I am now working in a SaaS company which focus in B2B market.
Now I am facing a question, which I have no idea why it happens.
The question is: The bounce rate is too low according to google analytics.
Of course, this is normally a good sign, but below 3% bounce rate would not be true, especially significant traffic are searching for dating sesrvice, which is totally irrelevant to our business and I suspect there are some BOTs that brush the statistic.
Does anyone face the same question before, and how can I tackle it?
Many thanks for your help in advance!
The most common reason for such a low bounce rate is a duplicated tracking code on the site. This happens because the tracking
You can test your tracking code installation using the Tag Manager Assistant extension on Chrome.
The use of the extension is pretty straight forward just install, enable and open the site you want to test.
If you are having issues with the implementation you will see something like this.
Related
I have an image heavy art site and my FID score needs improving. The new Google algorithm taking place in June is going to punish me for having pages that take 256ms to load , but google analytics script takes up 156ms of that.
Should I remove it?
Remove only if you think Google Analytics is not important for you, There are some hacks which I personally do not recommend to resolve GA script issue shown in PSI but if you still wishes to resolve you can find helpful answers in this post. PageSpeed Insights 99/100 because of Google Analytics - How can I cache GA?
It might be a very stupid rocky question but I’ve never worked with Shopify before.
We have implemented Google Analytics via default functionality available with Shopify Plus. On top of it, I have added quite simple JS to track Consumer Funnel Steps and activated enhanced ecommerce feature.
One month later I have discovered the discrepancy in both number of transactions reported and the revenue that is nearly 50% which clearly indicates that something went wrong. My investigation has shown no patterns from the point of payment method/checkout process/device category. Our success manager told us that the process looks ok from their end and the issue is on our end.
Please help me to understand where else shall I look to identify the bug. Thanks!!
This is a common issue for Google Analytics and it happens on all ecommerce platforms and the main reason behind it is ad blockers.
About 20% of users use ad blocking extensions which prevents Google Analytics from firing and capturing any data regarding that visit (this also includes ecommerce data), thus, discrepancies are created between the numbers reported in Shopify backend and Google Analytics.
There are more reasons behind why the discrepancies might happen (some of them are of legit concerns like faulty tracking) but ad blocking extensions are probably responsible for most of the discrepancies. If interested, you can see the full list of transaction discrepancy causes here.
I'm trying to find a way to track "paid traffic" from Youtube, ie. people who click on one of our ads, got redirected to one of our videos, then clicked on a link in the comment section. At the moment everybody coming from Youtube appears under the Youtube channel in our analytics.
Yet, inside Youtube Analytics, I can see that 90% of people watching specific videos come from paid traffic.
I tried to see if I could get any possible information from the youtube APIs but it looks like nothing is useful, event to determine how could be the split between paid/unpaid traffic.
Also, impossible to find a split by video.. except in GA. Therefore, no possible link?!
1/ Is it possible to link paid traffic internal to Youtube and part of the "youtube" channel traffic in GA? data-wise or just mathematically?
2/ Is there a way to hadve an idea or approximate the convertion rate?
PS: I know this should not be seen a pure conversion channel*
To answer your questions:
1. Is it possible to link paid traffic internal to YouTube and part of the "YouTube" channel traffic in Google Analytics? data-wise or just mathematically?
As far as I know, yes it is possible. In fact, there's no better way to analyze your new brand channel layout than integrating it with Google Analytics. Reasons as given:
The main difference between YouTube analytics and Google Analytics is that the former provides data about the videos, while the latter provide data about the visitors of the channel’s pages.
To use this feature, please refer to the steps given in How to integrate your YouTube One brand channel with Google Analytics
2. Is there a way to have an idea or approximate the conversion rate?
I tried looking for documentation on conversion rate but it seems that this doesn't exist as also mentioned in Conversion rate between YouTube views and track sales
And, as suggested in Google AdWords Help, in tracking viewer conversions for video ads,
Since video advertising doesn’t always drive immediate conversions, we recommend that you look at view-through conversion data, which shows the number of online conversions that happened within 30 days after a viewer saw, but did not click, your video ad.
I hope that helps.
So I've been working on a website for a while. GA account has been up for a couple months but I waited for the website to be finished before putting up the actual JS tag.
In the meantime, the website is being HTTP password restricted (basic authentication) so it isn't even accessible unless you know the user/pwd combination.
To my surprise, I realized today that GA has logged several hundred views to the root of my website. Paths are mostly things like:
/
/?from=http://social-widget.xyz/
/?from=http://www.traffic2cash.xyz/
Bounce% and exit% both at 100% for all of them.
I realize this looks like referral spam, and there are ways to prevent it. Came across this upon googling:
http://botcrawl.com/block-social-widget-xyz-referral-spam-in-google-analytics/
My question is: how can GA log anything anyway when no tag is up and the website isn't even accessible?
Thank you very much in advance
Because it's spam. They hit Google Analytics directly with random GA codes and don't even go through your website.
GA can't tell if these are real hits (from website visits) or fake hits (from spam bots who hit GA directly calling the same ode as they would if on the website). Though arguably they should do more about this.
Massively annoying - particularly when first starting out as this can be a heavy proportion of your "traffic".
It's easy to set up a filter rule is to catch a lot of this by filtering on hostname. As they are randomly hitting GA and don't even know what website they are hitting GA for, they don't usually set this correctly. Real traffic should only come from yourwebsitedomain.com so add a filter for that.
STRONG piece of advice: abandon the default UA-########-1 tracking code of your new website -- simply do not use it!
Create a second and third property on the Admin screen, then use the tracking code for the third property. You will immediately see a lot less spam. No filters or segments necessary!
If you want the whole sad story about spam visits in GA, I have been maintaining the Definitive Guide article for over a year now:
http://help.analyticsedge.com/spam-filter/definitive-guide-to-removing-google-analytics-spam/
I've previously used statcounter, which does a great job. I'm looking to start tracking with google analytics as well, but it seems to be way off.
I tried to figure out the cause of the discrepancy and it looks like google is counting each page view times 5,10 or sometimes even more. For example, this is a site I barely use. I accessed it at 11:00 today. Instead of showing just 1 hit from me, its showing 10 users as having gone to the site
http://screencast.com/t/GT29OKzG
Similar things are happening with my other sites as well.
Do I have some weird setting turned on?
The unusual spike on direct traffic is most likely caused by spam, lately spam like free-share-buttons and similars, have been hitting with fake direct visits along with the referral.
The usual way to stop the spam by adding a filter for the referral won't work on this case since the fake direct visits will still go through.
To stop the fake direct traffic and any form of ghost spam, referral, keyword, page... you can use a filter that includes only your valid hostnames. You can find more information about this solution here
https://stackoverflow.com/a/28354319/3197362
And more details on the fake direct traffic issue here:
http://www.ohow.co/unusual-increase-in-direct-traffic-on-ga-spam/
Hope it helps,