Zombie Traffic from Google and Traffic Shaping/Throttling - Analysis

[tedster]

We need a dedicated thread to look at this odd phenomenon being reported by a subset of our members. It really isn't about any particular "update" because the apparent signs have been reported since 2008.

I have personally seen just a few examples of traffic shaping and nothing I could really call zombie traffic, but I think it's time for all of us to take the reports seriously and at least give advice on how to analyze what these webmasters are seeing.

To truly make sense of this, we'll need to pull in many areas of Google that we rarely talk about. This ain't your daddy's SEO! Here's a pretty good overview, from 2010: [webmasterworld.com...]

[TheMadScientist]

Yeah, but we're not talking about GoogleBot (I hope), because that should be simple to identify as GoogleBot (or Google in general) via IP Address and hopefully we're not missing that...

One of the interesting posts in this thread is relating to previews ... I got a Google or Bing IP Address (I don't remember which it was for sure) for preview requests in my stats rather than a visitor's IP Address as an X-Forwarded-For like it should be for a while ... Has anyone tried tracking the 'zombie visits' by omitting the X-Forwarded-For from IP Logging and running an IP Lookup on the requests for the page(s) in question during 'zombie hours'?

If you don't track the X-Forwarded-For you should get the 'farthest down stream' requesting IP Address, which would be Google if it's preview related (and they do (or did when I tested) send keyword info with preview requests at least as much as they do for anything these days lol) and it did trigger JavaScript events, which would mean it would show in Analytics and other JS stats as a visit, but they were all really short bounces...

[SEchecker]

@ The MadScientist

I’m sorry m8 I mixed you up with bluntforce

Still I do not agree on many things you telling. But do appreciate your intention to help!



@xcoder

We did implement polls: like did you found what you was looking for so on ( based on the poll the user satisfaction shows the % our bounce reflecting the % when there are no Zombies), we also tried to block posts with a javascipt pop up what requires interaction to proceed forward... I have watch heatmap records. The content under the pop up is scrollable but in shadow... All of the zombie visitors still have the same pattern and arrearage time on site.. some seconds....and all come to the site scroll up and down (note that they still have a pop-up 500 x 500 in the middle of their screen, offering something 100% related to the content they visit for FREE)). They stop during the 3 - 4 sec scrolling mainly by images and keywords. The majority of them closes the popup after 3 - 4 seconds. My experience of average users shows that they rather need some time to read the pop up and not scrolling nowhere, use the FREE offer or close it instantly....

Again that is just an observation what might not provide very accurate data, but it does show something and I think its important to keep on tracking this phenomenon... but @frankleeceo posts could have some impact on this … that already crossed my mind but I’m still not convinced or missing out some data...



@frankleeceo

Good post thanks for the input!

I personal have the theory and this would be somehow confirm with the observations, that G tries to split BUYERRS from INFO SERACHER with different data sets. I’m seeing G very soon in the situation to offer the KNOWLEDGE SEARCH what will be not any more the SEARCH we are used to know and where are ALL included. On the other hand THE ONLINE BUSINESS SEARCH what would include all websites making money by selling services, products so n... This is already going to happen to some degree, since G did implement the paid G SHOPPING.

How do I react on this my theory?

I did rewrite some meta descriptions and made some slight on pages content changes, containing our product names. So actually I deleted the product names from the meta description, titles and content. This should test the performance pages with product names included via non product mentioned posts... I do not adore anyone to follow this practise btw... Its very risky...



@ All posters requiring data observation sales vs non sales...


Following patterns are observed on this our site:

1. Steady daily sales when no zombies on the site
2. Higher sales on payment days
3. No sales within hours when a zombie period starts (zombies coming and going its not like 7/7 24/24 its more like 1 day, OFF, 2 days OFF
4. Steady sales within the zombie period and when it ends (ofc) (before noticing this phenomenon I only saw the increased traffic and was thinking m8 company is missing out some sales )

I can to 100% confirm that in zombie On period the sales is OFF!

I can confirm that mostly after the zombie period is OFF – sales is ON


In most of the times if we would miss out sales on a day.. we get magically a nearly amount of sales we would have missed out almost instantly or in a very tight period of time... usually sales periods on our sites are split steady over the day and night...

