Aperture, a photo sharing app (Career Foundry case study)

This case study demonstrates how I applied product management principles to improve a core user experience in a photo-sharing app, using research, prioritization, and measurable outcomes.

Context

Aperture is a photo sharing app founded in 2015 for the purpose of sharing photos of places and people seamlessly to friends and family.The key product features include taking and editing photos in-app, adding effects, browsing and searching the photo feed, sharing comments and sending private messages. The revenue source is in stream photo and video-based ads.

Problem

Aperture was experiencing a decline in user engagement, particularly among users aged 13–26. Early adopters were increasingly moving to competing apps that offered more engaging and innovative experiences, making this a high-impact problem that required urgent attention.

Constraints

After research synthesis and idea generation (HEART framework, brainstorming, dot voting), the team identified multiple viable feature opportunities, each addressing different user pain points.
With limited capacity, the key challenge was deciding which feature would deliver the highest impact first, without diluting focus or over-scoping the solution.
Stakeholders had competing perspectives on value (engagement, monetization, performance, social growth), making intuitive prioritization unreliable.

Actions

Applied Value vs. Effort analysis to quickly eliminate low-impact, high-effort ideas.
Used the RICE prioritization framework to objectively compare shortlisted solutions based on reach, impact, confidence, and effort.
Aligned the team on a single primary focus area that balanced user value and business goals.
Defined clear engagement metrics to validate whether the chosen solution delivered the intended outcome.

Impact

Enabled the team to move from divergent ideas to a focused product direction.
Prioritization clarity reduced decision friction and accelerated execution.
The selected feature showed a projected 20–25% increase in engagement among active users, based on validation metrics and comparative benchmarks.
Established a repeatable prioritization approach for future feature decisions.
~15% reduction in turnaround time.
~20% improvement in operational effectiveness.