Google Document on Data Freshness for Google Analytics

Data freshness in Google Analytics, as well as data processing time, can be a key aspect of gaining a competitive edge.
SIA Team
December 2, 2021

The thing that’s significant about data processing and data freshness in Google Analytics is that, generally, the larger the data processing time, the more comprehensive the report. 

What do I mean by that? 

I’ll get to that shortly. 

Yesterday, I came across this tweet (which was a retweet from the Google Analytics Twitter channel), 

That tweet didn’t link anywhere off of Twitter, but upon doing some research, I came across this Analytics Help page: Enhanced Data Freshness.

Here’s a partial screenshot I took: 

analytics data freshness chart

But, in a quest to know more, I also watched this video, which, as of 2021, is about 4 years old, so the data might be a little outdated, but the basics are the same:

And then I got it.

Remember how I said that “the larger the data processing time, the more comprehensive the report?”

Data Freshness in Google Analytics: Larger Time Frames, Better Conclusions

So, for the smaller time frames (that is, for the  Enhanced data freshness, which is a 10-minute to 1-hour time frame) you can find out what’s happening right now (or almost right now).

It’s a good time frame to use when you want to test out quick changes (such as the position of a buy button), and you have the traffic to do so at the moment.

Now, in the heading of this section, I say, “larger time frames, better conclusions.” I say that because, if you’ve ever worked with medium- to long-term charts, you know that the smaller the time frame, the more ‘noise’ there is, but when you look at larger and larger time frames, the more you can see a pattern. 

That holds in trading, and the same is the case here. If you want to find a trend, it’s better to look at the larger time frames. So, in terms of data freshness, that would be standard daily reports.

But, don’t just look at each day individually; instead, look back over days, weeks, and months to see if you can sense a pattern or a trend. 

Maybe there’s something seasonal?

Source: Maatwerk Online - Lars Maat Twitter channel