This is actually what backdraft was observing as well and this observation made me post here, cuz that kind of pattern can not be accidental …



Traffic throttling:

To say something about traffic throttling as well... I’m convinced our site is being throttled because the overall impressions and clicks within a month form G are mainly same, if I cut out the zombies.

I notice 20% plus traffic for the first 2 days an article get published and hit top 1 - 6 rank in G search... after this 2 days traffic goes back to normal (that could be a freshness bonus tho)

But what makes me thing throttling: What ever we publish G just splits the overall impressions on all performing pages... When a new performing article comes out the made impressions are missed on other pages or posts.


As we are in the lucky situation of a natural growing we gain overall +20% traffic per month also by G . The throttling I’m referring to is monthly based..so within the month the traffic form G stays the same …

As in real live growing is a process over time and as I see it, the same applies to G and I’m not complaining on this because I do little mind if the growing is limited by an algo or human or life it self. I’m thinking that this is G´s way of applying a natural growing effect, with what I can/must live with. I think G needed to do that to protect himself form fraud, spam and other harming effects... building up trust to a site and protecting searchers.

[TheMadScientist]

This almost sounds like it's preview related with dataset (or user base) switching to determine the 'right place' for a page... (And maybe sometimes it gets 'stuck' in 'query type (or user group) determination flux' for extended periods?)

Think like an eye test...
Better or Worse ... Switch ... Better or Worse ... Switch ... Better or Worse

Put the page in Dataset 1 for Visitor Group A (on for an hour (or day or whatever))
Put the page in Dataset 2 for Visitor Group A (on for an hour (or day or whatever))
Change the Title, put the page back in Dataset 1 for Visitor Group A (on for an hour (or day or whatever))
Change the Title, put the page back in Dataset 2 for Visitor Group A (on for an hour (or day or whatever))

Put the page in Dataset 1 for Visitor Group B (on for an hour (or day or whatever))
Put the page in Dataset 2 for Visitor Group B (on for an hour (or day or whatever))
Change the Title, put the page back in Dataset 1 for Visitor Group B (on for an hour (or day or whatever))
Change the Title, put the page back in Dataset 2 for Visitor Group B (on for an hour (or day or whatever))

Is there any possibility the pages in question receiving the 'zombie traffic' could be 'on the fence' between being 'seen' by an algo as content or transactional type pages (or some other query types) that might cause them to get 'stuck' for periods where the only (or most reliable) way to determine what type of query they should be shown for (or user group they should be shown to) is to show them to two (or more) different groups of people where the query they make is determined to be 'query type 1' for one group and 'query type 2' (possibly with the same keywords but different visitor intent (or visitor group type) as determined by past search behavior) for the other group and then track visitor behavior for each?

My gut keeps telling me previews have something to do with this (especially after reading all the scroll patterns are the same, because the preview could do that - I don't remember from testing for sure, but it definitely could and it does trigger JavaScript events) and 'switching' a page in and out of two (or more) different query types and/or user groups is something you could do to determine which query type (or user group) a page should rank for and that would explain why Backdraft7 is seeing a spike in zombies around the time of updates.

Google Updates, the algo can't quite determine where a page(s) go, so they show one group and a ton of people just 'roll over the preview' (stats are triggered but nothing happens) then they show another group and they click and buy normally ... And, (possibly) sometimes pages (or sites) get 'stuck' for some reason for an extended period.

BTW SEchecker, I'll get over it, but please, try and get who you're quoting and replying to straight, because it's really not cool to call someone a liar and then 'oops' it out later, especially those of us have been around here contributing for getting close to a decade now and have worked hard to build up a bit of credibility.

[edited by: TheMadScientist at 9:55 am (utc) on Nov 30, 2012]

[SEchecker]

@ TheMadScientist
sorry again for the wrong quote!

Well as we did take action 7 month ago while noticing that something is going on ,we did rebuild the site and created a mix of transactional / informational. That seemed to perform much better but it looks like G has issues with it cuz he cannot clearly target the purpose of the site, so I presume the the observations from the last months COULD be testing related.
If it is testing related, then it would confirm the theory G has pre-made datasets of BUYER vs. NON BUYER.

