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@Suvidit-Academy thanks for the response, however, it seems terribly unlikely that these brands all had a legitimate massive fall off in search interest all on the exact same date...

I am finding several instances of weird data drop offs on Google Trends at 1/1/2022. It seems like it's for data associated with a type/category as opposed to a search term. Here are some examples of "search interest" dropping suddenly off to next-to-nothing for prominent brands.

• Patagonia / clothing company
• Lands' End / clothing company
• Carhartt / workwear company

Example screenshot.

Does anyone know what the cause of this is? Has Google stated anything directly about why the data suddenly changed so significantly?

@Kateparish Thank you -- I think this is it. These are definitely not paid ads or a featured snippet. It's discouraging to see how thoroughly Amazon and the big box stores dominate these listings...

What are these called (screenshot attached)? They are organic product listings in the body of the SERP that look just like paid ads, but are placed below paid ads.

I would like to read up on how to optimize for them, but am having trouble finding information.

Curious if anyone else is having this problem. I have, for example, a page that is listed in Search Console as having a CLS of .44 - it is listed as a "CLS issue." The same page rendered in LightHouse shows 0 for field data CLS and 0.02 for lab data (both in the "green"). It has been over a month since I made updates to the page to improve CLS. I tried to submit a validation in Search Console, but "validation failed." I'm not sure what else to fix on the page when LightHouse data shows it as in the green! I have the same issue with other pages as well.

Super helpful. Thank you!

Does anyone know if it is problematic to have a space between the "no" and the "follow"? I just discovered our CMS has been inserting a space and am trying to understand if it the reason why something that we were trying to keep from being indexed has become indexed.

Hi everyone,

I've been reading the 2017 report by Groupon and the 2017 article by Neil Patel r.e. dark traffic. Both of these articles work on the assumption that most long URLs are not direct traffic because people wouldn't type a long URL into their browser. However, what happens to me personally all the time is that I start typing a URL into the browser, and the browser brings up a list of pages I've visited recently, and I click on some super long URL that I didn't bookmark but have visited in the past. That is legitimate direct traffic, but it's a long URL. I'm just wondering if there's something flawed in my reasoning or in the reasoning of Patel and Groupon. Maybe most people aren't relying on browsers like I am, or maybe things have changed a lot in the past 3 years. What do you think? And are there any more recent resources/articles that you would recommend r.e. trying to parse out dark traffic?

https://neilpatel.com/blog/dark-traffic-stealing-data/

Thanks!

Thanks for the reply. I'll check out the links you included.

I thought it might be helpful to show an example of what got me thinking along these lines. This is a study about A/B testing of title tag changes. They don't say they accounted for position fluctuation; maybe they didn't, but it seems like you'd have to in order to have meaningful results.

https://www.rankscience.com/coderwall-seo-split-test

For example, let's say you want to A/B test a title tag change. You are hoping to identify whether a title tag change increases CTR. But, position is always fluctuating a bit and that affects CTR, too. So, I'm interested in how you could hold position constant in order to isolate the change in CTR that is due to the title tag change.  Does anyone know of resources/tools/tutorials for how to do this?

It's been... a very long time since I took statistics (-:  I have access to Excel, MS Access, and R studio.

Thanks for the info. My concern is that there are some instances where Google is splitting the traffic between two PDP urls. I guess it's good to know it is a problem others have. From what I've read and what you've said, I don't see a solution without eliminating cross-listing of PDP's between relevant categories, and doing that (I think) would make for a poor user shopping experience.

We have products that are listed across multiple categories. This results in muliple urls for the PDP, for example:

mystore.com/shirts/shirt-101.html

mystore.com/shirts/pink-shirts/shirt-101.html

They make use of the canonical tag and point back to only one product listing url, however Google has indexed both urls in some cases.

Has anyone else run up against this and does anyone have advice on how this should be handled?

Thank you everyone for your responses. Sorry for the belated reply -- I didn't realize this question had garnered any responses. This is helpful information and thanks again.

I've had someone tell me that google doesn't pay attention to H3 tags -- only H1 and H2.  I haven't found much online to back this up or discredit it; thought I'd ask the Moz community!

Thanks!

This Moz blog references a page load time of 2-3 seconds. I've seen the 3 seconds referenced elsewhere, but I'm not sure what that measurement is -- is the target a 3 second speed index, or 3 second CPU idle?  Or something else?  Curious if anyone knows the answer.

https://moz.com/blog/website-page-speed

Thank you!  That helps a lot.

Thanks so much for the reply. I am still struggling to understand when it's best to use robots.txt

I think I understand that url parameters are best handled in the search console parameters tool, and if you want to keep a page out of the index, it's best to use meta noindex rather than blocking it in robots.txt

What would be an example of when you would want to disallow something in robots.txt?

Hi, wondering if anyone can point me to resources or explain the difference between these two. If a site has url parameters disallowed in Robots.txt is it redundant to edit settings in Search Console parameters to anything other than "Let Googlebot Decide"?