Data Science for Platform Design and User Engagement

Data Science for Platform Design and User Engagement

Updated 10 months ago

An important measure of success when launching a new product is your user's level of enagegement on the platform.

In most cases, high levels of user engagement depend on the ability of your platform's functionalities to meet your user's needs, coupled with a good user experience, and overall design of the platform.

It is often very difficult to undo the effects of a poorly designed platform once it is already in production.

At PĂ´leFLS, we are in the development phase of an open bilingual accelerator. As part of my job, I conduct research that informs developers about features/ functionalities that should be included and how they should be rendered.

Most importantly, I am constantly on the lookout for innovative ways our team can integrate and leverage functionalities that will achieve a high level of community engagement among our target stakeholders.

For that matter, we decided to launch a social study that will assist our team to understand our stakeholder's preferences. We intend to carry out the following steps:

  • Identify existing platforms and communities where our target stakeholders are actively producing the data we need (e.g. Social media and review sites).
  • Mine user experience reviews about similar ( FSL, ESL, Second language acquisition, bilingualism or immersion) platforms,  from various stakeholder perspectives.
  • Classify stakeholder sentiment and extract useful knowledge about positively reviewed platforms.

Where our desired outcome is:

  • To understand how to translate the concept of an engaged community with our target audience into functionalities, and design of our platform.

This post (and a few more in this series) will serve as a project update page for this study. Stay tuned!

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