InspireAI
An AI-powered companion for the Pinterest platform that delivers highly personalized content recommendations, facilitates interest-based community formation, and offers creators actionable insights
Problem Statement
How might we provide highly personalized recommendations, enable meaningful community formation, and deliver insightful creator analytics to ensure Pinterest users can discover, engage, and create more effectively?
Problem Background
Most Pinterest users visit the platform for inspiration, but many struggle to discover personalized content, find relevant communities, and gain insights that help them create engaging content. Pinterest’s existing recommendation system offers broad suggestions but lacks the precision to serve users based on their unique interests and behaviours. As a result, users often abandon their searches without saving or engaging with pins. Additionally, creators find it difficult to understand which content resonates most with their audience, hindering their growth.
Users also face challenges in connecting with like-minded individuals or participating in communities built around shared passions. While group boards exist, they are hard to discover, and users have no easy way to find communities relevant to their interests. Creators, on the other hand, lack actionable insights to optimize their content strategy.
Furthermore, competing platforms such as TikTok, Instagram, and YouTube have adopted AI-driven content discovery and community-building features that significantly enhance user engagement. TikTok’s algorithm, for example, ensures content is surfaced based on user behaviour, creating a highly engaging experience. Pinterest, while a powerful tool for inspiration, has yet to fully harness AI in a way that moves beyond basic discovery to actionable steps and meaningful connections.
The absence of AI-driven personalization also limits Pinterest’s ability to provide relevant recommendations tailored to evolving user preferences. Users frequently express frustration with generic suggestions that do not align with their unique interests or past interactions. Additionally, creators lack insights into when and how to post content to maximize reach and engagement, leading to inefficiencies in their content strategies.
By integrating AI-powered personalization, community-building features, and creator insights, Pinterest can bridge these gaps, offering users a seamless experience that extends beyond inspiration into actionable execution. Addressing these issues will improve retention, enhance user satisfaction, and solidify Pinterest’s position as a leading platform for both discovery and engagement.
Research Insights
User Pain Points
Users on Pinterest often struggle with finding content that is truly relevant to their interests and needs. Many report frustration with the platform’s recommendation algorithm, which tends to surface broad or unrelated content rather than highly personalized suggestions.
As a result, users frequently leave Pinterest to search for additional resources, such as tutorials, shopping links, or community discussions, on external platforms like Google, YouTube, or TikTok.
This not only disrupts their user journey but also diminishes Pinterest’s role as an all-in-one inspiration and execution tool. Additionally, the lack of community-driven engagement makes it difficult for users to connect with others who share similar interests. While Pinterest does have group boards, they are often difficult to discover and do not foster dynamic interactions.
Content creators also face significant challenges, as they struggle to identify which types of posts perform best and how to optimize their content for visibility and engagement. Without detailed insights into audience preferences and behaviours, creators are left guessing about the best strategies for growth, ultimately leading to lower content output and reduced platform engagement.
Supporting Data
Research conducted with Pinterest users highlights the platform’s core issues and areas for improvement. A significant 85% of surveyed participants indicated dissatisfaction with Pinterest’s ability to help them take actionable next steps after discovering an idea.
Many expressed frustration with having to leave the platform to find more detailed information, such as step-by-step guides or product links. Additionally, 71% of users, particularly within the 18-24 age group, reported that they often abandon Pinterest mid-session because they cannot find relevant or actionable content quickly enough. While users rated Pinterest highly for its ability to provide inspiration, they found it lacking when it came to executing their ideas.
Another recurring complaint was the inefficiency of Pinterest’s search functionality, with many users stating that search results often surface outdated or irrelevant content. This issue discourages continued engagement and reduces the likelihood of users returning to the platform frequently.
Content creators also struggle to gain insights into their audience engagement patterns, with many stating that they do not have access to meaningful analytics that could help them refine their content strategy. By addressing these issues with AI-driven personalization and actionable insights, Pinterest can significantly improve user satisfaction and engagement.
Feedback
User research further reinforces the need for AI-powered enhancements to Pinterest’s platform. Many users expressed that while they enjoy browsing Pinterest for inspiration, they frequently experience frustration when trying to move from idea discovery to execution.
One user noted that while they often save pins related to home décor projects, they struggle to find actionable guidance on where to purchase materials or how to follow through with a project. Another user mentioned that they love collecting fashion inspiration but wish Pinterest could provide personalized outfit recommendations based on their saved styles.
Creators also voiced their concerns, with one stating that they feel lost when it comes to optimizing their content for maximum engagement. Without clear insights into which pins resonate most with their audience, they often find themselves posting inconsistently or producing content that fails to gain traction. Many users also emphasized the lack of interactive features that could help them connect with others who share similar interests.
Unlike platforms such as Instagram and TikTok, which have strong social and community components, Pinterest remains largely a solitary browsing experience. These insights underscore the importance of introducing AI-powered recommendations, community-driven features, and enhanced analytics to transform Pinterest into a more engaging and action-oriented platform.
Landing on the Solution
To address these challenges, InspireAI integrates multiple AI-driven features designed to enhance personalization, community engagement, and creator support. By leveraging advanced machine learning models, InspireAI ensures that users receive highly relevant pin suggestions tailored to their browsing history, preferences, and engagement patterns.
Additionally, AI-driven community formation helps users connect with others who share similar interests, fostering deeper engagement and collaboration.
For creators, InspireAI introduces an Insights Dashboard, providing them with detailed analytics on pin performance, audience engagement, and content trends. These features work together to create a more dynamic, engaging, and data-driven Pinterest experience.
