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Honeybadger

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So I now got 700 push ad subscribers
always get unsubscribes each push
pushing only blog posts
last push got
  • 700 sends
  • 11 clicks (1.5% CTR)
  • 2 unsubscribes (0.3% unsub rate)
Hey @T J Tutor
cant find the correct forum for push ads
looked under traffic sources
 
Pretty cool
got 60 push visits today from 3 pushes
next step --> set up GA integration
it will show who came from push
& how their metrics compare 2 site avg
all feeds back to Google via CruX
so it affects SEO & ranking
CruX stats need 2 be better than organic SEO
or at least similar
I think 0.3% unsub rate from 700 is ok
so thats a good sign
but I need 2 be sure --> GA will tell me
 
more than 750 push subscribes
if it keeps going I will have 1,000 push subs
in 12 days from today
Tuesday, July 19
got extra 100 visitors last 2 days from push
website return rate is 26%
they are not bots Ive checked GA
 
design a MySQL (or other relational) database.table and write some queries of a few months data

I like VB & Access & SQL for this, but easily done with VBA and MS Word too. Of course there are many other options.

Yeah, would definitely be a great little project. I used to do this with everything in the early days.
 
Does each push user have an ID that you can factor statistics for?
like push_user 345 and his visit history
|date | time|creative id| then a walk-about-URLS|
like a CSV you can sort in exel (or google sheets, calc [office libre])
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Really. I think you would need to design a MySQL (or other relational) database.table and write some queries of a few months data --like 90 days
I would try to calculate,
  1. the user churn (attrition [rate and number of days])
  2. the best creative image ids used
  3. the most popular URLs and their creative
90 days might give you 20K datapoints for a sample.
 
I like VB & Access & SQL for this, but easily done with VBA and MS Word too. Of course there are many other options.
Truth is; this is super trivial (for me) when the data is collated correctly from its source.
My problem is taking the time and justifying the expense to create the data in the first place.
 
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