This would bring up the question why G do things like that?

What would bring up my theory that G is preparing something (or already in process) big, something to split up SEARCH and BUY, what could end up as STRIKT: Knowledge Search Engine vs Product Shop (Search) Engine al a Amazon. Well actually this is going to happen right now, but I think the dimension will be much bigger and will change the way G looks, - is used by people and brands himself - and this will have a big impact to searchers and of course to online business as this could be a signal:

“If you want to make online business, you need to give a share to G”

Like everywhere else, the principle is the same in real-live. The only difference is that you the business owner is AWARE of the situation.

If you want to sell, you gone need to

a. invest
b. cooperat
c. share the profit.


To me it looks G is becoming something like a Shopping Mall visited by BUYERS and people just looking for something or spend some time there

- It is hard to enter with a product
- You are responsible for your product
- You must full fill guidelines and requirements
- You need to pay for advertising
- If you product isn’t good enough, not needed enough or branded enough - people will just watch it on the shelf and you most probably will get kicked out after some time

The lowest position in the Shopping Mall is in front of the store where you need to pay a concession or fee for the space and you are on you own. In Europe this is called a product info stand (so this is where I would place all INFO Websites in G) but still if you want to sell or make some money from the passing visitors you gona need to pay a min. fee. Or the info or product is interesting to the Shopping Mall on a low lvl to entertain, inform or full fill the free space where customers passing by...like oh nice look silver jewels or oh a massage apparatus or some1 gives you a flyer in your hand, make some charity action, something...

But the real business is done inside of the stores and there the Brands dominate...


@backdraft do you see at your end that zombies targeting a set of specific pages/ topics or is it side wide?

[TheMadScientist]

If it is testing related, then it would confirm the theory G has pre-made datasets of BUYER vs. NON BUYER.

I haven't made it all the way through your post, because I really need to get some sleep, but they already do way more than that ... There's definitely query type separation and caching in use, which, since Caffeine can be updated in near real time, but, the short version is: There's definitely more than only Buyer v Non-Buyer for query types.

[edited by: TheMadScientist at 9:59 am (utc) on Nov 30, 2012]

[SEchecker]

Please note that if Info converts to profit ( example advertising) you actually have a product as well (its not any more JUST info)

that might explain why some info sites are going fine and some starting to struggle...

[frankleeceo]

Could the difference between Buyer and Nonbuyer simply based upon their past browsing habits or classifications? I do believe it goes deeper than simple Info / Buying intent. But I do think that is mainly triggered when certain key phrases are used. Such as "How" etc.

Based on SEchecker's notes on user behavior. "Zombies" do behave differently than your average user. And it should definitely be so because its a different subset of visitor profile. It would actually weird if your Zombies behave all the same as the regular average visitors. Maybe I can expand my theory with my previous car example.

Site A: Good for 18 year old who loves cars
Site B: Good for 20~30 year old who loves cars

Let's say your site is Site B, you can get healthy volume of traffic who purchase pretty regularly. But once in a while Google throws different visitor profiles into the site. In an extreme example, we will say 5 year olds who love cars. 5 year olds would look at the cool images, but never buy, and most of them exit fairly quickly. None of them ever really sign up for anything.

Google throws that subset of users at both Site A and Site B periodically, and find that none of them sticks. Thus Google determines that both Site A and Site B is bad for 5 year olds who love cars. These subset group of users (5 year olds) would definitely behave differently. But both sets would get thrown with these visitors periodically. It is google's Crowdsourcing capability at force, they do not have to physically "check" the sites, they simply use the user's behaviors.

I think we would be able to decipher more if there is a way to figure out exactly the user categories of those Zombie traffic. I think from webmasters point of view, we can only figure out what they do, and how they do, our biggest task to decipher the puzzle is to figure out "who they are". I think we have already determined "why" these zombies may exist in Google's crowdsourcing algorithm. Zombies traffic do behave differently as in these traffic never convert, but they are there.

