Executive Summary

GlowGuide stands at the inflection point between early-stage beauty tech product and scalable, retention-driven growth engine. With 523 opt-ins to date, zero active campaigns or segments in Customer.io, and a 44-event Amplitude taxonomy that has never been connected to a lifecycle program, the opportunity is as stark as it is urgent: every day without automated lifecycle flows is a day of compounding user churn and wasted acquisition spend.

This report delivers the complete lifecycle automation infrastructure for GlowGuide — from platform assessment through production-ready email copy, flow architectures, broadcast calendars, A/B testing frameworks, and a measurement system that ties email engagement to in-app activation and revenue. Every deliverable is built to ship, not to "consider."

Our platform discovery revealed a critical gap: GlowGuide has the technical infrastructure (Customer.io with 3 channels configured, 20 people properties, and 17 custom events; Amplitude with 44 active event types) but zero operational lifecycle programs. No campaigns are running. No segments are built. No automated flows exist. The entire subscriber base — women aged 25–54, spending heavily on aesthetic treatments, and highly motivated by proof and data — is receiving no post-signup engagement whatsoever.

The strategic response is a two-flow lifecycle architecture plus an 8-broadcast rolling calendar, all supported by a rigorous A/B testing framework and cross-platform measurement system:

• Flow 1 (Signup → Install): A 4-email sequence deployed over 72 hours, engineered to convert signups into app installs by leveraging urgency, social proof, personalization, and GlowGuide's unique value proposition of data-driven treatment tracking. Every email includes A/B subject line variants, wireframe-ready layout specifications, and OneLink deep-link CTAs.
• Flow 2 (Install → Activate + Return): A 5-touchpoint journey triggered on app install, designed to drive the critical baseline photo, first treatment log, and sustained return behavior over Day 1 through Day 7. This flow directly attacks the 40–60% install-to-churn rate that defines the beauty tech category.
• Broadcast Calendar (8 sends across 2 weeks): A precision-targeted, multi-channel campaign calendar spanning email, push, SMS, and in-app — each send focused on a single behavioral bottleneck, with cross-channel suppression logic to prevent fatigue and protect users already progressing through automated flows.
• A/B Testing Framework: 17 discrete tests across flows and broadcasts, all structured for 50/50 splits at 95% confidence, prioritizing subject-line creative swings that maximize learning within a constrained 523-subscriber universe.
• Measurement Framework: A three-platform analytics infrastructure (Customer.io + Amplitude + AppsFlyer) with specific KPI targets, funnel configurations, dashboard requirements, and weekly reporting templates that connect email opens to app activation to subscription conversion.

The projected impact targets are concrete: >15% signup-to-install conversion sustained over 30 days, >30% baseline photo completion within 72 hours of install, >25% next-day return rate for activated users, and >2% campaign click rates — up from the current 0% across every metric. This program transforms GlowGuide's lifecycle from a silent void into a measurable growth driver.

Overview

GlowGuide’s lifecycle flows are engineered to systematically convert new subscribers into high-value, engaged app users. These Customer.io automations are mapped specifically to the critical breakpoints seen in the journey from ‘opt-in’ to ongoing activation: first, moving users from signup to install, then from install to active, sticky behavior. Each flow leverages real product triggers, personalization, and behavioral branching. All timing, messaging, and branching logic is tuned to the expectations of GlowGuide’s primary audience: data-driven women 25–54 who routinely invest in aesthetic treatments and want proof, not guesswork.

Flow 1: Signup → Install Flow

Business Goal

Bridge the value gap from “signup” to first app install, reducing friction and maximizing the chance a lead becomes a real user. Early dropout is the #1 driver of wasted acquisition spend in beauty tech.

Entry Trigger

User Created event with a valid ‘email’ attribute.

Email Sequence & Logic

Email Touchpoints

Branching and Exit

• Any 'Application Installed' event at any point ends the flow.
• Non-installers after 72h age out; suppression rules prevent future install prompts.

Segment Details

Flow 2: Install → Activate + Return Flow

Business Goal

Convert new installers into active users by driving the first high-value action (photo check-in) and encouraging sustained engagement over the first week. Reduces Day 1 and Day 7 drop-off — critical to LTV.

