Your team spent three weeks implementing deep linking. The SDK is live, the links work, and users who click them land in your app instead of a browser dead-end. But if your deep linking strategy stops at "open the app to the home screen", you're using infrastructure-grade technology for something a basic redirect could handle.

Deep linking isn't just a technical feature. It's growth infrastructure that changes how you run campaigns, measure attribution, and design user journeys across every channel where your app needs to show up.

Most teams treat deep links as a convenience layer for existing users. The real opportunity is using them to collapse the gap between discovery and conversion for new users, track campaign performance that would otherwise vanish into "(not set)", and create experiences that work across platforms, channels, and user states without manual routing logic.

Beyond "Open the App": Deep Linking as Growth Infrastructure

Here's the problem with basic app opens: they don't carry context. A user clicks your Meta ad, installs your app, and opens it three hours later. Without deep linking, your app has no idea which campaign drove that install, what product they were interested in, or what promo code they expected to use.

Deep linking solves three operational problems that affect how growth teams allocate budget:

1. Attribution accuracy: Links carry UTM parameters and campaign identifiers through install flows, connecting ad spend to in-app revenue even when users don't convert immediately.

2. Conversion velocity: Users land exactly where they need to be (product page, checkout, level 5) instead of navigating from the home screen, which typically improves D0 conversion rates by 20-40%.

3. Cross-platform consistency: The same link works whether someone clicks it on iOS, Android, or web, routing to the App Store, Play Store, or fallback page based on device detection.

The use cases below show how growth teams actually deploy deep linking in production across channels that represent 60-80% of mobile UA spend: influencer campaigns, paid social, email, QR codes, out-of-home advertising, SMS notifications, and web-to-app handoff flows. Each scenario includes implementation complexity, attribution impact, and the specific deep linking features required to make it work.

Use Case #1: Influencer Campaign Tracking with Unique Promo Codes

The scenario: You're running 15 influencer partnerships simultaneously. Each creator posts a unique promo code, but without deep linking, attribution breaks. Influencers share generic App Store links, users install, and there's no connection between install and campaign. Your only signal is self-reported promo code usage, capturing maybe 30-40% of conversions.

How deep linking fixes this: Generate unique deep links per influencer with campaign parameters and promo codes. After install, deferred deep linking delivers campaign data and auto-applies the code at checkout.

Attribution impact: Instead of "15 influencers drove 2,400 installs", you see "Creator A drove 180 installs with 22% D7 purchase rate, Creator B drove 340 installs with 8% D7 purchase rate". Cut low-performers, double down on high-performers. Blended influencer ROAS typically improves 30-50% within two months.

Implementation requirements: Dynamic link generation, deferred deep linking, event tracking connecting promo usage to source. Platforms like Linkrunner handle this with one API call per link.

Use Case #2: QR Code Menus to Specific Restaurant Listings (Food Delivery)

The scenario: You're partnering with 500 restaurants. Each needs QR codes on tables opening directly to their menu. Basic QR codes link to the App Store, then users manually search for restaurants. Conversion from scan to order: 8-12%.

How deep linking fixes this: Each restaurant gets a unique deep link in their QR code. Installed users open directly to the menu. New users install, then deferred deep linking opens the exact restaurant they scanned.

Attribution impact: Scan-to-order conversion increases from 8-12% to 25-35% by eliminating search friction. You gain channel-level attribution showing which restaurant partnerships drive incremental orders vs cannibalising existing traffic.

Implementation requirements: QR generation at scale, device detection, deferred deep linking, App Links/Universal Links verification. Medium complexity, but scales infinitely once configured.

Use Case #3: WhatsApp Sharing with Referral Attribution

The scenario: Users share products via WhatsApp for referral rewards. WhatsApp strips URL parameters and breaks web-to-app redirects. Without deep linking, attribution dies. Referral take-up looks like 2-3%, but that's just manual code entry.

How deep linking fixes this: Generate unique referral links using universal link formats WhatsApp respects. Direct app opens for installed users. Deferred deep linking captures referrer ID for new installs.

Attribution impact: Referral take-up increases from 2-3% to 12-18%. You calculate true viral coefficient and identify which cohorts drive quality referrals. Typically adds 8-15% to organic install volume within three months.

Implementation requirements: Per-user link generation, WhatsApp compatibility testing, deferred deep linking with user ID matching, fraud detection for self-referral abuse.

