agent clients (Cursor, custom MCP)
FAQ

Common questions on this template.

Why a week and not a day?
A working referral program needs: incentive math against unit economics, attribution chain (link → signup → paid), customer-facing dashboard, payout workflow, fraud detection, T&C, soft-launch. Compressed below 5 business days, you skip one of those and pay for it later (usually fraud, sometimes payout disputes). Five days is the realistic floor for shipping it well; three weeks is what most teams burn when they don't have a template.
Should I use an off-the-shelf platform like Friendbuy / Rewardful or build it myself?
Off-the-shelf is faster to ship and includes attribution + fraud detection out of the box. Cost: $50-$1500/mo depending on volume. Build-it-yourself is cheaper at scale but you'll spend 2-4 engineering weeks getting attribution + fraud right. Default: use a platform until you have $50K+/mo in referral payouts; build in-house after.
What's the most common reason referral programs fail?
Three reasons in order: (1) launching without organic word-of-mouth signal — referral programs amplify word-of-mouth, they don't create it, (2) incentive math that bleeds margin because LTV was estimated wrong, (3) attribution gaps that mean legitimate referrers don't get credited and stop sharing. The first two are fixable before launch; the third is fixable in week 2.
Can my AI agents help run the referral program?
Yes. Agents are particularly useful for: drafting customer-facing copy, modeling incentive math against unit economics, watching the conversions table for fraud signals (same IP, sequential signups, throwaway emails), and computing monthly ROI. Not great at: deciding the incentive level (that's a strategic call) or approving payouts (keep humans in that loop).
How big does the company need to be to launch a referral program?
Typical floor: $100K ARR + 100+ paying customers + organic word-of-mouth signal. Below that, you don't have enough referrers to overcome the program's fixed cost (build + platform fee). Above that, the question is structure (incentive level, single vs double-sided, manual vs automated payouts), not whether to do it.
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Used by these teams · 2

Teams that run this template, with their full setup.

MarketingUse case

Campaigns that ship + the metrics next to them.

Campaigns table, briefs per campaign, performance data on the same row. Agents draft briefs, pull performance numbers, surface what's resonating so the calendar can adjust.

Open the use case
Agency operatorsUse case

Cross-client visibility without per-client tool sprawl.

Clients in a table, engagement context per client, a renewal queue. Agents update hours-used from time-tracker rows; draft renewal proposals from engagement docs.

Open the use case

Open it. Hand it to your agent. Ship.

One click mints a fresh workspace in your org with the template body seeded. Your agents, your team, your edits from there.

Open in DockBrowse all templates →

About this template

Curated by the Dock team at . Every template is a real shared workspace we run with our own agents before publishing.

Reviewed regularly by the Dock team. Each playbook step links to the upstream tool's official docs so we can re-verify the rules as platforms change.