PitchPal: Expanding Language Learning Opportunities
September 2024
When?
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May 2024
Who?
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Anqalab, a forward-thinking tech company aiming to diversify its offerings.
What?
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Design of an AI-driven app to provide meaningful conversational practice through real-life prompts and personalized feedback.
The problem
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Many language learners struggle with tools that fail to prepare them for real-life conversations, focusing instead on grammar and vocabulary drills. This lack of practical speaking practice often leads to frustration and stalled progress.
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The founders were interested in exploring an AI-video tutor to address these challenges. However, user research indicated a stronger need for accessible, audio-based solutions to build confidence and engagement.
The Language Barrier
Learning a new language is more than memorising vocabulary: it’s about confidently engaging with people in real-life situations. Yet, many learners feel let down by existing tools that fail to prepare them for actual conversations. PitchPal aimed to fill this gap by offering bite-sized, context-specific conversational exercises that could fit into anyone’s day.
The Growing Language Learning Market
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The global language-learning market is projected to reach $75 billion by 2028, driven by demand for accessible, flexible solutions.
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Over 80% of language learners say that speaking a language confidently is their primary goal, with 70% of learners citing speaking as the most challenging skill to practice.​
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Despite this, only 25% feel that traditional language apps adequately prepare them for real-life communication.
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Speaking practice lessons with native speakers can cost $50–$100 per hour, creating a financial barrier for many learners.
Bridging the Gap in Language Learning
Beyond practical challenges, language learning is deeply emotional.
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55% of learners feel discouraged when they can’t apply what they’ve learned in real situations.​
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40% quit within the first six months, citing low confidence and lack of engaging content as primary reasons.
Opportunities for Change
PitchPal was conceived to address these challenges by focusing on what matters most to users:
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Quick, engaging exercises that mirror real-world interactions.
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Feedback that’s constructive, not intimidating.
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A gamified structure to keep learners motivated and coming back for more.
Exploring Opportunities in Language Learning with PitchPal
PitchPal was conceived as a response to the founders’ desire to explore untapped opportunities in the language-learning market through a potential AI-powered video tutor to address challenges faced by language learners. They aimed to address the gap between traditional language-learning apps and the need for real-life conversational practice.. My role was to uncover the challenges faced by language learners, validate assumptions about their needs, and create an accessible, scalable tool that could bridge this gap.
This case study outlines how I applied a structured design process to identify and validate user needs, culminating in the development of an accessible, audio-driven platform for real-time conversational practice. This process not only tested the feasibility of the concept but also laid the groundwork for a scalable, innovative solution that aligns with the growing demand for practical, confidence-building language-learning tools.
User Research
User Interviews
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Interviewed 20+ users.
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Diverse skill levels and backgrounds, including students, professionals, and casual learners.
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Explored how language learners acquire new languages, their motivations, and the effectiveness of existing learning methods.
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Explored their language-learning experiences, including methods used, motivations, and challenges.
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Identified which features they found most useful, what they felt was missing, and why their current methods did or didn’t work.
Survey
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​Over 120 participants completed a survey, used to validate insights from interviews and understand broader trends.​
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Collected data on languages learned, reasons for learning, methods used, and features they wished existing tools offered.​
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Quantified user behavior and pain points to prioritise design decisions.
Competitor Analysis
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Analysed several language-learning platforms to identify gaps and common user pain-points.​
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Highlighted the lack of affordable, scalable alternatives to native speaker-led lessons, which are often prohibitively expensive for many learners.
Contextual Inquiry
Observed how users interacted with language-learning tools in in various real-world scenarios, such as commuting, during work breaks, or at home, uncovering key frustrations and opportunities.
Main Insights from User Research
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A confidence gap: Learners lacked tools that helped them practice speaking in realistic contexts, leaving them unprepared and anxious.
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Boredom from repetitive content: Existing apps often relied on gamification, but their repetitive exercises didn’t simulate engaging real-life interactions.
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Frustration with passive learning: Users wanted more than just listening or reading—they needed active, immersive speaking practice.
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Flexibility is key: Bite-sized lessons designed for busy schedules were highly preferred.
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Motivation is a challenge: Many learners struggled to stay motivated, especially when progress wasn’t clearly measurable.
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Low Interest in Video: Contrary to initial assumptions, video-based interactions were not popular.
Hypotheses
The Solution
Validating the concept
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The founders wanted to validate the concept before proceeding further. For this, I recommended a smoke test using a website showcasing an “AI-powered virtual English tutor”. I designed the website, which included:
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App store download buttons.
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A form to collect user information and reasons for interest.