Entry Trigger

Application Installed event

Logic Sequence (Text Diagram)

Email Touchpoints

Branching and Exit

• Completing baseline check-in and first series log exits user from future nudges.
• If "Application Opened" in last 5 days, user ages out of re-engagement step.

Segment Details

Implementation Notes

A/B Testing Framework for GlowGuide Lifecycle Emails

Overview

GlowGuide’s early lifecycle program is your opportunity to turn sign-ups into engaged, long-term subscribers—and ultimately, paying users. Every email in Flow 1, Flow 2, and the key launch broadcasts represents a lever to increase engagement and conversions. But with just 523 opt-ins to date, sample size is the main constraint. This testing framework is designed to help you maximize learning per send, prioritize statistically meaningful subject line tests, and extract actionable insights—even if reaching significance takes time.

Primary A/B Test Plan: Flow Emails and Broadcasts

Each test is structured for rapid, interpretable learning in Customer.io or similar ESP UI. Every entry below includes:

Flow 1 (4 Emails)

Email 1

• Hypotheses:
• If urgency framing (“Your skin journey starts here”) is used, then open rates will increase because new users are motivated to get started immediately.
• If personalized framing (“You’re in, {{first_name}}”) is used, then open rates will increase because seeing their own name feels exclusive and welcoming.
• Variant A: “Your skin journey starts here”
• Variant B: “You’re in, {{first_name}}”
• Metric: Open Rate
• Sample Split: 50/50, minimum 200 total, 95% confidence

Email 2

• Hypotheses:
• If benefit framing (“See what your treatments are really doing”) is used, click rate will rise because users want proof of results.
• If curiosity framing (“Your personalized skin plan is ready”) is used, open rate will rise because recipients are intrigued by something just for them.
• Variant A: “See what your treatments are really doing”
• Variant B: “Your personalized skin plan is ready”
• Metric: Open Rate
• Sample Split: 50/50, 95% confidence

Email 3

• Hypotheses:
• If FOMO framing (“Don’t lose your first check-in window”) is used, open rate will increase because people want to avoid missing something important.
• If social proof framing (“Other members are already tracking”) is used, open rate will increase because users follow the lead of their peers.
• Variant A: “Don’t lose your first check-in window”
• Variant B: “Other members are already tracking”
• Metric: Open Rate
• Sample Split: 50/50

Email 4

• Hypotheses:
• If personalization (“{{first_name}}, your recommendations are waiting”) is used, open rate will increase due to individual attention.
• If value promise (“We picked treatments just for you”) is used, open rate will increase because it suggests unique, high-value content inside.
• Variant A: “{{first_name}}, your recommendations are waiting”
• Variant B: “We picked treatments just for you”
• Metric: Open Rate
• Sample Split: 50/50

Flow 2 (5 Emails)

Email 1

• Hypotheses:
• If curiosity framing (“What actually works for your skin?”) is used, open rate will be higher because users are searching for clarity in a noisy category.
• If transformation framing (“Watch your glow evolve, step by step”) is used, open rate will be higher for those motivated by end-result vision.
• Variant A: “What actually works for your skin?”
• Variant B: “Watch your glow evolve, step by step”
• Metric: Open Rate
• Sample Split: 50/50

Email 2

• Hypotheses:
• If ‘before/after’ theme (“See every change, no more guesswork”) is used, open rate will rise because photo progress is tangible proof.
• If pain-point theme (“Tired of wasting money on products?”) is used, open rate will rise because it strikes at a key user frustration.
• Variant A: “See every change, no more guesswork”
• Variant B: “Tired of wasting money on products?”
• Metric: Open Rate

Email 3

• Hypotheses:
• If streak mechanic (“Day 3 streak: you’re on a roll!”) is used, open rate will rise because progress is addictive.
• If trusted guide (“How our experts track what works”) is used, open rate will increase for those who value expert insight.
• Variant A: “Day 3 streak: you’re on a roll!”
• Variant B: “How our experts track what works”
• Metric: Open Rate

