Personalized Onboarding Flows with Deep Link Data

Every user who installs your app got there from somewhere: an ad, a referral link, a social media post, a QR code, or an organic search. That "somewhere" tells you what the user cares about. Deep links carry this context through the install, letting you build an onboarding experience that matches the user's intent instead of showing them a generic welcome screen.

For deferred deep linking mechanics, see Deferred Deep Linking for Personalized Onboarding. For the complete onboarding guide, see User Onboarding with Deep Links.

The Context You Can Capture

Deep links carry data through the install process. Here's what each source tells you:

Source	Deep Link Data	What It Tells You
Ad campaign	Product category, promo code, ad creative	What product/feature attracted the user
Referral link	Referrer name/ID, reward details	Who sent them, social proof context
Content link	Article topic, feature page	What they were reading about
QR code	Physical location, event, product	Where they scanned (in-store, billboard, packaging)
Partner link	Partner name, integration context	B2B or partnership origin
Email link	Subscriber segment, email campaign	Existing relationship context

Implementation Pattern

Step 1: Capture Context on First Launch

// On first app launch
async function initializeOnboarding() {
  const deferredLink = await Tolinku.checkDeferredLink();

  const context = {
    source: 'organic', // default
    campaign: null,
    referrer: null,
    product: null,
    promoCode: null,
  };

  if (deferredLink) {
    const params = deferredLink.params;
    context.source = params.utm_source || 'deep_link';
    context.campaign = params.utm_campaign;
    context.referrer = params.ref;
    context.product = params.product;
    context.promoCode = params.promo;
  }

  onboardingStore.setContext(context);
  return context;
}

Step 2: Choose the Onboarding Flow

function getOnboardingFlow(context) {
  if (context.referrer) {
    return 'referral'; // Acknowledge the referrer, show reward
  }

  if (context.product) {
    return 'product_focused'; // Skip category selection, show the product
  }

  if (context.campaign) {
    return 'campaign'; // Show the campaign-specific landing
  }

  return 'default'; // Standard onboarding
}

Step 3: Customize Each Step

function OnboardingScreen({ context }) {
  const flow = getOnboardingFlow(context);

  switch (flow) {
    case 'referral':
      return (
        <ReferralWelcome
          referrerName={context.referrerName}
          reward="$10 off your first order"
        />
      );

    case 'product_focused':
      return (
        <ProductOnboarding
          product={context.product}
          promoCode={context.promoCode}
        />
      );

    case 'campaign':
      return (
        <CampaignLanding
          campaign={context.campaign}
          headline={getCampaignHeadline(context.campaign)}
        />
      );

    default:
      return <StandardOnboarding />;
  }
}

Personalization Strategies

Skip Irrelevant Steps

If the deep link tells you the user's interest, skip steps that ask about it:

Deep Link Context	Steps to Skip
product=fitness	"What are you interested in?" category picker
ref=friend123	"How did you hear about us?" survey
partner=EMPLOYER	Account type selection (partner defines it)
promo=PREMIUM_TRIAL	Pricing page (they already know the offer)

Every skipped step reduces drop-off. If you know the answer, don't ask the question.

Show Relevant Content First

Reorder the onboarding to show the most relevant content based on context:

User from a fitness ad:

1. "Welcome! Let's set up your fitness profile." (not generic welcome)
2. Fitness preference selection
3. Account creation

User from a referral:

1. "Sarah invited you! Here's your $10 reward."
2. Quick account creation
3. Browse products (with reward highlighted)

User from a QR code at a retail store:

1. "Welcome! Scan products to see reviews and prices."
2. Location permissions (to enhance in-store experience)
3. Account creation (optional, can browse first)

Pre-Fill Known Data

If the deep link includes data the user already provided (email from a newsletter signup, name from a partner integration):

function AccountCreationScreen({ context }) {
  return (
    <Form>
      <Input
        label="Email"
        defaultValue={context.email || ''}
        disabled={!!context.email} // Pre-filled and locked
      />
      <Input label="Password" />
      <Input label="Name" />
    </Form>
  );
}

Customize Messaging

Tailor the copy to match how the user arrived:

Source	Welcome Message
Referral	"Sarah thinks you'll love [App]. Here's $10 to get started."
Fitness ad	"Ready to crush your fitness goals? Let's go."
Back-to-school campaign	"Everything you need for the new semester."
Organic (no context)	"Welcome to [App]. Let's get you set up."

Small copy changes make the experience feel intentional, not generic.

Deferred Deep Linking Requirements

Personalized onboarding depends entirely on deferred deep linking working correctly. The user clicks a link, installs the app, and the context must survive the install process.

How Deferred Deep Links Work

1. User clicks https://go.yourapp.com/signup?product=fitness&promo=FIT20
2. User is redirected to the App Store / Play Store
3. User installs the app
4. On first launch, the SDK contacts the server
5. The server matches the device (fingerprinting) to the original click
6. The deep link data (product=fitness, promo=FIT20) is returned to the app

Match Rate

Deferred deep link match rates are typically 60-80%. Factors that affect matching:

• Time between click and install (shorter is better)
• Network changes (different Wi-Fi/cellular between click and install)
• Device privacy settings (iOS App Tracking Transparency, Android privacy features)

For the 20-40% of users where deferred matching fails, fall back to the default onboarding flow. The personalized flow is a bonus, not a requirement.

For contextual deep linking patterns, see Contextual Deep Linking: Pass Data Through the Install.

Measuring Personalized Onboarding

Key Metrics

Metric	Personalized	Default	Expected Lift
Onboarding completion rate	60-80%	40-60%	+20-40%
Time to complete	2-4 min	4-8 min	-50%
Day 1 retention	40-60%	25-40%	+30-50%
First conversion	20-30%	10-15%	+50-100%

A/B Testing

Test personalized vs. default onboarding for users from the same source:

function getOnboardingVariant(context) {
  // 50/50 split for users from ad campaigns
  if (context.source === 'ad' && Math.random() < 0.5) {
    return 'default'; // Control group
  }
  return getOnboardingFlow(context); // Personalized
}

Track completion rates, retention, and conversion for each variant.

Funnel Analysis

Track each onboarding step with the context:

analytics.track('onboarding_step', {
  step: 'account_creation',
  flow: context.flow, // 'referral', 'product_focused', 'default'
  source: context.source,
  campaign: context.campaign,
  stepsSkipped: context.skippedSteps.length,
});

This reveals which personalization strategies drive the biggest improvements and which sources produce the highest-quality users.

For onboarding use cases, see the onboarding documentation. For deferred deep linking details, see the deferred deep linking docs. For deep linking features, see Tolinku deep linking.