Use Case #4: Email Campaign to In-App Product Pages (eCommerce)

The scenario: Weekly emails feature personalised product recommendations. Without deep linking, email links go to mobile web saying "Download our app". Users who download must manually search for products. Conversion drops 60-70%.

How deep linking fixes this: Each product link is tagged with product ID and campaign source. Existing users open directly to product pages. New users install, then deferred deep linking opens the exact product from email.

Attribution impact: Email-to-purchase conversion increases from 0.8-1.2% to 2.5-4%. You measure which product categories and recommendation strategies drive highest revenue per send.

Implementation requirements: Product-level link generation, email client compatibility with fallback to universal links, UTM tagging connecting email engagement to in-app revenue.

Use Case #5: OOH Billboards to App Store with Context Passing

The scenario: Running 50 billboard QR codes across metro stations promoting specific offers. Without deep linking, attribution dies at App Store. Your "attribution" is just install volume during campaign period, no connection to outcomes.

How deep linking fixes this: Each billboard gets unique deep links with location, creative variant, and offer code. After install, deferred deep linking delivers parameters, auto-applies offers, and records billboard location as install source.

Attribution impact: Shift from "OOH drove 8,000 installs" to "Connaught Place drove 420 installs with 31% D7 retention, Andheri drove 680 with 18% retention". Eliminate underperforming locations, improve OOH efficiency 40-60% without increasing spend.

Implementation requirements: Bulk link generation, long-lived links for 3-6 month campaigns, deferred deep linking with location data, BI integration connecting spend to revenue.

Use Case #6: SMS Notifications to Transaction Details (Fintech)

The scenario: Transactional SMS for payments and bills. Without deep linking, links break or open to generic home screens. Users navigate 4-6 taps manually to find transactions. Most abandon.

How deep linking fixes this: SMS links tagged with transaction ID. Existing users open directly to transaction screens. Uninstalled users reinstall, then deferred deep linking opens correct transaction after login. Web fallback for users refusing reinstall.

Attribution impact: SMS-driven app opens increase from 18-25% to 45-60%. Support volume reduces 20-30% because users self-serve transaction lookups instead of calling support.

Implementation requirements: Transaction-level link generation at scale, secure parameter handling with encryption, deferred deep linking with authentication state management, web fallback.

Use Case #7: Social Media Ads to Specific Game Levels

The scenario: Meta and TikTok ads showcase specific game levels. Without deep linking, users install but start at level 1 regardless of ad creative. Disconnect between ad (level 15 boss fight) and experience (tutorial) creates 40-50% drop in D1 retention.

How deep linking fixes this: Each ad creative gets unique deep links tagged with level ID. After install, deferred deep linking skips tutorial and opens demo of the level shown in ad.

Attribution impact: D1 retention increases from 35-40% to 55-65%. D7 ROAS improves 25-40%. Creative-level attribution shows which game levels make best ad content.

Implementation requirements: Creative-to-level mapping, game engine integration (Unity/Unreal), deferred deep linking across iOS/Android, analytics connecting ad creative to in-game behaviour.

Use Case #8: Web-to-App Handoff for Logged-In Users

The scenario: Users browse on mobile web, add cart items, then want to checkout in app. Without deep linking, app opens to home screen, users logged out, cart empty. Conversion drops 70-80%.

How deep linking fixes this: Web-to-app links include cart contents and session tokens. Deep link validates token, logs users in automatically, displays cart ready for checkout. Continuous session despite platform switch.

Attribution impact: Web-to-app conversion increases from 12-18% to 40-55%. Revenue per web session increases 30-45% because users finishing in app have higher average order values.

Implementation requirements: Secure session token generation, cart serialisation, authentication handling, universal link/app link setup working reliably across browsers.

Implementation Complexity: What Each Scenario Requires

Not all deep linking use cases demand the same engineering investment. Here's how the complexity breaks down:

Low complexity (2-4 hours of dev work):

• Static QR codes with pre-generated links (Use Case #2, basic version)

• OOH billboards with location tracking (Use Case #5)

• Simple influencer tracking without auto-applied promo codes (Use Case #1, basic version)

Medium complexity (1-2 days of dev work):

• Per-user referral links with attribution (Use Case #3)

• Email campaigns with product-level links (Use Case #4)

• Social media ads with creative-level targeting (Use Case #7, if game engine supports deep link parameters natively)

High complexity (1-2 weeks of dev work):

• SMS links with transaction-level security (Use Case #6)

• Web-to-app handoff with authentication (Use Case #8)

• Influencer tracking with auto-applied promo codes and fraud detection (Use Case #1, full version)

The common pattern: scenarios requiring per-user data, authentication state, or cross-platform session continuity demand backend coordination beyond just implementing the deep linking SDK. Most teams underestimate this coordination cost and then get stuck during QA when links work but data doesn't flow correctly between systems.

