Structuring emails

Ok, after one week of reading emails, I’ve been able to structure 2100 of them. 2071 to go… It is becoming obvious most e-mails are about payment, not being able to log in. Lots of emails are replies to newsletters: mentioning to be unsubscribed, mentioning their mail address changed of wanting to receive more information about courses.

But there are lots of emails left which can be structured into these categories:

  • complaints
  • requests
  • asking for support
  • questions
  • remarks
  • commercial offers
  • wishes

NOTE TO MYSELF: It might be interesting to study the amount of support asking emails per month, related to the amount of people registering, login in. Did the amount of support mails increase? Because there are less members logging in? Because the quality of courseware is better? Because information isn’t up to date?

INTERESTING: I’ve ┬áread a lot of emails which I rarely receive nowadays, due to improved or added features.


  • asking to be unsubscribed from the newsletter (added feature to unsubscribe in newsletter)
  • asking for password (added “forgotten password” feature)
  • general questions (added FAQ to contact page)

Also nice to see people are just emailing because they are thrilled to learn, sending new year messages or just saying they are pleased with the quality.



EPP: reading and structuring (a lot of) emails

Ok, let’s start and figure out what can be improved in zelfstudie.be. By doing an case study I’ll try to find out in 3 stages which new or modified features are wished by the members/students of zelfstudie.be

In the first stage I’ll gather all emails from the last years. From 19 July 2010 to 1 June 2014 this are exactly 4227 emails. After deleting spam, messages from Twitter, unsubscribes from newsletters 3234 emails are remaining. I somehow underestimated the amount of hours needed to read these mails.

By putting them in subfolders I can structure these questions, complaints, remarks, commercial offers and wishes.

The second step will be extracting the most interesting needs/wishes/questions and linking these to members who spent the most time on the website. These numbers are gathered by Google Analytics and on the other hand an own written script.