As far as why some sites like Amazon rises prominently on the SERP, my guess is that as long as a subset group of users use the service. Google eventually determines a certain subset, personalization, or localization of users is good for that particular service. No matter how illogical or incorrect it may be.

You may never have to use Amazon yourself, but if let's say 80% of the users in your area, ISP service, or hell even browser version, find a particular website useful for a query - You may be grouped with that particular subset. We can say that Google can "incorrectly" determine - if you are a Chrome user who's age 25 and search for widget, there is a 90% chance you'll like Amazon for that specific query. So even if your 10% of user that absolutely hate Amazon, Google will still serve Amazon to you.

I have read experiences of websites reporting temporary traffic gains after significant marketing pushing - periods after the pushing period. It may be that website has attracted visitor profiles not registered in Google before. Thus based upon that user input, Google throws in additional mixture of users to see their behaviors. And this may be why the traffic increase is always temporary.

[xcoder]

I've installed a real time traffic viewer to one of the websites i monitor. This web site is pet related and enjoy good daily traffic numbers.

Some about this web site:
It has a great web forum which *used* to be extremely busy with at least 20-30 new posts every day and more then 4000 members. I am simply buffeld as to the reason this forum died this year and now receive only about 2 posts per week.

The site is not a great earner so i never gave it too much attention. It kind of took off by itself and enjoyed nice growth (hits and memberships wise) naturally over the years (it is more then 12 years old but had a number of face lifts to bring the look up to date). The site s also naturally linked from many other pet related resource. It is quite popular good quality info site with lots of users contributions.

Well back to the "real time viewer script", this script reports in real time the number of viewers on site. Their IP address, where they came from, what page they are on, their browser and screen resolution as well as screen dimensions. It also adds up and reports the number of pages each viewer browsed.


I've just finished an almost 3 hours session of looking at the reports as they refresh in real time and my conclusion for this session is one. MOBILE DEVICES...lots and lots of mobile devices (many tablets but with smartphones even more. Smartphones hit one page only (in the vast majority of cases) while tablets often load more then one page.

It is starting to look like the "Zombies" ARE smartphones (on that particular website anyway).

Question asked. How to best monetize this traffic now that i know that there are so many smartphones on that particular website at any given moment.

maybe an app affiliate program of some sort?..... or something else? your ideas are most welcome...

[edited by: xcoder at 1:14 am (utc) on Dec 2, 2012]

[TheMadScientist]

Fascinating...

[backdraft7]

xcoder - I've been doing everything I can navigation wise to retain mobile visitors, bigger buttons and even spacing single text adds between main buttons to monetize "fat fingers" (lol). I test daily on my galaxy tab 10.1 but the site also works on smaller devices. Today however, I'm just ridin the storm out with the latest apparent update.

[xcoder]

@backdraft7

They do not convert (smartphones). It is a given on the website i mentioned (and on a number of ecom sites i run). They simply waist bandwidth and i get nothing in return.

What i am thinking of doing is incorporating a detection script that will redirect smartphones users to a page with a list of downloadable apps (affiliate based) and a message saying "Sorry this website can only be viewed on screens of xy size". F$%&*k'm.

Bandwidth = $.

Google can keep them as far as I'm concerned... they are worthless.

[edited by: xcoder at 4:34 am (utc) on Dec 2, 2012]

[diberry]

There are other problems with smartphones that we can't do anything about: connection problems. I often use my smartphone when I'm out and about, to check prices, to find a place to eat/shop, to get the quick answer to a question I just thought of, etc. But I'm in an area with poor reception, so very often I just can't load the sites I want to load.

And even if I can load them and see clearly that they have something I want to buy, interacting with an https section of the site can be a nightmare on a smartphone, so I end up just emailing the link to myself to open on my home computer later. In these cases, I'm probably a zombie visitor... but I often end up buying later from my home PC.

I don't have an Ipad, so I can't speak to that. But I wouldn't write off mobile visitors as useless just yet. The devices need to improve some, and so do connections. But every mobile visit is still an opportunity to, at the very least, impress someone enough to make them want to visit our sites on a regular computer.