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After a conversation with the founders, they decided they would run a Google Ads campaign to validate the smoke test.
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Based on the results from the Google Ads campaign, the founders decided to move the project forward and I designed an MVP and an initial product plan focused on user needs.
Designing the MVP
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To launch quickly, the initial app version allowed users to record audio and receive feedback on their pronunciation and grammar. This simple approach validated the concept and addressed the need for affordable speaking practice.
Prompts were provided to help the user get started. This feature was improved later on with hints.
Fun facts were displayed to account for the long loading time for the feedback generation.
Feedback was provided based on the user's speaking skills.
Challenges identified
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While the MVP achieved downloads, user retention was low:
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Most users engaged in only one practice session and did not return.
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This highlighted the need for more dynamic, engaging features that aligned with users’ goals and behaviours, as identified during user research.
The three options shown to gauge interest from user behaviour. Based on the results, video was deprioritised.
Evolving the solution: Real-time conversations
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Based on user research findings, the app evolved into an AI-driven real-time conversational platform focused on audio-based interactions. The new version prioritised creating realistic, context-specific conversations tailored to the user’s learning level and goals. Key features included:
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Personalised Conversations: The AI learned from user behaviour to create tailored, context-specific scenarios.
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Real-Time Transcript: Provided a visual representation of the conversation to help users follow along.
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Supportive Tools:
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Repeat: Replay phrases for better understanding.
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Translation: Quick access to native language translations.
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Hints: Suggestions to keep conversations flowing.
Providing accessibility options increased retention and boosted user satisfaction.
Boosting Engagement
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To address low retention and encourage consistent practice, I introduced the following features based on user feedback and behavioural analysis:
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Push Notifications
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Notifications were triggered 24 hours after the last session, gently reminding users to continue learning.
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This strategy significantly increased daily active users.
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Skill Score Mechanism
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A visual skill score system tracked users’ progress, displayed as a graph to show trends over time.
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Scores decreased after inactivity, encouraging users to return and maintain consistent practice.
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This mechanism helped users see tangible progress and motivated them to improve, addressing engagement challenges identified in user research.
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Future potential: The skill score could evolve to include certifications or equivalency to international standards, adding value for users seeking measurable milestones.
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Dynamic Notifications
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Custom messages tied to the skill score were introduced, such as to keep the momentum going, or a catch-up session when the score was going down.
The skill score mechanism improved engagement by allowing users to see measurable progress.
Why is this solution useful?
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The real-time conversation feature tackled the core problem of enabling practical speaking practice in realistic scenarios. By integrating tailored feedback, dynamic tools, and personalised interactions, the app aligned closely with user needs as identified in research.
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The engagement-focused features (like push notifications and skill scores) helped users stay motivated and increased retention, making the app a more effective tool for building confidence in spoken English.
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The potential to integrate certifications or recognised levels added a future-ready dimension to the solution, enhancing its long-term value.
Lessons learnt
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This project highlighted the importance of iterative design and user-centric solutions. Starting with an MVP helped quickly validate concepts and reveal gaps, such as low retention. Iterating with real-time conversational features and engagement tools demonstrated the value of addressing user needs directly to boost satisfaction and retention.
The Solution
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I designed PitchPal as a real-time conversational practice platform designed to address language learners’ needs for practical speaking opportunities. The MVP initially offered audio recording and feedback, but subsequent iterations incorporated real-time conversations, transcripts, translation tools, and skill scores. These features boosted engagement, improved retention, and empowered users to build confidence in their language skills.
What was special?
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The real-time conversation feature became the core of PitchPal, offering users tailored, immersive speaking practice. Combined with engagement tools like skill scores and accessible features such as transcripts and translations, PitchPal stood out as an inclusive and user-friendly language-learning platform.
How did I contribute?​
I conducted comprehensive user research to identify and validate pain points and assumptions about language learners. I designed the MVP and later iterated on advanced features, such as real-time conversations and engagement tools like skill scores. These enhancements directly addressed user needs and improved the app’s usability and retention outcomes.
What's next? Growing the design.
The initial focus of PitchPal was to address the gap in conversational language learning through real-time, audio-based interactions. To further refine and expand the platform, here are some potential next steps:​
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Enhancing real-time conversations: Expand the AI’s ability to simulate more dynamic and nuanced conversational scenarios tailored to user goals, such as job interviews, travel, or casual conversations.
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Introducing certification programs: Develop a certification feature to validate users’ skills and align progress with recognised language standards.
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Localisation and personalisation: Adapt content to regional accents, languages, and cultural contexts to provide a more tailored learning experience for diverse users.