According to the Google sampling documentation, sampling is done based on sessions (fact). In Google MCF queries, sessions are not available as a metric or dimension (fact?) Now I wonder: how is sampling done if there is no metric or dimension for sessions (and date)?
I suspect that sampling for Google MCF is done based on a maximum number of rows of 10.000 for each query. Are there more than 10.000 results? Than sampling is true. Is this correct?
Use-case: let's say I make a query and the "TotalResults" are 67540. Does this mean that I can get all the unsampled data with querying 7 calls (6x10000 and one time 7540 rows)? How do I know which dateranges to query than?
Tried some different approached and found out that the sampling is doe based on sessions and dates, same as the other data from the API.
Related
In the internet i tryed to find information, but it very hard ,because in any forums i found diffrent information.
How many hits i can collct in GA4 property in one month without sampling and limits?
In GA3 i could collect only 10M in one month, but in GA4 i don't know.
And after 10M in month, data will be collecting or Google will stop collect new data more than 10M hits?
In official Google docs - https://support.google.com/analytics/answer/11202874?hl=en
They say Explore sampling limits = 10M events per query
What does it mean?
It is impossible that in the report there were more than 10M lines?
It means that when you generate a non-standard report involving 10 million hits, sampling is applied. In that case you can reduce the time frame to involve fewer hits.
I would love to understand what I'm looking at - why are the numbers different in this report when I add a segment?
This is the report without any segmentation:
This is the same report with the Mobile Traffic segment:
There two methods that Google uses to identify the number of users.
Calculation 1: Pre-calculated data
This calculation relies only on the number of sessions in the given date range and the time of each session. (This is determined by technology managed on the device, like a web browser, and is often referred to as the client-side time.) Because the result of this calculation can be added to the pre-aggregated data tables, Analytics can reference the table to quickly retrieve and serve this data in a report, including when you change the date range.
Calculation 2: Data calculated on the fly
Calculation 2 is based on the way you assign, collect, and store persistent data about your traffic. There are many solutions you can implement to customize this, but the most common way this data is going to be assigned and stored is through cookies managed via a web browser.
Adding a segment will force GA to calculate the data on the fly and that's why you are seeing a difference in the numbers.
Are you using GA free or 360? and the time range you are using is same in both reports?
You can also have a look into the Google article https://support.google.com/analytics/answer/2992042?hl=en
You are victim of sampling:
https://support.google.com/analytics/answer/2637192?hl=en
Sampling applies when:
you customize the reports
the number of sessions for the report time range exceeds 500K (GA) or 100M (GA 360)
The consequence is that:
the report will be based on a subset of the data (the % depends on the total number of sessions)
therefore your report data won't be as accurate as usual
What you can do to reduce sampling:
increase sample size in UI (will only decrease sampling to a certain extend, but in most cases won't completely remove sampling)
reduce time range
create filtered views so your reports contain the data you need and you don't have to customize them
We are running the Google Analytics free version and I'm seeing some inconsistent results regarding data sampling. I have tried my requests in Google Analytics Query Explorer, the GA Sheets add-on, and within the GA interface.
Basically, I am comparing results from a complete date range against the sum of results for that date range broken into smaller chunks (to reduce/remove the chance of sampling occurring). Metrics are sessions, transactions, and revenue. I have a session-level dynamic segment applied: sessions::condition::!ga:landingPagePath=#/thanks
As you may expect, the results from the single request are different (counts are lower) than those from summing the multiple smaller requests. For example, sessions are 45,311 vs. 51,596 and income is further apart. This implies that sampling is being used for the larger request. The trouble is that the API response explicitly says that sampling is not used in any case, i.e. "Contains Sampled Data" equals "No", even for the full date range within which our property should be exceeding the 500,000 session threshold for sampling to kick in.
I'm almost certain that the results from summing smaller date ranges are correct, as these are pretty close to what we see in our CMS analytics.
Can anyone explain the mechanics behind this? Is GA doing some sort of behind-the-scenes sampling to produce this inconsistency?
Thanks,
Daniel
Sounds like sampling. Check all your sources to see if they contain sampling and make sure you have Sampling Level Set to "HIGHER_PRECISION".
1) Google Sheets Google Analytics Add-On in cell B6 of the data for each query check to see if it says "Yes: for "Contains Sampled Data"
2) Google Analytics Query Explorer in the header below your profile name check to see if it says "Contains Sampled Data: Yes"
You are on the right track in breaking your query down into smaller chunks with smaller date ranges to avoid sampling. Here is a post on how to Avoid Google Analytics Sampling using Python
I'm seeing inconsistencies between reported ga:sessions, ga:users, ga:pageviews from a query spanning a year through the API, and the same date range from the GA website.
