Instant AI Profiles Launch

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The challenge

Trial-to-paid for editing was stuck at roughly 5% — against an 11% baseline elsewhere in the product. The culprit was a single wall: Aftershoot asked photographers to upload and train on 2,500 photos before they could edit in their own style. That's a brutal wait-time-and-privacy barrier dropped right at the activation moment, and most trials never made it past it.

The reposition

Instant AI Profiles let a photographer import their existing Lightroom presets and have the AI analyze them in seconds — their signature style, day one. No 2,500-photo upload, no multi-day wait, no privacy worry.

The targets

The base isn't one audience, so the launch wasn't one message. I segmented it and set a distinct conversion target for each cohort — because an active trial, a lapsed user, and a long-expired trial each need a different reason to come back:

• Active trials — editing-focused, already in the product.
• Expired trials — 5+ projects or 100+ edits before lapsing.
• Reactivations — lapsed users worth winning back.
• Search-based new users — high-intent inbound.

What I built

• User segmentation strategy — the cohort model and conversion targets above.
• In-app onboarding copy — tied to the slider triggers (Exposure, Tint, White Balance) so the value landed in the moment.
• Reactivation email sequences — segmented lifecycle flows with factors.ai retargeting.
• Product release notes — the launch narrative across update pages.

Cross-functional ownership: I ran this end-to-end across product (in-app onboarding) and lifecycle (the segmented sequences) — mapping the work and owning the launch.

Targets vs. what I achieved

What I learned

Reactivations and active trials convert at dramatically higher rates once the training wait-time barrier is removed. The wait was the problem — eliminate the friction at the activation moment and the audience that already wanted the product finally converts.

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