For teams implementing multiple use cases simultaneously, platforms like Linkrunner reduce complexity by handling link generation, parameter passing, deferred deep linking, and attribution logic in one integrated system. The alternative is stitching together separate tools for link management, attribution, and analytics, which creates maintenance burden and increases the surface area for breakage.

Attribution Impact: Which Use Cases Drive Measurable Lift

Here's what matters to growth teams: not every deep linking use case improves the metrics you're optimising for. Some use cases are table stakes (transactional SMS, basic app opens), while others directly affect CAC, retention, and revenue.

Highest attribution impact (measurable improvement in CAC or ROAS within 30 days):

• Influencer tracking with promo codes (Use Case #1): CAC transparency improves budget allocation, typically increasing influencer ROAS by 30-50%

• QR codes to specific pages (Use Case #2): Conversion improvement from 8-12% to 25-35% translates to 2-3× effective ROAS for offline channels

• Social ads to game levels (Use Case #7): D1 retention lift from 35-40% to 55-65% compounds into 25-40% better D7 ROAS

Medium attribution impact (measurable improvement in retention or LTV within 60-90 days):

• Referral programs via WhatsApp (Use Case #3): Viral coefficient improvement from 0.05 to 0.15 adds 8-15% organic volume over time

• Email-to-product deep links (Use Case #4): Conversion improvement directly lifts email channel contribution to revenue by 30-45%

• Web-to-app handoff (Use Case #8): Order completion rate improvement drives 20-30% higher web session value

Lower direct attribution impact (operational improvement, not revenue-measurable):

• OOH with location tracking (Use Case #5): Better spend allocation across locations, but hard to A/B test causality

• Transaction SMS links (Use Case #6): Reduces support load and improves NPS, but doesn't directly affect acquisition or monetisation

The use cases with highest impact share two characteristics: they reduce friction at conversion-critical moments (checkout, first-time use, content discovery) and they provide attribution visibility that was previously invisible (influencer performance, creative-level ROAS, channel contribution).

Teams should prioritise implementing use cases in this order: start with scenarios that directly affect paid UA efficiency (influencer tracking, social ads), then layer in conversion-focused scenarios (email, QR codes, web-to-app), and finally add operational scenarios (SMS, OOH) once the high-impact use cases are live and working reliably.

Key Takeaways

Deep linking stops being a technical convenience feature when you implement it across the channels where your budget actually flows. The eight use cases covered here represent real workflows that growth teams run weekly: influencer campaigns, paid social, email sends, QR code rollouts, OOH media buys, transactional notifications, and web-to-app conversion paths.

The pattern across all scenarios: deep linking preserves context across platform boundaries, whether that's carrying campaign parameters through the App Store, maintaining cart contents from web to app, or connecting an OOH billboard scan to downstream revenue events. Attribution accuracy improves when links replace guesswork, and conversion rates improve when users land where they need to be instead of navigating from generic entry points.

Implementation complexity varies widely. Basic scenarios (static QR codes, OOH tracking) require minimal dev work and can go live in hours. Complex scenarios (authenticated web-to-app handoff, transaction-level SMS links) demand backend coordination and take weeks to ship reliably. Most teams underestimate the operational coordination required between marketing, product, and engineering to make advanced use cases work correctly under production load.

For teams running multiple deep linking scenarios simultaneously, unified platforms like Linkrunner simplify the operational complexity by handling link generation, deferred deep linking, attribution logic, and cross-platform routing in one system. This matters when you're managing hundreds of influencer links, thousands of email product links, and millions of transactional SMS links concurrently. The alternative is building and maintaining deep linking infrastructure in-house, which most teams underestimate until they hit scale.

If you're currently using deep linking only for basic app opens, pick two use cases from this list that align with your largest UA channels. Implement them properly with attribution tracking, measure the impact on conversion and retention, and then expand to additional scenarios based on what delivers measurable lift. The goal isn't to implement all eight use cases immediately; the goal is to shift deep linking from "nice-to-have convenience" to "core growth infrastructure that affects budget decisions".

Want to see how Linkrunner handles dynamic link generation, deferred deep linking, and attribution tracking across these use cases? Request a demo to explore implementation options for your team's specific channels and workflows.