Periodic Reporting for period 1 - ELIA (Elia - Smart Assistant for English Learning)
Okres sprawozdawczy: 2023-07-01 do 2024-06-30
Elia aims to address the pressing need for effective English language learning tools, empowering non-native speakers to achieve proficiency and improve their economic opportunities. English, as the global lingua franca, can significantly impact individuals' lives, with proficiency leading to wage increases of up to 67% for those who master it. Our mission is to reduce inequalities and create opportunities by helping people own their English skills.
Elia leverages state-of-the-art AI and psycholinguistic research to create a personal assistant that integrates English learning seamlessly into users' daily routines. By personalizing interactions, Elia maximizes learning outcomes, making users feel as if they have a native speaker or teacher by their side. This approach targets learners with intermediate and advanced English proficiency, focusing on specific daily English needs.
Currently available as a browser plugin, Elia plans to expand to desktop and mobile platforms once product-market fit is achieved, ensuring continuous and accessible learning experiences. With the current initial traction of more than 10,000 users, the primary objective is to establish sustainable growth by identifying and catering to our market's specific needs.
Elia leverages state-of-the-art AI and psycholinguistic research to create a personal assistant that integrates English learning seamlessly into users' daily routines. By personalizing interactions, Elia maximizes learning outcomes, making users feel as if they have a native speaker or teacher by their side. This approach targets learners with intermediate and advanced English proficiency, focusing on specific daily English needs.
Currently available as a browser plugin, Elia plans to expand to desktop and mobile platforms once product-market fit is achieved, ensuring continuous and accessible learning experiences. With the current initial traction of more than 10,000 users, the primary objective is to establish sustainable growth by identifying and catering to our market's specific needs.
Throughout the project, significant strides were made in enhancing Elia's functionality and user experience. Initial efforts involved extensive market research and user feedback collection to refine Elia's features. Key activities included developing advanced AI algorithms for personalized learning, optimizing the user interface, and conducting rigorous testing to ensure seamless integration into users' daily routines.
Our collaboration with experts Andrej Persolja, Alejandro Marco Bartolome, and Jos Nederpel provided valuable insights into product-market fit and user acquisition strategies. These efforts led to the identification of key user segments and the implementation of targeted marketing campaigns, boosting user engagement and retention — first signs of achieving product-market fit.
In terms of marketing, we executed five major marketing campaigns to test various hypotheses and identify the most effective strategies for growth. Each campaign focused on different aspects of our marketing approach, including target audiences, messaging, and monetization strategies. These campaigns provided valuable insights into targeting, messaging, and monetization strategies, helping to refine our approach for better user engagement and business outcomes.
One of the key growth engines we aimed to achieve, as outlined in the proposal, was product stickiness. We measured stickiness using the "very disappointed" rate. If 40% of Elia users indicated that they would be very disappointed if they could no longer use Elia, this signified that we had reached the product-market fit stickiness milestone. We tracked this metric monthly, asking new users on their first day of using Elia how disappointed they would be if they could no longer use the product. This data was collected via Amplitude. Over the 12-month period, the average "very disappointed" rate was 47%, indicating that we have achieved product-market fit. This conclusion is based on responses from 855 unique users.
Despite the high indication of product-market fit manifested as the stickiness metric, it was very challenging to find a target group with the highest willingness to pay and thus find a sustainable monetization business model. As part of the marketing campaigns, we experimented with various subscription models, ranging from freemium models where there was always some part of the free version available, to more strict subscription models with no free version, only a limited free trial. However, none of these models resulted in a sustainable subscription base. Consequently, we reevaluated our B2C strategy, concluding that Elia has the highest potential as a freemium model, not as a paid free trial only subscription. To ensure sustainable growth, we began exploring different B2B strategies and partnerships, which are still in progress and will be further developed.
Our collaboration with experts Andrej Persolja, Alejandro Marco Bartolome, and Jos Nederpel provided valuable insights into product-market fit and user acquisition strategies. These efforts led to the identification of key user segments and the implementation of targeted marketing campaigns, boosting user engagement and retention — first signs of achieving product-market fit.
In terms of marketing, we executed five major marketing campaigns to test various hypotheses and identify the most effective strategies for growth. Each campaign focused on different aspects of our marketing approach, including target audiences, messaging, and monetization strategies. These campaigns provided valuable insights into targeting, messaging, and monetization strategies, helping to refine our approach for better user engagement and business outcomes.
One of the key growth engines we aimed to achieve, as outlined in the proposal, was product stickiness. We measured stickiness using the "very disappointed" rate. If 40% of Elia users indicated that they would be very disappointed if they could no longer use Elia, this signified that we had reached the product-market fit stickiness milestone. We tracked this metric monthly, asking new users on their first day of using Elia how disappointed they would be if they could no longer use the product. This data was collected via Amplitude. Over the 12-month period, the average "very disappointed" rate was 47%, indicating that we have achieved product-market fit. This conclusion is based on responses from 855 unique users.
Despite the high indication of product-market fit manifested as the stickiness metric, it was very challenging to find a target group with the highest willingness to pay and thus find a sustainable monetization business model. As part of the marketing campaigns, we experimented with various subscription models, ranging from freemium models where there was always some part of the free version available, to more strict subscription models with no free version, only a limited free trial. However, none of these models resulted in a sustainable subscription base. Consequently, we reevaluated our B2C strategy, concluding that Elia has the highest potential as a freemium model, not as a paid free trial only subscription. To ensure sustainable growth, we began exploring different B2B strategies and partnerships, which are still in progress and will be further developed.
Our project with Elia, an AI-powered personal assistant, has significantly advanced English language learning by integrating AI and psycholinguistics into users' daily activities, such as writing emails and watching videos, thus enhancing both engagement and efficiency. We achieved a notable 47% average "very disappointed" rate over 12 months from 855 users, indicating strong user engagement and fit. Although our various subscription models did not prove sustainable, we now see greater potential in a freemium model and are exploring B2B partnerships to drive growth. Insights from five marketing campaigns have refined our strategies, highlighting that productivity-related features yielded the highest user engagement. Moving forward, we will focus on enhancing Elia’s capabilities, exploring B2B opportunities, and expanding into international markets, using user feedback to guide our development. Overall, our project has pushed the boundaries of AI-driven language learning, providing high engagement and valuable insights into monetization, with promising prospects for future growth through B2B strategies.