With the usage of digital marketing, measuring the success of sites is the most controversial of topics. Because it is the most popular search engine in the world, Google offers tools that show clients detailed traffic source reports.
Google Analytics Reports were a mystery that attracted people’s attention. Therefore, most curious specialists decided to study Google Analytics Reports to show clients how efficient it is. Some of these specialists started to investigate a year-long case study regarding whether Google Analytics Reports were safe or not.
While many people have praised the service that provides people with searching traffic on Google Analytics, some of them are still approaching it with suspicion.
In this article, you can examine a long-term case study, its rates, and its changes by looking at the researcher’s experience with third-party statistical services. Most of them actually under-report traffic.
Let’s consider two things and decide together:
But what cannot be rationalized is how Google Analytics thinks a site has lost 50% of its traffic when user server logs indicate that traffic has held steady.
What is even more curious is that some pages continue to perform well according to both Google Analytics and server logs, whereas other pages show a severe drop in traffic from Analytics but either no drop-off or significantly lesser in server logs.
For the month of January, the Google Analytics Report of one page of a popular television actress' page showed 6000 unique visitors and 8100 page views.However, according to the researcher's server log, that page received 10,000 views (disallowing for known robots).
For July, Google Analytics Reports say the same page received only 700 visitors and 900 views but the researcher’s server logs indicate over 8,000 views. While we don’t have the opportunity right now to look at the raw logs, sometimes “server software lumps data” even when it doesn’t want to be lumped together, but nothing like this kind of discrepancy has ever been shown.
For a more specific example, a white cheese dip page showed more than 9,000 views in January according to server logs and more than 7,000 in July for Xenite.Org and Google Analytics show about the same numbers for those months.
NOTE: This site is still available and is operating as science fiction and fantasy domain. Also, for the white cheese dip example, Summer drop-offs are typical for Xenite.Org, which has a large appeal among students of all ages.
The discrepancies vary across the selection of pages.
For Xenite’s home page, over 12,000 visitors viewed it in January but Google only showed 2200.
In July, Google thought the website only received about 800 page views on the main page but server logs indicate 3,000. Maybe the robot filtering didn’t work the way it should have on the researcher’s server logs.
What it found unusable in Google Analytics' testimonials from other people is that all the overzealous recommendations fail to mention any comparisons whatsoever.
While the case study is intended to run through till the end of the year, the declining data patterns for Analytics make absolutely no sense whatsoever.
Another traffic measure comes in the form of referrals from Google.
In January, about 28,000 referrals (as Big Daddy rolled out) were accumulated from google.com/search (just one of many Google referring URLs).
In July, about 16,000 referrals were recorded from the same URL. It can be concluded that some search placements were lost in July for a while, which happens occasionally. And as mentioned above, we can normally see a decrease in traffic during the summer months for the selected website (We’ve been tracking Xenite.Org’s traffic for nine summers now — this is a normal drop).
The researcher's server logs indicate they had 97,000 visitors in January and 81,000 visitors in July. So while a greater proportion of the summer traffic comes from non-Google sources, they didn’t lose almost 50,000 visitors — which Google Analytics data suggests it should have been.
So, the question to the rest of you is:
NOTE: This was not a sudden drop in Analytics data — the overall numbers have declined each month.
Source: Michael Martinez
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