I've been able to match ga:sessions & ga:pageviews exactly by requesting every month separately and summing the values, however in the case of ga:users I am still seeing wildly different figures between the numbers returned by GAPI and the GA website.
The number is actually larger than the year's figures when I sum the month's figures, and both numbers are higher than the values reported in the GA website.
What dimension/metric could GA be using for 'Users'?
I suspect your having an issue with sampling level. If the request you are making returns a large enough amount of data in this case selecting a full years worth of data. The server will return the results sampled.
Sampling
Google Analytics calculates certain combinations of dimensions and
metrics on the fly. To return the data in a reasonable time, Google
Analytics may only process a sample of the data.
You can specify the sampling level to use for a request by setting the
samplingLevel parameter.
If a Core Reporting API response contains sampled data, then the
containsSampledData response field will be true. In addition, 2
properties will provide information about the sampling level for the
query: sampleSize and sampleSpace. With these 2 values you can
calculate the percentage of sessions that were used for the query. For
example, if sampleSize is 201,000 and sampleSpace is 220,000 then the
report is based on (201,000 / 220,000) * 100 = 91.36% of sessions.
When requesting from the api the Default sampleing level is used this is in order to increase speed of the request. You can change that by sending specifying the samplingLevel to use in your request.
samplingLevel=DEFAULT
Optional.Use this parameter to set the sampling level (i.e. the number of sessions used
to calculate the result) for a reporting query. The allowed values are consistent with
the web interface and include:
•DEFAULT — Returns response with a sample size that balances speed and accuracy.
•FASTER — Returns a fast response with a smaller sample size.
•HIGHER_PRECISION — Returns a more accurate response using a large sample size, but this may result in the response being slower.
I try to pull out the (unique) visitor count for a certain directory using three different methods:
* with a profile
* using an dynamic advanced segment
* using custom report filter
On a smaller site the three methods give the same result. But on the large site (> 5M visits/month) I get a big discrepancy between the profile on one hand and the advanced segment and filter on the other. This might be because of sampling - but the difference is smaller when it comes to pageviews. Is the estimation of visitors worse and the discrepancy bigger when using sampled data? Also when extracting data from the API (using filters or profiles) I still get DIFFERENT data even if GA doesn't indicate that the data is sampled - ie I'm looking at unsampled data.
Another strange thing is that the pageviews are higher in the profile than the filter, while the visitor count is higher for the filter vs the profile. I also applied a filter at the profile to force it to use sample data - and I again get quite similar results to the filter and segment-data.
profile filter segment filter#profile
unique 25550 37778 36433 37971
pageviews 202761 184130 n/a 202761
What I am trying to achieve is to find a way to get somewhat accurat data on unique visitors when I've run out of profiles to use.
More data with discrepancies can be found in this google docs: https://docs.google.com/spreadsheet/ccc?key=0Aqzq0UJQNY0XdG1DRFpaeWJveWhhdXZRemRlZ3pFb0E
Google Analytics (free version) tracks only 10 mio page interactions [0] (pageviews and events, any tracker method that start with "track" is an interaction) per month [1], so presumably the data for your larger site is already heavily sampled (I guess each of you 5 Million visitors has more than two interactions) [2]. Ad hoc reports use only 1 mio datapoints at max, so you have a sample of a sample. Naturally aggregated values suffer more from smaller sample sizes.
And I'm pretty sure the data limits apply to api access too (Google says that there is "no assurance that the excess hits will be processed"), so for the large site the api returns sampled (or incomplete) data, too - so you cannot really be looking at unsampled data.
As for the differences, I'd say that different ad hoc report use different samples so you end up with different results. With GA you shouldn't rely too much an absolute numbers anyway and look more for general trends.
[1] Analytics Premium tracks 50 mio interactions per month (and has support from Google) but comes at 150 000 USD per year
[2] Google suggests to use "_setSampleRate()" on large sites to make sure you have actually sampled data for each day of the month instead of random hit or miss after you exceed the data limits.
Data limits:
http://support.google.com/analytics/bin/answer.py?hl=en&answer=1070983).
setSampleRate:
https://developers.google.com/analytics/devguides/collection/gajs/methods/gaJSApiBasicConfiguration#_gat.GA_Tracker_._setSampleRate
Yes, the sampled data is less accurate, especially with visitor counts.
I've also seen them miss 500k pageviews over two days, only to see them appear in their reporting a few days later. It also doesn't surprise me to see different results from different interfaces. The quality of Google Analytics has diminished, even as they have tried to become more real-time. It appears that their codebase is inconsistent across API's, and their algorithms are all over the map.
I usually stick with the same metrics and reporting methods, so that my results remain comparable to one another. I also run GA in tandem with Gaug.es, as a validation and sanity check. With that extra data, I choose the reporting method in GA that I am most confident with and I rely on that exclusively.