Top Pages & Top Users
Keep two things in mind when analyzing your Data Export data:
- Rows are individual events created during sessions
- Individual sessions can be found by grouping on a compound key of
sessionid+userid
More information about how Fullstory defines sessions can be found here.
All SQL examples are written in Postgres SQL.
You can discover the top pages visited by your users by grouping on pageurl and then calculating the average sessions per user for each page.
select pageurl as "page",
count(distinct userid) as "unique users",
count(sessionid) as "total sessions",
"total sessions"/"unique users" as "avg sessions per user"
from fsexport
group by pageurl
order by "avg sessions per user" desc
Grouping on userid and counting distinct sessionid will provide the number of sessions for each user. You can use this to discover your most active users. Users that have been identified with FS.indentify() can have email addresses.
select userid as "user id",
useremail as "email",
count(distinct sessionid) as "sessions per user",
count(sessionid) as "total events"
from fsexport
group by userid, useremail
order by "sessions per user" desc