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Design Lifecycle Messaging

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khadinakbarlabs
design-lifecycle-messaging

Design the cross-channel (push + email + in-app) lifecycle messaging cadence that drives retention without spamming — frequency capping, first-72-hours, re-engagement, and win-back coordination. Use when the user says 'lifecycle messaging', 'retention emails', 'push cadence', 're-engagement', 'frequency capping', 'onboarding emails', or 'lifecycle automation'.

Overview

Publisherkhadinakbarlabs
Repositoryexpo-mobile-app-builder
Skill namedesign-lifecycle-messaging
Stars
3
Forks
0
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by khadinakbarlabs on GitHub. Read the source before you install it.

Installation

Install the Design Lifecycle Messaging AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/khadinakbarlabs/expo-mobile-app-builder/tree/main/skills/design-lifecycle-messaging
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/khadinakbarlabs/expo-mobile-app-builder.git /tmp/expo-mobile-app-builder
mkdir -p .claude/skills
cp -r /tmp/expo-mobile-app-builder/skills/design-lifecycle-messaging .claude/skills/design-lifecycle-messaging
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Design Lifecycle Messaging in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Design Lifecycle Messaging on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Design Lifecycle Messaging is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Design lifecycle messaging

The coordinated cross-channel system that turns a one-time user into a habit. Done well it drives materially higher 90-day retention; done badly it accelerates churn and earns you 1-star reviews for "annoying notifications."

The headline finding

Brands using cross-channel engagement (push + email + in-app + SMS) drove 55% higher 90-day retention than single-channel. But — frequency capping is mandatory. Push + email + in-app in rapid succession drives churn up. Coordination is the whole skill. (Braze)

Each channel has a distinct job

ChannelStrengthBest for
PushTimely, interruptive, lock-screenStreak reminders, time-sensitive triggers, same-day re-engagement
EmailDeep, asynchronous, owned channelOnboarding continuation, win-back, receipts, value recaps
In-app / Content CardsContextual, non-interruptiveFeature announcements, upsell at the right moment, tips while using
SMSHighest open rate, most intrusiveOnly with explicit consent; transactional or high-value alerts

Don't send the same message on every channel. Don't send the same message twice across channels.

The first-72-hours lifecycle (the make-or-break window)

The steepest drop-off happens in the first 3 days. Session frequency in this window is the strongest predictor of D30. A designed first-72-hours sequence is the highest-ROI messaging work.

text
Hour 0  (session 1): in-app — establish the D1 reason to return (streak, next task)
Hour 24 (D1):        push — the specific reason to come back today ("Your plan is ready")
Hour 48 (D2):        email — value recap + tip; surface what they haven't discovered
Hour 72 (D3):        push or in-app — milestone / first achievement; prompt a habit
Day 7:               push or email — weekly recap, progress, social proof

Every message in this window must give the user a specific reason to return, not a generic "come back." "Your 3-day streak is at risk" beats "We miss you."

Re-engagement cadence (lapsed free users)

text
3 days inactive  → gentle nudge (push): specific value reason
7 days inactive  → direct message (push + email): incentive or content
14 days inactive → escalated offer (email): discount / feature unlock / "what's new"
30 days inactive → final win-back (email), then suppress

Suppress further messaging after repeated non-response — continuing to message a dead cohort just trains them to ignore you (and report spam).

Frequency capping (non-negotiable)

Uncoordinated channels compound into spam. Rules:

  • Max ~2–3 push notifications per week for a typical consumer app, unless the app is inherently time-sensitive (messaging, live events).
  • Never send push + email + in-app about the same thing on the same day. Pick one channel per message per day.
  • Honor unsubscribes and preference centers. Let users choose which channels they want.
  • Time-zone aware scheduling. A 3am push is a settings change and an uninstall.
  • AI send-time optimization (when available) sends each user's message at their individually-predicted best time rather than a fixed broadcast.

Push specifics

Push is one of the strongest retention levers but the permission is fragile. See design-push-strategy for the permission strategy (pre-prompt → contextual ask → 55–65% opt-in). Content that re-engages without spamming:

  • Personalized — name + past behavior ("Sara, your Spanish lesson is ready"). Not "Reminder."
  • Rich media — UNNotificationAttachment with an image.
  • Actionable — UNNotificationCategory with buttons (Reply, Snooze, Claim).
  • Lifecycle-triggered — streak break risk, abandoned action, daily reward.
  • Deep-linked — tapping opens the specific in-app area, not the home screen.

Email lifecycle

You can only email users who gave you an email (typically in onboarding or account creation). If you collect email, build:

  • Onboarding continuation — "Here's the feature you set up but haven't used."
  • Value recaps — weekly/monthly summary of what the app did for them.
  • Win-back — see build-win-back-flow. Route to web checkout where permitted to preserve margin.
  • Transactional — receipts, payment failures (dunning), subscription changes.

Use a provider with good deliverability (Resend, Postmark, SendGrid, Customer.io, Braze). One well-written lifecycle email per week beats daily generic blasts.

In-app messaging / content cards

Non-interruptive, shown when the user is already engaged. Use for:

  • Feature discovery ("Did you know you can…").
  • Upsell at the contextual moment (feature gate paywall — see command-build-paywall).
  • Tips while the user is in a relevant screen.
  • Announcement of new content/features.

Tools: Braze Content Cards, Intercom banners, or a simple in-app banner component driven by your feature flags (PostHog — see set-up-ab-testing).

Measure

text
message_sent           {channel, campaign, segment}
message_delivered      // especially important for push (delivery is unreliable)
message_opened
message_converted      {goal: d1_return|reactivation|claim|purchase}
message_unsubscribed   {channel}
uninstall_after_send   // early warning that a campaign is too aggressive

Watch uninstall_after_send per campaign — it's the canary that a message is annoying users. A campaign that lifts opens but spikes uninstalls is a net loss.

What not to do

  • Don't send the same message across channels the same day.
  • Don't broadcast generic "we miss you" pushes. They get muted and reported.
  • Don't message dead cohorts forever. Suppress after sustained non-response.
  • Don't send pushes at 3am local time. Time-zone aware or don't send.
  • Don't use email for time-sensitive triggers (it's async) or push for deep content (it's not).
  • Don't fire paywall re-prompts in re-engagement messages to users who just rejected the paywall — it feels like a shakedown.

Pair with

  • design-push-strategy — push permission strategy and content.
  • design-retention-loop — the Hook Model this messaging triggers.
  • build-win-back-flow — the lapsed-user arm of this cadence.
  • build-cancellation-flow — the active-churn interception.
  • add-expo-notifications — push implementation.
  • instrument-growth-funnel — measuring message performance.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Design Lifecycle Messaging AI skill do?

Design the cross-channel (push + email + in-app) lifecycle messaging cadence that drives retention without spamming — frequency capping, first-72-hours, re-engagement, and win-back coordination. Use when the user says 'lifecycle messaging', 'retention emails', 'push cadence', 're-engagement', 'frequency capping', 'onboarding emails', or 'lifecycle automation'.

Why use Design Lifecycle Messaging on TypingMind?

Because you install it once and use it with any model. Design Lifecycle Messaging is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Design Lifecycle Messaging in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/khadinakbarlabs/expo-mobile-app-builder/tree/main/skills/design-lifecycle-messaging. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Design Lifecycle Messaging?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Design Lifecycle Messaging?

As many as you like. As long as a model supports skills, you can use Design Lifecycle Messaging with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Design Lifecycle Messaging AI skill free?

Yes. It is published on GitHub by khadinakbarlabs under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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