Explanation of Solution
Through AI-powered recommendations, InspireAI bridges the gap between inspiration and execution, ensuring that users receive content that is both relevant and actionable.
The introduction of AI-driven communities enables users to participate in interest-based discussions, making Pinterest a more interactive platform. Meanwhile, the creator analytics tools empower content producers with valuable insights, helping them refine their strategies and maximize their reach.
Our testing phase demonstrated that users who engaged with InspireAI-driven features spent more time on the platform and reported higher satisfaction levels compared to those using the traditional Pinterest experience.
User Flows/Mockups
https://www.figma.com/design/Bh5dvhwUXKPM9nWtCGMWuJ/Untitled?node-id=0-1&t=Jyi5FTR3cMyAG1PS-1
Future Steps
Moving forward, InspireAI will continue to evolve to meet the needs of users and creators while leveraging AI-driven improvements. The next phase will involve refining the personalization engine, ensuring that recommendations become increasingly accurate based on evolving user behaviours.
Additionally, expanding metadata for shoppable pins will allow users to access direct purchasing options without leaving the platform. Future development efforts will focus on deeper integrations with e-commerce platforms, allowing Pinterest to bridge the gap between inspiration and action more effectively.
Enhancements to AI-assisted group formation will ensure that users can effortlessly discover and engage with communities that match their interests.
To further support content creators, InspireAI will introduce advanced analytics, including engagement benchmarks, content gap identification, and predictive insights that help optimize posting strategies.
Continuous improvements to search functionality will ensure that users receive the most relevant, high-quality results. These iterative enhancements will make Pinterest a more personalized, interactive, and insight-driven platform that caters to both users and creators.
Learnings
Product Manager Learnings:
Rowel Sabahat
During my time in Co.Lab’s AI Product Management Bootcamp, one of the most valuable lessons I learned was how to properly identify user problems at their core and break them down into actionable steps. Initially, it can be tempting to assume a solution without fully understanding the root cause of a problem.
However, through structured user research and iterative problem validation, I developed a more methodical approach to product thinking. This involved conducting in-depth user interviews, analyzing pain points, and ensuring that every feature or product decision directly addressed a real user need. By honing this skill, I now approach problem-solving with a user-first mindset, ensuring that solutions are deeply rooted in data and genuine pain points rather than assumptions.
Another key takeaway was learning how to flesh out ideas in great detail to develop a well-thought-out and comprehensive solution. In product management, having a high-level concept is just the beginning—success comes from being able to articulate and refine an idea with clarity, thinking through edge cases, dependencies, and long-term viability.
This bootcamp pushed me to take abstract ideas and turn them into structured, actionable product roadmaps. I learned to define user flows, feature priorities, success metrics, and technical feasibility with a level of depth that ensures products are not just functional but impactful. This skill has greatly improved my ability to collaborate cross-functionally, as clearly defined ideas lead to smoother communication with engineers, designers, and stakeholders.
Lastly, I gained a deeper appreciation for the power of iteration in product development. Some ideas might not seem viable or promising at first, but constant refinement, feedback loops, and real-world testing can transform them into something exceptional.
In many cases, my initial concepts evolved significantly after receiving user feedback, team critiques, and usability testing insights. Learning to embrace change and iteration rather than resisting it has been an invaluable lesson that I will carry forward in my career. Great products are not built overnight; they are the result of continuous learning, adaptation, and a commitment to delivering value to users.
Designer Learnings:
Designer Learnings:
Jo Sturdivant
- Adapting to an Established Team: Joining the team in week 6 of 8 was challenging, as I had to quickly adapt to existing workflows, dynamics, and goals. This mirrors real-world situations where you often integrate into teams mid-project, and flexibility is essential.
- Work-Blocking for Efficiency: With only two weeks to complete the project, I learned the importance of a structured work-blocking system. This approach allowed me to manage my time effectively and meet deadlines under pressure.
- Making Data-Driven Design Decisions: Unlike my past projects, I had to rely on research conducted by others. This was a valuable experience in using pre-existing data to guide design decisions, helping me focus on the core insights without starting from scratch.
Developer Learnings:
Developer Learnings:
Vanady Beard
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As the back-end developer, I learned how important it is to create efficient and reliable systems that support the entire application. This experience also taught me the importance of optimising the database and ensuring the backend is scalable and easy to maintain.
Developer Learnings:
Stephen Asiedu
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As a back-end developer, I've come to understand the importance of being familiar with various database systems and modules. This knowledge enables me to build diverse applications and maintain versatility in my work. I've also learned that the responsibility for making the right choices rests on my shoulders, guided by my best judgement.
Developer Learnings:
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Developer Learnings:
Maurquise Williams
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- Process of Creating an MVP: Developing a Minimum Viable Product (MVP) taught me how to focus on delivering core functionalities balancing between essential features and avoiding scope creep.
- Collaboration in a Real-World Tech Setting: This experience taught me how to collaborate efficiently in a fast-paced tech environment, keeping the team aligned and productive, even while working remotely across time zones.
- Sharpening Critical Thinking and Problem-Solving Skills: This experience honed my ability to think critically and solve problems efficiently. By tackling challenges and finding quick solutions, I sharpened my decision-making and troubleshooting skills in a dynamic, real-world setting.
Developer Learnings:
Jeremiah Williams
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All in all this experience was very awesome I learned that in coding with others being transparent is key
Developers Learnings:
Justin Farley
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I learned how important communication is when working with a team. Communication provides understanding, advice, ideas, and much more. While working with the product team, I’ve found that communication keeps everything flowing smoothly. Working with a team also showed me that every member brings something different to the table and we all have to work together in order to align and meet our end goal.