Email 4

• Hypotheses:
• If next-action framing (“Time for your next photo: ready?”) is used, click rate will rise due to explicit guidance.
• If science credential (“50,000+ studies inform your plan”) is used, open rate will rise for evidence-driven users.
• Variant A: “Time for your next photo: ready?”
• Variant B: “50,000+ studies inform your plan”
• Metric: Open Rate

Email 5

• Hypotheses:
• If confidence promise (“Feel confident in every choice”) is used, open rate will increase for goal-driven users.
• If curiosity gap (“What changed since you started?”) is used, open rate will increase for those seeking self-reflection.
• Variant A: “Feel confident in every choice”
• Variant B: “What changed since you started?”
• Metric: Open Rate

Key Broadcast Sends (Week 1)

Broadcast: Monday Week 1

• Hypotheses:
• If urgency (“The most important email you’ll get today”) is used, open rate will spike for users who fear missing out.
• If ease (“You can do this in 60 seconds”) is used, open rate will rise for users overwhelmed by typical routines.
• Variant A: “The most important email you’ll get today”
• Variant B: “You can do this in 60 seconds”
• Metric: Open Rate

Broadcast: Wednesday Week 1

• Hypotheses:
• If data framing (“Is your skin data working for you?”) is used, open rate will rise among measurement-oriented readers.
• If emotional journey framing (“How your glow story begins”) is used, open rate will increase among aspirational users.
• Variant A: “Is your skin data working for you?”
• Variant B: “How your glow story begins”
• Metric: Open Rate

Broadcast: Saturday Week 1

• Hypotheses:
• If personalized/conversational (“{{first_name}}, let’s check your week!”), open rate will rise due to relationship-centric tone.
• If direct action (“See this week’s results now”), open rate will rise among action-takers.
• Variant A: “{{first_name}}, let’s check your week!”
• Variant B: “See this week’s results now”
• Metric: Open Rate

Statistical Requirements and Constraints

How to Read Results in Customer.io

Customer.io provides direct A/B testing UI:

• Each experiment automatically splits traffic and tracks open/click rates by variant.
• Use the “A/B test” report for each email or broadcast. Watch for confidence indicators (at least 95% confidence before calling a winner—but investigate directional trends before).
• If one variant is leading by >8pp after 200+ sends and confidence is rising, consider declaring a winner if segment size is too small for full significance.
• Call a winner when: The platform declares >95% confidence and the numerical gap is meaningful to your business (open rate up 6–10pp or unique click-through >2pp).
• If test is inconclusive: Keep rolled up subject line learnings for future broadcasts; consider combining multiple sends as a meta-analysis.

Takeaways and Next Steps

With a finite early audience, every email is an experiment in what sparks action with real, time-pressed beauty consumers. This playbook ensures that GlowGuide’s lifecycle program systematically builds insight into:

• The urgency, curiosity, and personalization angles that resonate
• Whether progress tracking, expert proof, or emotional “glow” is the best motivator
• How subject lines translate into meaningful downstream engagement

Execute these tests for all new launches. Update your messaging library with every winner—then refine the journey as your list grows and windows for statistical significance shorten.

Appendix: Sample Size/Statistical Calculator Reference

• “Email A/B test sample size” (ConvertKit; see https://www.convertkit.com/resources/email-ab-sample-size)
• “Litmus Sample Size Calculator” (https://www.litmus.com/resources/email-ab-testing-sample-size-calculator/)

Answering Your Core Question

This broadcast calendar for Month 1 addresses the critical challenge: reaching users who have not entered— or have fallen out of—automated onboarding and retention flows. By activating this "untouched middle," GlowGuide accelerates the core user behaviors that drive retention, such as taking a baseline photo, building a product routine, and maintaining check-in momentum. Every broadcast stands alone with a single focus, clear CTA, and tightly defined segment.

Philosophy & Objectives

GlowGuide's approach to Month 1 broadcasts is anchored in three priorities:

Restore and Accelerate Key Behaviors

• Prompt users stalled before their baseline photo or check-in, who might otherwise churn out quietly.
• Motivate routine-building to move them deeper into the app experience.

