Hi,
I see that the Organic traffic has hiked up from 1807 visits to 2134 visits, 2292 visits, 2433 visits correspondingly and again has dipped to 1628 visits and 1208 visits in a week.
1. Where can we check what caused the traffic hike and dip suddenly in the same week?
2. I see a huge difference in the number of visits in Adobe and Google analytics for the same dates. The visits recorded in Adobe Analytics has 400 visits (per day) more than the visits recorded in google analytics. Can you please let me know what could be the reason for this difference in the number of visits.
Any help is greatly appreciated.
Thanks in advance.
Prathiksha.
Solved! Go to Solution.
Same problem occurred to me few months back, However, in my case paid search traffic dipped and natural search traffic spiked. Below is my observation :
1. The Paid search cid or utm code had any junk which is preventing detection of paid traffic and attributing to natural or direct
2. Paid campaign click through link was http//:www.abc.com. However, the landing page is https//:www.abc.com. Therefore, upon redirect the cid/utm codes are not piggybacked and shows as either direct or natural traffic.
Hope this helps.
Thanks,
Pradyut
There can be multiple reasons to it. Most common ones are:
Also, data comparison with GA isn't recommended considering different algorithm and data interpretation methods each tool uses.
Same problem occurred to me few months back, However, in my case paid search traffic dipped and natural search traffic spiked. Below is my observation :
1. The Paid search cid or utm code had any junk which is preventing detection of paid traffic and attributing to natural or direct
2. Paid campaign click through link was http//:www.abc.com. However, the landing page is https//:www.abc.com. Therefore, upon redirect the cid/utm codes are not piggybacked and shows as either direct or natural traffic.
Hope this helps.
Thanks,
Pradyut
Thank you very much AbhijeetKMishra
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Thank you so very much pradyut.c. Appreciate the help
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I would recommend reading up on the following KB article: Troubleshoot spikes and drops in data
Your predicament is one that makes data research kind of fun, since you'll be diving into your data to determine what the comon ground was. Segmentation will definitely be your best friend, so be sure to use it liberally t try and identify any common threads. You can also use workspace's anomaly detection, which might be able to point you in the right direction of what the root cause was.
Good luck!
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