This is a case study on collaboration tool company that helps teams or individuals organize, track, and manage their work.
For this case study, I will look into user adoption. The company defines an "adopted user" as a user who has logged into the product on three separate days in at least one seven-day period. I believe that adopted users are more likely to be successful at using the collaboration tool in the long term than those that are not adopted, so I want to know what things are likely indicators of future adoption. With this in mind, I will identify which factors predict user adoption.
My work will focus on improving this experience to increase adoption, so I'd like to know how successful the collaboration tool currently is at getting different types of users to adopt.
For the privacy of the data, I will only make the dataset visible in this Jupyter Notebook without posting the actual data on github.
- Investigate user journey for each demographic (Guest vs Full Member) to detect drop-off points and troubleshoot.
- Optimize the on-boarding experience that is tailored for different demographics.
- Especially, for Personal Project sign-ups , we can prompt these users to create their own project so they will continue to use Asana even after finishing working on other's project.
- Encourage Full Member to explore other premium features on Asana other than their cross-team projects so they can create their own documentation/plans for their individual or team work.
- As the likelihood of adopted users for Google sign-ups are the highest, we should expand this fast and seamless sign-up experience more by partnering with Facebook, Linkedin, Outlook, etc. to accelerate more sign-up growth rate and user adoption.
- Emails are not effective at improving user adoption, so we need to extend the analysis on other messaging platforms to test which other communication channels can do a better job at engaging users (push, in-app messaging, etc.)
- Since the high growth rate in 2014 greatly impact the user engagement and adoption, we can expand the analysis to find key success indicators on user actions or product features that best pivot growth and adoption rate during 2014.
- Regarding further exploration, I am keen on exploring (1) Does the size of members in an organization affect adoption rate? (2) Which actions do a team or an individual took that best indicate adoption rate?