Test Messaging Hooks at Scale

• Use broad reach, A/B-tested subject lines and content variables to find what unlocks each user segment. Early learning shapes future campaigns and triggers.

Orchestrate a Cohesive Engagement Cadence

• Coordinate across email, push, SMS, and in-app so no user receives more than one broadcast per day—and automate suppression for those in active flows, to prevent message fatigue.

The Calendar: Rationales & Roles

Each send targets a distinct bottleneck or opportunity, sequenced to avoid collision and drive cross-channel lift:

Week 1

Week 2

Strategic Considerations

Audience Targeting & Size Estimates

Messaging Design & Success Metrics

Broadcasts vs. Automated Flows: How Suppression Works

GlowGuide's automated flows (Flow 1: onboarding, Flow 2: re-engagement/retention) take priority for any user currently progressing through them, especially if messaging content overlaps. Suppression is enforced such that:

• No user receives a topic-duplicate broadcast while in a corresponding flow step (e.g., users in the onboarding sequence don't get baseline photo emails from broadcasts)
• Daily throttling is applied: Max 1 email per user per day, counting both journeys and generic campaigns
• Eligibility resets dynamically as users exit flows or complete blocking behaviors (e.g., check-in completed)

Why It Matters — Impact Beyond Email

GlowGuide's Month 1 broadcast strategy is how early "stuck" users become lifelong active customers. This approach:

• Prevents the steepest early drop-off points from becoming permanent leaks
• Builds a habit and data foundation for deeper personalization in months 2–3
• Surfaces the messaging hooks (by channel and segment) that will make both journeys and brand editorial succeed
• Establishes a modern, multi-channel cadence that respects the user's experience, supports the brand's premium positioning, and maximizes total LTV.

Next Steps: Operationalization

• Review audience membership weekly; flex upcoming slots to adapt to real behavior patterns
• Archive AB test results and feed winners into journey flows for rapid optimization
• Monitor channel mix performance—deprecate poorly performing sends, double down on breakouts

Primary KPIs by Flow

The lifecycle program consists of two critical flows, each with distinct success metrics tied to business outcomes:

Flow 1 Metrics: Signup → Install Attribution

Email Performance by Step

Track granular conversion at each email touchpoint to identify drop-off points:

Email 1 (Welcome):

Email 2 (Value Reinforcement):

Email 3 (Social Proof):

Email 4 (Personalized Reminder):

• Open rate: Target >20%
• Final conversion rate: Track as recovery mechanism

Cross-Platform Attribution

• Overall conversion rate (target: establish baseline, then +20%)
• Time from signup to install (median, 75th, 90th percentile)
• Install rate by clinic/market via zipcode analysis (if available)
• Attribution window: 72 hours (matching flow duration)

AppsFlyer Integration:

• Track installs with "email_campaign" parameter
• Monitor impression-to-install where data available (currently limited to TikTok)
• Cross-reference Customer.io campaign IDs with install events

Flow 2 Metrics: Install → Activate + Return

Activation Cascade Tracking

Primary Funnel (Sequential):

1. Install → Baseline Photo (Email 1 impact)

1. Baseline → First Log (Email 3 trigger)

• Progression rate: Target >40% of baseline completers
• Time between baseline and first log: Track median

1. First Log → Return (Emails 4-5 impact)

• Next-day return rate: Target >25%
• 7-day re-engagement conversion: Target >15%

Time-Based Cohort Analysis

Track user progression with time deltas for each conversion:

• Install to first check-in: Target <48 hours for 50% of users
• Baseline photo to routine building: Track correlation
• Email send to app open: Attribution window analysis

Amplitude Funnel Configuration

Master Funnel: Install → Subscription Ready

Build this exact funnel sequence in Amplitude:

1. Application Installed (Entry event)
2. User Created (Account setup)
3. Application Opened (First session)
4. checkin_completed (with had_photos:true) (Baseline captured)
5. checkin_completed (with is_first_series_checkin:true) (First progress log)
6. Application Opened (Day 2+ sessions) (Return behavior)
7. [Premium Actions] Shop Now Clicked / Shop Partner Clicked (Monetization signals)

