education & e-learning
education
AIDIFY: Content recommendation
engine powered by machine learning
Empowering the pharma industry with personalised learning
AIDIFY is a pioneering startup on a quest to deliver top-tier training materials, with a sharp focus on legal compliance across pharmacovigilance, clinical trials, and regulatory affairs. Through its subscription-based platform, AIDIFY introduces a mix of video microlearning, live webinars, and on-demand courses, all tailored to automate, personalise, and standardise the development process for employees in the pharma sector.
Miquido has collaborated closely with AIDIFY since 2020. Our course recommendation engine lies at the heart of a Learning Experience Platform (LEP), directing users towards achieving competency goals. Personalised recommendations boost user engagement by encouraging them to explore further learning opportunities and play a critical role in reducing churn rates. Over time, this approach has enabled AIDIFY to cultivate a community of loyal customers, laying a solid foundation for sustained business success.
96.5%
predictions’ accuracy
3 months
to deliver a recommendation engine
Challenges
Keeping pace with the pharma industry
The pharmaceutical industry is constantly evolving, with legal requirements that change regularly. This means that professionals must keep their knowledge up-to-date, which can be resource-intensive. To tackle this challenge, industry experts have launched a subscription-based educational platform called AIDIFY, explicitly designed for pharma employees. The founders of AIDIFY aimed to provide high-quality training materials to speed up the process of acquiring industry-specific knowledge and cater to each user’s individual learning needs. Their goal was to accelerate employee career development and support pharma companies heavily investing in workforce education.
Personalisation of learning experience
Traditional learning platforms often adopt a one-size-fits-all strategy that fails to address the unique needs and learning preferences. This generalised approach can result in a less efficient learning experience, with employees wasting time on materials that don’t align with their specific requirements. Personalisation is key to effectively engaging employees by ensuring the training they receive is relevant to their job role and career goals. The creators of AIDIFY recognised the importance of enhancing the learning journey for users and assisting companies in maximising their training budgets. Therefore, they set out to offer a distinct, data-driven, skill-based training framework tailored to each user’s needs.
Overcoming data scarcity challenges
When it comes to recommending career development courses, there’s a lot to consider: industry regulations, current trends, and user behaviour metrics. This is where AIDIFY faced a significant hurdle. In its early days, the platform struggled with a lack of detailed user behaviour data essential for training and fine-tuning recommendation algorithms. Without rich interaction data, producing precise and relevant course suggestions proved difficult.
To solve this problem, AIDIFY looked for a proficient partner in data science and machine learning. They needed someone who could build a top-notch recommendation system from scratch. This system would have to overcome data scarcity obstacles and improve alongside the platform, ensuring every user gets personalised course suggestions that fit their needs perfectly.
Solutions
Hybrid recommendations for enhanced learning
Miquido’s data science team has developed a recommendation engine that blends content-based and collaborative filtering to deliver tailored course suggestions. This dual approach ensures that recommendations are not solely based on a course’s popularity but are finely tuned to match each user’s unique learning patterns, preferences, and career aspirations. By identifying commonalities among users, the engine can suggest courses that have benefited individuals with similar profiles while also considering individual interactions, such as course completion rates and feedback. This customised strategy streamlines the learning journey, ensuring users efficiently gain the necessary skills.
Data-driven personalisation for optimal course matching
To tackle the challenge of limited initial data, Miquido employed a collaborative filtering approach that leverages a broad spectrum of user activities. By scoring key user actions on the platform, this method enabled the system to make accurate course recommendations early on. As it gathered more data from user interactions, the system’s ability to tailor course suggestions improved, ensuring a rapid enhancement in personalising the learning experience.
Utilising metrics such as click-through rate, course completion rates, and average course ratings, Miquido crafted a robust system that underpins the recommendation engine. This strategy not only addresses the issue of initial data scarcity but also guarantees that the platform evolves, continually refining its recommendations to reflect real user engagement and feedback.
Churn prediction module to boost retention
To mitigate user churn and further enhance AIDIFY’s value proposition, we have also introduced a predictive module designed to forecast the likelihood of users disengaging. This module utilises advanced analytics to generate reports predicting user churn, incorporating essential user data along with a percentage-based risk assessment of platform abandonment. The insights derived from these reports enable both the sales and analytics departments to take proactive steps in engaging with users at risk of churn, offering personalised incentives to retain them. This predictive approach not only helps maintain a satisfied and engaged user base but also provides valuable insights into improving the platform’s features and user experience, contributing to the overall quality and competitiveness of AIDIFY.
Results
Accelerated time-to-expertise of pharma employees
By deploying a system that tailors course complexity and content to each user’s progress, AIDIFY significantly speeds up the proficiency attainment of pharma employees. Early adopters have reported faster adaptation to new regulations, highlighting the system’s impact on reducing training costs and enhancing compliance. This innovation allows companies to address training requirements precisely and bridge skill gaps for every employee. With the ability to preemptively identify skill deficiencies, AIDIFY ensures that pharma professionals are equipped with the necessary competencies to excel in their roles, safeguarding both the business’s interests and public health.
Enhanced user engagement and retention
Miquido has developed a sophisticated hybrid recommendation engine that tailors course offerings by analysing user behaviour, completion rates, and feedback. Impressively, the engine achieved a recall metric score of 96.5%, underscoring its ability to identify and recommend relevant courses to users. Consequently, AIDIFY has significantly strengthened its market position, attracting an increasing number of corporate clients eager to equip their teams with seamless, continuous learning opportunities.
Market differentiation through data-driven personalisation
AIDIFY sets itself apart by using data science and machine learning to tailor learning experiences. The advanced recommendation engine fine-tunes course suggestions based on how users interact with the content. This level of precision in AIDIFY’s recommendations has caught the eye of the pharma sector, sparking initial partnerships. Pharma companies appreciate how quickly AIDIFY can develop their employees and adapt to the industry’s changes. The benefits for our client are clear: a better competitive edge, more customers, and the chance for higher pricing, all thanks to AIDIFY’s unique, effective, and personalised learning approach.
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