timeframe that tagging was down? Is the any way to collect the data?

[Mr_Moorthi]

Is there a quantitative piece that can be added for the timeframe that tagging was down? X attempts, X tags, or X members.

[Jennifer_Dungan]

So when you say "tagging was down"... I assume this is a generic ask, for if Adobe's processing goes down, or say you have a bad deployment and your analytics breaks?

Really, in either case you will just end up with a hole in your data...  I don't really understand what you are trying to add... if tracking is down, nothing in your analytics implementation will be tracked, including anything that you add....

Unlike mobile apps that can enable "offline" tracking, that will collect info locally in the app, then send a batch of data once the user reconnects, I don't believe there is much you can do on a website... since the user is online to use a website in the first place; and I don't know how you would detect tacking down and store information to send later (and maintain all the proper timestamps and all the values to send later once tracking is back up and running).

Really, this is one of the reasons we use GA as a backup analytics system... we don't track as much or with the same granularity that we do with Adobe, but IF tracking goes down, we can at least see an approximate impact. If both go down simultaneously (i.e. someone deploys code that breaks everything) we sometimes just have to take the loss.....

Or are you looking for something that will notify you when tracking goes down, or there is a big (if not complete) drop or spike? If so, you are probably interested in Alerts:

https://experienceleague.adobe.com/docs/analytics/analyze/reports-analytics/alerts.html?lang=en

I like to use "threshold percents" rather than raw numbers in most cases, since traffic will fluctuate based on the time of day or day of the week (less traffic on weekends or holidays, less traffic over night). You will need to determine what works best for you.

Here is a good blog post about time of day, to avoid overnight false alarms: https://experienceleaguecommunities.adobe.com/t5/adobe-analytics-blogs/woken-up-at-3am-by-false-hour...

If I have misunderstood your ask, please let me know if there is something else I can help with. 

[Mr_Moorthi]

@Jennifer_Dungan  Thanks for your detailed explanation. We have updated the datalayer part besed on the certain requirement. But unfortunality Adobe not colleted the data during particular time period and we lost that data. Now customer wanted to know how many visitor logged in during that period.

[Jennifer_Dungan]

Was it down for the entire site, or just on the pages that you updated your data layer on?

[Mr_Moorthi]

Not Entire Site. AEM pages are working fine without any issue . Due to data layer change Data not collected for all the pages.

[Jennifer_Dungan · Accepted solution]

OK, at least that may be something to work with... not knowing your site or the behaviours I will be keeping this generic... 

So it sounds like you want to know how many people "logged in" (I suspect you are tracking login success on the page that wasn't working), and you have no user status on other pages.

Do you have pages or features which are restricted to logged in users that were still tracking.... Depending on how popular they are (like this is something logged in user almost always go to cause its the reason to log in, vs something they rarely visit) this could be a semi-indicator of your logged in users.

Or many you have an actual click tracking on your buttons leading to the login screen... now of course there's going to be some people who abandon this flow... but if you look at historical clicks to completions.. you may be able to do some approximate math to calculate the number of successful logins based on historical success rates?

The other possibility, is you could try to use Raw Data feeds to look at all the referrers. Assuming the page following login was being tracked.... while we all know that internal urls are filtered from our reports... the raw data feed stores the full referral information. It may be possible to see how many people came from your non-tracking login screen.... but of course, you then have to process this data to get rid of the exclusions, and if people can navigate from the login page to where ever they land (i.e. successful logins send people to the home page) you could still be over-counting based on the abandonment....

While none of the above are ideal, I listed them in the order I thought might yield the best "approximation".. but these may also inspire another solution because you have familiarity with your own site and there may be another calculation that you can do.

Good luck.