Segmentation Cuts

Analyze funnel performance across:

Behavioral Tracking

Key Events Beyond Funnel:

• Session duration by visit number
• Feature exploration patterns (photos, routines, recommendations)
• Drop-off points within critical flows

AppsFlyer Attribution Framework

Milestone Events Configuration

Track these 3 critical milestones per acquisition source:

Cost Efficiency Analysis

Key Questions to Answer:

• Which ad sources produce users who actually activate? (not just install)
• What's the true cost per activated user by channel?
• Which sources have the best email engagement rates?

Attribution Windows

• Install attribution: 7 days (AppsFlyer default)
• Activation attribution: 14 days (extended for email-driven behavior)
• Cross-reference with Customer.io flow completion rates

Dashboard Requirements & Reporting Cadence

Customer.io Dashboard

Flow Performance View:

• Conversion rates per email step
• Drop-off point identification
• Time-to-convert distributions
• A/B test winner tracking
• Suppression logic effectiveness (users in flows vs. broadcasts)

Campaign Health Metrics:

• Send volume vs. deliverability rates
• Engagement trends by cohort
• Revenue attribution (when subscription data is available)

Amplitude Dashboard

Funnel Analysis:

• Install→baseline→first log→day-2 return progression
• Segmented by cohort week and entry source
• Time-to-event analysis for each funnel step
• User journey path analysis (where do people go after baseline?)

Behavioral Insights:

• Session patterns by lifecycle stage
• Feature adoption correlation with email engagement
• Retention curves by activation milestone reached

AppsFlyer Dashboard

Media Source Performance:

• Cost per install vs. cost per activation vs. cost per first check-in
• Channel-specific user quality scoring
• Attribution data quality monitoring (flag impression data gaps)

Cross-Platform Attribution:

• Install source vs. email engagement correlation
• Paid media efficiency when combined with lifecycle emails
• Organic vs. paid user lifecycle performance comparison

Weekly Reporting Template

Performance Summary (Week-over-Week)

Flow 1 Performance:

• Signup volume: [Number] (±X% WoW)
• Install conversion rate: [X]% (±X pp WoW)
• Best performing email: Email [N] with [X]% click rate
• Attribution insight: [Channel] users [X]% more likely to install

Flow 2 Performance:

• New installs: [Number] (±X% WoW)
• Baseline completion rate: [X]% within 72h (±X pp WoW)
• Day-2 return rate: [X]% (±X pp WoW)
• Email engagement lift: [X]% open rate improvement

Channel Performance:

• Top traffic source: [Channel] ([X]% of installs)
• Most engaged cohort: [Week] installs ([X]% activation rate)
• A/B test results: [Winning variant] increased [metric] by [X]%

Next Week Actions:

1. [Specific optimization based on data]
2. [A/B test to launch]
3. [Audience segment to focus on]

Monthly Strategic Review

• Lifecycle program ROI calculation
• Cross-platform attribution model refinement
• User journey optimization opportunities
• Technology integration improvements needed

Success Criteria & Optimization Triggers

Green Flags (Program Working)

Yellow Flags (Needs Attention)

Red Flags (Immediate Action Required)

Implementation Roadmap

Week 1: Foundation Setup

• Configure Amplitude funnel with exact event sequence
• Implement Customer.io campaign tracking parameters
• Audit AppsFlyer event mapping completeness
• Set up cross-platform user ID mapping

Week 2-3: Dashboard Building

• Build Customer.io flow performance dashboards
• Configure Amplitude cohort and segmentation views
• Set up AppsFlyer cost-per-activation tracking
• Create automated weekly reporting template

Week 4+: Optimization Cycle

• Launch first round of A/B tests based on baseline data
• Implement attribution model refinements
• Begin cohort-based performance analysis
• Scale successful tactics to broadcast campaigns

This measurement framework transforms GlowGuide's lifecycle program from an email marketing expense into a measurable growth driver, with clear attribution to user activation and revenue outcomes.