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Create a referral program that rewards users for inviting friends
Create an AI writing assistant that helps draft product copy
Redesign the onboarding flow to reduce drop-off
Introduce a premium pricing tier with analytics and collaboration features.
15
Starting discovery
Gathering information about your idea.
Starting with the core problem to shape all follow-up questions.
What is the primary growth challenge you're trying to solve?
Help me understand the core issue driving this feature idea. This will shape the entire direction of our discovery.
1
Low organic acquisition
2
High churn rate
3
Poor activation
4
Low referral rate
Problem Space
Problem
Target users
Competitive Context
Reward preference
Constraints
Success Criteria
Thought Process
Proposed Solutions
Based on your discovery answers, here are three approaches ranked by growth impact.
Double-Sided Reward
Both referrer and invitee receive credits. Creates viral loop through mutual incentive alignment.
Natural viral loop from mutual incentives
Both parties motivated to convert
More complex credit tracking for two sides
What you'll need to build
1
Referral Link Generator
Unique trackable links with UTM params and invite code attribution
2
Credit Ledger System
Track pending, earned, and redeemed credits for both referrer and invitee
3
Notification Pipeline
Email/push triggers for invite sent, accepted, and reward earned milestones
Single-Sided Credit
Referrer earns credits for each successful invite. Simpler to build, lower viral coefficient.
Fastest to ship with minimal backend
Easy for users to understand
Invitees have no incentive to sign up
What you'll need to build
1
Invite Code Engine
Generate and validate unique referral codes per user with expiration and usage limits
2
Referrer Wallet
Track earned credits, redemption history, and configurable payout thresholds
3
Conversion Tracker
Attribute sign-ups to referrers and verify qualifying actions before issuing credits
Gamified Leaderboard
Social competition with tiered rewards. High engagement but risk of gaming the system.
Highest engagement through competition
Escalating tiers drive sustained referrals
Vulnerable to abuse and self-referrals
What you'll need to build
1
Leaderboard Engine
Real-time ranking system with weekly, monthly, and all-time views with tie-breaking logic
2
Tiered Rewards System
Define reward tiers (Bronze, Silver, Gold) with escalating incentives and unlock thresholds
3
Anti-Gaming Layer
Detect and prevent self-referrals, duplicate accounts, and referral abuse patterns
Double-Sided Referral Rewards Program

Double-Sided Referral Rewards Program

Both referrer and invitee receive credits. Creates viral loop through mutual incentive alignment.

Overview

Current referral rates are low (<2%) because there is no incentive for existing users to invite others. Paid acquisition costs are rising, making organic growth channels critical for sustainability. The goal is to increase organic user acquisition by 30% through a mutual incentive referral program. Both the referrer and the new sign-up receive platform credits, creating a natural viral loop that drives sustained growth.

User Stories

As a paying user, I want to share a referral link with friends so that we both earn credits when they sign up.
As a new user, I want to receive a welcome credit from my friend's referral so that I can try premium features for free.
As a product manager, I want to track referral attribution and reward redemption so that I can measure program ROI.

Feature Requirements

Name Priority Effort
Generate unique referral links per user		 P0 Each user gets a unique URL; link tracks clicks and sign-ups
Track referral attribution across devices		 P0 Referral credit persists across mobile, desktop, and email opens
Credit ledger for referrer and invitee		 P1 Both users see credits in account; credits apply to next billing cycle

Success Metrics

Referral Rate
8%
From 2% baseline, targeting Q2 launch — tracked via referral analytics
New Users via Referral
500/mo
Currently ~40/mo organic — target by end of Q2, tracked via referral attribution
Referral CAC
$12
vs. $42 paid acquisition — credit cost per converted referral, reported monthly

Knowledge Base

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Drop files here or click to upload PDF, DOCX, TXT, Markdown, or paste a URL
Added sources
User Segmentation Report — Power Users & Converts.pdf
3.2 MB · Uploaded 5 days ago
Active
Stripe Billing Integration Docs
stripe.com/docs/billing · Linked
Active
User Segmentation Report — Power Users & Converts.pdf
Active
Growth Research · Internal

User Segmentation Report

Identifying high-propensity referral segments for Q2 2026 program design

Executive Summary

This report profiles the two user segments most likely to drive high-quality referrals for an upcoming incentive program: Power Users (daily active, long-tenured) and Recent Converts (paid upgrade within the last 30 days).

Together these segments represent 18% of MAUs but generate 64% of observed organic word-of-mouth signals — inbound referral traffic, social mentions, and self-reported "heard from a friend" survey responses.

Recommendation: Build segment-specific reward ladders rather than a single flat incentive. The two segments refer for different reasons and respond to different motivators.

Segment 01 — Power Users

Daily active for 30+ consecutive days, tenure > 6 months, NPS ≥ 9.

Segment size
12,400
% of MAU
8%
Avg ARR
$4,200
Referral propensity
3.8×

Key behaviors

  • Average 7.2 features used per week (vs. 2.1 baseline)
  • Send collaboration invites to teammates 4.6× more often than average users
  • 84% have customized workspace branding — strong ownership signal
  • Top outbound channels: Slack communities, Twitter/X, in-person networks

Why they refer

Qualitative interviews (n=24) indicate power users refer primarily for belonging and status — they see themselves as "the person who brought the team onboard" and enjoy the social capital of recommending tools that work.

Monetary incentives were rated as least motivating by this segment. Recognition and early access ranked highest.

Segment 02 — Recent Converts

Completed a paid upgrade within the last 30 days.

Segment size
15,800
% of MAU
10%
Avg ARR
$2,100
Referral propensity
2.4×

Key behaviors

  • High engagement honeymoon — avg 5.1 sessions in first week post-upgrade
  • Actively evaluating ROI; likely to share tool with decision-makers at other companies
  • Top outbound channels: LinkedIn posts, direct email to peers, internal team rollouts
  • Referrals peak at day 7–14 post-conversion, then decay sharply

Why they refer

Recent converts refer to validate their purchase decision. Bringing a peer along reduces cognitive dissonance about a new subscription, and helps them unlock team features they paid for.

This segment responds well to team-oriented rewards (seats, credits toward team plans) more than individual cash incentives.

Recommendations

1. Build two reward tracks, not one

Power users → status-based (tier recognition, early-access features, leaderboards). Recent converts → utility-based (team seats, platform credits, onboarding credits for referred team).

2. Time the prompt to the moment

Power users should see referral prompts after milestone completions (e.g. 100th file created, 10th teammate invited). Recent converts should see prompts on day 7 of their paid subscription, during the peak propensity window.

3. Measure separately

Do not report a single "referral rate" KPI. Track conversion by segment: referrals-per-power-user and referrals-per-recent-convert. Aggregated metrics will hide the signal.

Open question: Should a user who is both a power user and a recent convert (tenure > 6mo + just upgraded plan) see the power-user track or the convert track? Suggest A/B test in pilot.
Prepared by Growth Research March 2026