Discussion: Analytics & Tracking

Hi all, as a Data Engineer, I believe Analytics are important to optimising and improving the features of any app - Even if it’s open source. For this instance, I’d like to start discussing the possibility of adding these after an MVP has been implemented.

To protect the safety and privacy of our users, we will not gather personal data: IP Addresses, Latitude/Longitudes, etc.

We could tracking the following:

• Date joined
• Cohort
• Country (Which would come from location and/or venue)
• Events attended (This can be calculated from rsvps, events)
• Browser type & version (Happy to remove them as well)
• Sponsor activity and engagement by venue
• Social engagement by venue

NOTE: All tracking options would be Opt-In and customisable. This means we would NOT track anything without consent from a user, under any circumstances.

[erictleung]

@timrodz thanks for kicking off the discussion (also great to be here @QuincyLarson 😄).

One thing to consider in this discussion is why we’re collecting this data. Typically, analytics (based on my knowledge) is for maximizing profits. I don’t believe this is the case here.

So some things to consider are specifically what kind of questions or insights do we wish to gain from collecting this data? From the issue I linked to earlier, this would be an interesting use of have a distributed recommendation system. So one thing we may want to collect is self-reported tags or terms that describe a group.

Some questions we might want to ask in order to figure out what data to collect:

• Which companies are sponsoring the most events? (This will give an idea of which companies are invested in open source or whatever themed organization)
• What kind of venues are friendly to host events? (In aggregate, we could start recommending places to consider that might be friendly to host if one venue declines)
• Based on even descriptions/titles, which are the most interesting/attended? (Gives a feel to what the audience/community is interested in)
• Based on even descriptions/titles, which are the least interesting/attended? (Do a postmortem on why these events were not as popular for future planning purposes)
• What is the distribution of chapters around the world? (Purely from an interesting statistic and possible for recommending local groups to others)
• What is the rate of new chapters being created? (Interesting statistic to know)
• Which chapters (freeCodeCamp-associated and not) are similar to each other that we could recommend? (Recommendations for other interesting events)

Having this list could also make collecting data more transparent if we can also give a list of questions we’re trying to answer. I’ve recently started using SyncThing (kind of like Dropbox but P2P). When they first ask to collect data from you, they gave an example JSON of the kinds of data they would be collecting. I really liked this level of transparency. Just something to consider.

tl;dr; first come up with general questions/insights we want in order to help brainstorm what data to collect

[Cheukting]

Hello data people! As a data scientist, I have the same question. I think one reason why meetup was so powerful is its ability to suggest people to other groups and events in the same city. Therefore some recommendation function would be great! To achieve we need to somehow have a maybe centralize user data storage. I hope this will not contradict the idea which most of the people involved in this project agree, decentralized the hosting of the app.

Looking forward to having discussion regarding the data issue.