How August AI Turns Web Visitors Into Mobile Patients at 6x Higher Conversion vs Industry Average

Building a healthcare AI category meant building a new patient journey

August AI's growth does not look like a typical consumer app. There is no big Meta or Google Ads spend driving the curve. Patients arrive through August's content, the August health library, the homepage, and the AI chat experience on web. The central question for the growth team was always the same: how do we move a web visitor who just had a useful experience into the mobile app, where they will get the full product?

Three things made this harder than it sounds.

• The web app is the front door, not the destination: a patient might start a conversation about a skin condition on the web app at 11 p.m. and need to come back to it tomorrow morning. That return visit needs to happen on mobile, but only if the handoff is seamless. A broken deep link, a missed install attribution, or a lost conversation state is the difference between a returning patient and a lost one.

• Owned channels were the entire engine: without a meaningful paid-ad budget, every install came from places August controlled: hero CTAs on landing pages, the footer, Health Library articles, Instagram bio links, and in-app shares. If those touchpoints were not measured precisely, the team could not know which content was driving patient acquisition.

• Organic was eating the real attribution: in a healthcare product where install spikes correlate with content launches, social mentions, and clinician shares, lumping a quarter of installs into an unattributed organic bucket meant flying blind on the channels that were actually working.

August needed an attribution layer that could keep up with a fundamentally non-paid growth model, one that respected how patients actually move from "I have a question" to "I have the app on my phone."

Linkrunner became the attribution backbone for an owned-channel healthcare growth model

August integrated Linkrunner as their MMP and deep-link layer, with a specific focus on three flows that traditional attribution stacks handle poorly.

• Web-app to native-app handoff: every patient using the August web app sees contextual prompts to continue on mobile. Linkrunner powers the deep link behind those prompts, preserving the patient's identity and conversation state across the install, and attributing the install back to the web-app session that triggered it. This is the single highest-value flow in the business, and the one most likely to break without dedicated infrastructure.

• Per-surface owned-channel attribution: August runs distinct Linkrunner campaigns for every meaningful surface: the Android landing hero, the iOS hero, global variants, footer CTAs, top-nav prompts, Health Library banners and graphics, Instagram bio links, and in-app share links. Every install is tied back to the exact entry point, not direct, not organic, but landing_page_hero_android, health_lib_topnav, or share_app.

• Deterministic install attribution: Linkrunner's deterministic install-ID matching (lr_ia_id) recovers installs that probabilistic systems would have dumped into the organic bucket. For August, this is the difference between knowing a patient came from a friend's WhatsApp share versus assuming they showed up out of thin air.

Owned channels became a high-conversion patient-acquisition engine

The August team now operates with a precision that is rare for a non-paid growth model. Every patient install is tied to a real, optimizable source, and the numbers reveal an acquisition funnel that punches far above its weight.

Metrics measured on Linkrunner

Owned landing pages convert at 5-10x industry norms

Most consumer apps see click-to-install rates in the 5-15% range. August's owned landing pages convert at 47-70%, a signal that patient intent is high, the deep-link routing is clean, and the experience from web tap to installed app is uninterrupted. Linkrunner is what makes that funnel both possible and measurable.

Why healthcare AI funnels behave differently

This is not just a story about good landing pages. It is a story about a category where the user shows up already convinced. People do not land on August AI to browse. They land because something specific is happening: a symptom they cannot explain, a lab result they do not understand, or a question they cannot ask at 2 a.m. By the time a patient taps "Get the app," they have often already had a conversation that gave them real, useful information. The install is not a leap of faith. It is a continuation of an experience that has already worked.

• 47-70% click-to-install on owned landing pages compared with the 5-15% consumer-app norm, because patients arriving from August's content already have a problem they want to keep solving.

• 60% conversion on the web-to-native handoff with 0.46% reinstalls, because patients who have used the web AI are graduating to mobile because they intend to come back.

• 33% conversion on in-app shares, because when a patient sends August to a friend or family member, the recipient is usually someone with an active health concern.

In categories like gaming or entertainment, attribution stacks have to fight for every install because intent is fragile and decay is fast. In healthcare AI, the dynamic is inverted: intent is unusually high, but it is spread across many small, owned surfaces. The bottleneck is not creating intent. It is not losing it between the moment a patient decides to install and the moment the app opens with the right context.

The web-to-native handoff is doing the work

The single most important number for August's product strategy is the web_app channel: 4,519 patient installs at a 60% click-to-install rate, with a reinstall rate of just 0.46%. On most channels, 15-30% of installs are existing users reinstalling. On the web-to-native flow, it is near zero, meaning every conversion is a net-new mobile patient moving from the web experience into the full product. The web app is not cannibalizing the mobile app. It is feeding it. Linkrunner's attribution is what makes that fact visible and provable.

Recovering 25% of installs from the organic graveyard

Since integration, 36,453 installs, 25% of the total, have been attributed by Linkrunner's deterministic install-ID matching. Without that recovery layer, those patients would have appeared as organic, uncreditable to any specific channel, content piece, or campaign. For a healthcare AI building a long-term acquisition engine, recovering a quarter of installs from anonymity is the difference between knowing what works and guessing.

iOS growth followed the playbook

In August 2025, their first full month on Linkrunner, August AI saw 629 iOS installs. By March 2026, that number had climbed to 3,538 per month, a 5.6x increase in seven months. The growth-team playbook did not change for iOS. The same owned-channel funnel and web-to-native flow drove the curve, with Linkrunner's deep-link infrastructure adapting cleanly across platforms.

What makes this work

• Healthcare-grade deep linking: patients can move from a web AI conversation to the same conversation on mobile without losing context. The technical work behind that handoff, including OS detection, deferred deep links, and install identity matching, is invisible to the user and owned by Linkrunner.

• Owned-channel granularity: August knows the difference between a Health Library footer install and a homepage hero install. That granularity is what lets the team double down on the surfaces that actually convert patients.

• No paid-ad scaffolding required: August's growth does not depend on a Meta or Google budget to validate the attribution stack. Linkrunner works as a first-class measurement layer for owned channels, which is what healthcare AI growth actually looks like.