Aperture
As the Product Manager, my key focus areas included improving features like filters, optimizing ad placements to be less intrusive, and enhancing user interactions across the platform. The approach involved deep research, prototyping, and strategic implementation to achieve the desired outcomes. The projected results aimed to deliver a more engaging and user-friendly experience while supporting the app’s revenue goals.
Phase 1: Problem discovery and stakeholder alignment
Aperture was experiencing a decline in engagement, especially among 18-24-year-olds, due to a lack of appealing features. Additionally, users across all demographics were frustrated by intrusive ads. However, reducing ad frequency wasn’t a viable solution as it would impact revenue. Instead, the plan was to adjust ad placement to more organic, user-preference-driven spots while enhancing key product features.
I started by crafting a clear company vision: “To connect people around the world through the power of images, fostering a community that celebrates meaningful moments.” This vision became the guiding star for decision-making throughout the project. I gathered the team for a brainstorming session to define our core product principles, which would inform all future decisions. These principles ensured alignment and allowed for consistent, value-driven choices during development.
Using a stakeholder analysis, I mapped out key contributors and their roles to ensure effective communication and alignment. I also defined a clear communication plan, which streamlined collaboration throughout the project.
Phase 2: Research and ideation
In this phase, the goal was to validate assumptions about why Aperture was losing users and develop feature improvements. A key hypothesis was that competitors offered more features that appealed to younger users, while Aperture’s ads were perceived as too disruptive.
- Ad Placement: Users reported that ads were too intrusive, so we decided to adjust ad placements to more organic locations, tailored to user preferences, without reducing frequency (to maintain revenue).
- Missing Features: Younger users preferred apps with more engaging features like music snippets and advanced filters.
- Performance Issues: Users were also frustrated with slow load times and frequent crashes after updates.
To address these insights, I led an ideation workshop using Miro to generate over 30 potential solutions. We applied the Effort vs. Value prioritization technique—my favorite!—to determine which ideas to pursue. The top priorities were improving filter functionality and tailoring ad placements based on user preferences.
A major challenge was balancing short-term wins, like adjusting ad placement, with long-term feature improvements, such as enhancing filter functionality. By using Effort vs. Value and MoSCoW prioritisation, we ensured that the highest-impact ideas were developed first.
Phase 3: Prototyping and testing
The main goal in this phase was to develop prototypes that improved the filter browsing experience and incorporated AI-powered filter recommendations. We also fine-tuned the ad placement strategy to ensure a smoother, more user-friendly ad experience without disrupting the flow.
We conducted A/B testing to measure the impact of the changes. The test results projected a 30% increase in engagement, with users responding positively to the filter improvements and more subtle ad placements.
Some users initially found new features like VR filters confusing. To address this, we added tooltips and brief tutorials to guide users through the new functionalities, improving their overall experience.
Phase 4: Launch and results
The final phase involved preparing for the product launch, implementing the new features, and tracking key metrics like user acquisition, retention, and engagement. A comprehensive product launch plan was developed, focusing on promoting the features through beta testing, social media campaigns, and influencer partnerships.
- 30% increase in user engagement within the first month (projections from A/B testing)
- 25% reduction in churn (projected)
- 15% increase in customer satisfaction (projected)
Maintaining performance stability during the launch was critical. By working closely with the development team and conducting thorough testing, we ensured the app would maintain a 99.9% crash-free rate post-launch.
Conclusion
This project allowed me to leverage a wide range of product management tools and methodologies to solve real-world problems. The strategic decisions I made — improving filters, optimizing ad placement, and introducing AI-powered recommendations — are projected to have a significant impact on user engagement and satisfaction. While the results are based on projections, the groundwork laid during this project provides a solid foundation for future growth. In future iterations, I would focus even more on continuous feedback loops to stay aligned with evolving user needs. This project was a rewarding and insightful experience, providing me with invaluable hands-on experience in driving product success!
