Content Recommendation Discovery on MindTools
As a user, I want to see recommended content based on my interests and usage
Project Context
Design a personalized content-recommendation feature for MindTools’ B2C platform, helping users discover relevant articles and toolkits based on their role, seniority, and interests—without feeling “creepy” or intrusive.
Challenge
Surface the right learning resources to each user, increasing engagement and satisfaction.
Key Questions
• How do users want to receive recommendations?
• How can we get data to recommend the right thing without annoying the user?
• Which recommendation tools could we use before trying to build our own?
• How can we build trust in our recommendations?
• How can we show the users that the data they provide is being used for recommendations?
• How can we get data to recommend the right thing without annoying the user?
• Which recommendation tools could we use before trying to build our own?
• How can we build trust in our recommendations?
• How can we show the users that the data they provide is being used for recommendations?
My Role & Responsibilities
• UX Research & Discovery - designed and ran moderated usability tests and interviews with 10 users and crafted 15-question surveys and 7 interactive “missions” in Maze and TryMyUI
• User Analysis & Story Mapping - synthesized feedback to identify patterns in how users expect to receive and adjust recommendations and defined key personas and mapped 5 core recommendation journeys
• Feature Definition & Prototyping - wrote 3 primary user stories to drive prototype scopes and built mid- to high-fidelity Figma prototypes for homepage and in-app recommendation panels
User Stories
• As a user, I want to see the top 3 most viewed content based on the same user’s role on the homepage, a right-side feature based on the onboarding questionnaire - What is your role? - What is your seniority level?
• As a user, I want to see interactive components on the content card placed as a recommended session - suggesting content that was confirmed as useful content based on similar users’ profiles with an option to update that recommendation by selecting the option to see less item
• As a user, I want to discover what matters to me on the homepage, a right-side feature based on the onboarding questionnaire - What topics do you like to develop today? (group-categories)
My Process, Outcomes, and Impact
Research
• Conducted 10 user interviews (B2C learners)
• Ran 10 interactive missions in Maze & TryMyUi (7 tasks each)
• Collected & analyzed feedback from 10 recorded test sessions
• Audited 5 third-party recommendation engines
• Ran 10 interactive missions in Maze & TryMyUi (7 tasks each)
• Collected & analyzed feedback from 10 recorded test sessions
• Audited 5 third-party recommendation engines
Ideation
• Facilitated 2 co-design workshops with UX & data teams
• Produced 15 sketch variations for recommendation widgets
• Built 8 low-fidelity wireframes for homepage & content cards
• Created 5 user-story maps driving feature scope
• Produced 15 sketch variations for recommendation widgets
• Built 8 low-fidelity wireframes for homepage & content cards
• Created 5 user-story maps driving feature scope
Validation
• Developed 2 high-fidelity Figma prototypes
• Tested with 10 participants over 3 recommendation tasks each
• Logged 12 usability insights and 30 preference ratings
• Iterated through 2 prototype versions
Execution• Tested with 10 participants over 3 recommendation tasks each
• Logged 12 usability insights and 30 preference ratings
• Iterated through 2 prototype versions
• Delivered 4 final mockups and interaction specs
• Authored 1 tool-evaluation matrix and integration roadmap
• Held 4 design-dev alignment sessions
• Seeded 6 new components (cards, preference controls) in the design system
• Authored 1 tool-evaluation matrix and integration roadmap
• Held 4 design-dev alignment sessions
• Seeded 6 new components (cards, preference controls) in the design system
UX Debts
The LPQ are the questions asked under the subscription process, they are marketing questions related and not directly connected to the Learning Experience
• What is your Country?
• What is your age?
• What Industry do you work in?
• How many people are employed at your company?
• What is your age?
• What Industry do you work in?
• How many people are employed at your company?
Marketing Opportunity
After the subscription, today, all users receive an email with a link to download an e-book called “Personal Development Plan“which guides the user to understand and track them, such as Strengths, Weaknesses, Goals, Target Date, and Carrer Mission
That information stays with the user in a PDF, which we see as crucial to building richer experiences around the platform, curing relevant content, and helping the users to achieve the goals
Key Learnings
• Trust Through Transparency — Clearly explaining “why” builds confidence in automated recommendations.
• Balance Data & Privacy — Only ask for essential info up-front; allow users to refine preferences later.
• Leverage Existing Data — Subscription and e-book questionnaires are a goldmine for initial personalization.
• Iterate Early & Often — Rapid prototype testing surfaces usability issues before heavy engineering investment.
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