How to personalize mobile onboarding by campaign without rebuilding the app

Paid install campaigns fail quietly when every user sees the same generic onboarding. Your Meta creative promises meal planning; screen two talks about generic productivity. CPI looks fine while activation tanks. Engineering's fix is often "we'll add a build flag for the fitness campaign," which ships two weeks after the ad spend is gone.

Personalize onboarding by campaign without rebuilding the app by combining attribution traits, remote flow branches, and fast publish cycles. Rheo resolves a flow manifest per user based on attributes (campaign, media source, creative, locale) and renders native screens. No new binary. No navigator refactor per campaign.

This guide covers attribute design, branch rules, operational workflow, and how paywall timing fits when billing UI stays in RevenueCat or Superwall.

Why campaign-specific onboarding matters

Signal	Generic onboarding	Campaign-aligned onboarding
Message match	Creative promise fades	Continuity from ad to screen 1
Time to value	Long explainer for everyone	Short path for high-intent cohorts
Paywall timing	One size fits all	Sooner for discount ads, later for trust ads
Measurable lift	Blended metrics hide wins	Per-campaign funnels

Attribution tools (AppsFlyer, Adjust, Branch, SKAN postbacks summarized in your data warehouse) tell you which campaign drove the install. They do not author UI. The gap between attribution data and onboarding experience is where remote flows live.

Architecture overview

Install → Attribution SDK → Traits on Rheo resolve
                ↓
         API returns manifest for channel + traits
                ↓
         Native onboarding screens
                ↓
         Optional: RevenueCat paywall node
                ↓
         Activation events → analytics

Your app integrates once:

• Rheo SDK at first open (or deferred entry point)
• Attribution SDK (AppsFlyer, etc.)
• Pass campaign fields as traits on resolve

Growth operates continuously:

• Author flows per campaign or campaign group
• Publish without App Store review
• Run experiments within a campaign cohort

Traits that actually drive branches

Avoid fifty traits on day one. Start with fields your attribution stack reliably sends:

Trait	Example values	Branch use
media_source	facebook, google, tiktok	Platform-appropriate copy tone
campaign	summer_fitness_2026	Dedicated screen sequence
adset	lookalike_us_25_34	Offer emphasis
creative	video_meal_prep_v3	Hero image match
af_status / equivalent	Organic vs non-organic	Skip paid-only urgency
locale	de-DE	Language and compliance

Normalize naming in a spreadsheet before you build twelve flows. summer_fitness and Summer_Fitness_2026 should not be two branches by accident.

Trait freshness

Attribution callbacks can arrive after first paint. Patterns:

Pattern	When to use
Default flow, swap on trait update	Attribution usually within 2 seconds
Short splash while traits resolve	Strict campaign match required
Hold branch until campaign non-empty	Prevent mis-assignment to default

Document your app's behavior so growth knows if first screen can change mid-session.

Branch design patterns

Pattern A: One flow, conditional screens

Single canvas with branches: if campaign contains fitness → fitness benefit screens, else → default.

Pros: One experiment framework, easier maintenance

Cons: Canvas complexity grows

Pattern B: Separate channels per campaign group

Channels: first_open_fitness, first_open_finance, first_open_default. Resolver picks channel from traits.

Pros: Clean analytics per channel, simpler canvases

Cons: More channels to maintain

Pattern C: Hybrid

Default channel with top 3 campaigns as overrides. Everything else falls through.

Pros: Balances ops and clarity

Cons: Requires governance (when to promote campaign to dedicated channel)

Team size	Recommended pattern
Small growth team	C with 2-3 overrides
Active paid spend across many lines	B for top spenders
Early product-market fit	A until campaigns stabilize

Worked example: fitness campaign

Campaign creative: "Track macros in 30 seconds."

Onboarding path:

1. Hero: meal photo + "Track macros in 30 seconds" (matches ad)
2. Single choice: primary goal (cut / maintain / bulk)
3. Two-screen product demo (logging flow only)
4. ATT prompt (after value, not before)
5. RevenueCat paywall with trial (paywall UI in RC, not Rheo)

Default path for organic users:

1. Generic value prop
2. Broader feature tour (4 screens)
3. Signup earlier in sequence
4. Paywall after signup

Same app binary. Different manifests. Publish new creative match the same day marketing swaps ad assets (hero image URL in manifest).

Personalization without paywall ownership

Rheo does not manage paywall templates. For campaign-specific pricing or trial length, pass offering identifiers to RevenueCat or Superwall based on the same traits:

Campaign type	Journey (Rheo)	Paywall (RC/Superwall)
Discount ad	Shorter path, urgency copy on screen 2	Promotional offering
Brand story ad	Longer narrative	Standard offering
Retargeting	"Welcome back" beat	Win-back offering if entitled

Journey and paywall experiments should not run on the same users without a design doc. Sequence: nail campaign onboarding in Rheo, then test offering in RC for that cohort.

Operational workflow

Day	Marketing	Growth / product
-7	Brief new campaign, share creative assets	Clone flow template
-3	Finalize tracking links	Wire trait mapping in staging
-1	QA install on test devices	Verify branch + funnel events
0	Launch spend	Monitor step funnel hourly
+3	Read CPI vs activation	Iterate copy on worst drop step
+14	Scale or kill campaign	Archive or promote channel

Publish cadence: Copy and image swaps are minutes. New branch arms are hours, not sprint weeks.

Analytics: per-campaign funnels

Required events (conceptual):

Event	Use
flow_started	Denominator per campaign
step_completed	Step drop-off
flow_completed	Onboarding done
paywall_presented	From RC + Rheo edge
trial_started	RevenueCat

Join campaign trait on every event. Dashboard questions you should answer:

• Which campaign has best step 3 completion?
• Where does tiktok traffic fall off vs facebook?
• Does shortened path increase trial starts without hurting week-4 retention?

Experiments within campaigns

Once baseline campaign flow exists, test inside the cohort:

Test	Example
Path length	3 vs 5 screens for same campaign
ATT timing	Before vs after demo
Social proof	With vs without testimonial screen
Paywall entry	Direct vs after signup

Hold campaign trait constant. Change only one flow variable per experiment.

Common failures

Failure	Fix
Traits never reach SDK	Debug attribution → Rheo callback chain
Every campaign gets default	Normalize campaign string matching
Creative mismatch persists	Update manifest hero, not just ads
Paywall shows wrong price	Sync offering ID mapping table
Ops overload (50 flows)	Consolidate to campaign groups

Compliance and store policy notes

Personalization must not deceive users about what the app does. Campaign-specific onboarding should reinforce the real product, not promise features you lack. Regional rules (GDPR consent timing, kids apps) may require locale branches independent of campaign.

Integration checklist

• Attribution SDK sends campaign fields to Rheo traits on resolve
• Default flow exists for organic and missing attribution
• Top campaigns have mapped flows or branches
• Paywall offering IDs documented per campaign group
• Step funnels visible per campaign dimension
• Publish process owned by growth (not release train)

Summary

Personalize onboarding by campaign by passing attribution traits into remote flow resolution, branching native screens without app rebuilds, and keeping paywall UI in RevenueCat or Superwall. Match ad promise to screen one, shorten paths for high-intent cohorts, and measure step funnels per campaign instead of blended activation.

Start for free and publish campaign-specific onboarding flows from the dashboard.