[xcoder]

so I end up just emailing the link to myself to open on my home computer later

I still see so many people (family & friends) that don't know how to send a link from their home pc. Good luck expecting them to do that from their smartphones.

Well after almost one year of taking no action on this type of traffic and gaining absolutely nothing by "giving it a chance" i am now ready to find a u$e for this dead beat traffic.

side note:
Smartphones are good when you use them with apps. Maybe that is the real future for the web... *apps*. Maybe websites as we know them are just a dying breed...

[Play_Bach]

Maybe that is the real future for the web... *apps*. Maybe websites as we know them are just a dying breed...

That's the prediction of at least one big name tech icon I know of. He suggested the same well over two years ago.

[xcoder]

That's the prediction of at least one big name tech icon I know of.

Who?

[backdraft7]

Another Thursday, another conversion slowdown. Still no evidence of a season rise. I can draw a straight & level line from October 1 to today and my traffic follows that line perfectly. The only difference between good conversion days and bad is apparently traffic quality. Traffic levels are even over the past month but conversion still totally ON or totally OFF during random periods.

[xcoder]

Last 6 minutes zombie traffic snapshot. (Mostly referred by Google. Hitting one page only and leave)... Comments welcome...


71.48.8.71           [Netscape]----[Screen Size: 1280x800]----[Color Depth: 24 colors]
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_6_8) AppleWebKit/534.57.2 (KHTML, like Gecko) Version/5.1.7 Safari/534.57.2

24.141.6.250           [Netscape]----[Screen Size: 1024x768]----[Color Depth: 32 colors]
Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.95 Safari/537.11

188.3.245.68           [Netscape]----[Screen Size: 1440x900]----[Color Depth: 32 colors]
Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.95 Safari/537.11

174.63.152.124           [Netscape]----[Screen Size: 768x1024]----[Color Depth: 32 colors]
Mozilla/5.0 (iPad; CPU OS 6_0_1 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/6.0 Mobile/10A523 Safari/8536.25

72.79.203.44           [Microsoft Internet Explorer]----[Screen Size: 1024x768]----[Color Depth: 32 colors]
Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.0; Trident/5.0)

174.107.180.67           [Netscape]----[Screen Size: 320x480]----[Color Depth: 32 colors]
Mozilla/5.0 (iPhone; CPU iPhone OS 6_0_1 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/6.0 Mobile/10A523 Safari/8536.25

76.120.158.211           [Netscape]----[Screen Size: 768x1024]----[Color Depth: 32 colors]
Mozilla/5.0 (iPad; CPU OS 6_0_1 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/6.0 Mobile/10A523 Safari/8536.25

131.229.23.68           [Netscape]----[Screen Size: 1440x900]----[Color Depth: 24 colors]
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_2) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.91 Safari/537.11

166.137.156.44           [Netscape]----[Screen Size: 320x396]----[Color Depth: 32 colors]
Mozilla/5.0 (iPhone; U; CPU iPhone OS 3_1_3 like Mac OS X; en-us) AppleWebKit/528.18 (KHTML, like Gecko) Version/4.0 Mobile/7E18 Safari/528.16


71.48.8.71           [Netscape]----[Screen Size: 1280x800]----[Color Depth: 24 colors]
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_6_8) AppleWebKit/534.57.2 (KHTML, like Gecko) Version/5.1.7 Safari/534.57.2

24.141.6.250           [Netscape]----[Screen Size: 1024x768]----[Color Depth: 32 colors]
Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.95 Safari/537.11

188.3.245.68           [Netscape]----[Screen Size: 1440x900]----[Color Depth: 32 colors]
Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.95 Safari/537.11


174.63.152.124           [Netscape]----[Screen Size: 768x1024]----[Color Depth: 32 colors]
Mozilla/5.0 (iPad; CPU OS 6_0_1 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/6.0 Mobile/10A523 Safari/8536.25


72.79.203.44           [Microsoft Internet Explorer]----[Screen Size: 1024x768]----[Color Depth: 32 colors]
Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.0; Trident/5.0)


174.107.180.67           [Netscape]----[Screen Size: 320x480]----[Color Depth: 32 colors]
Mozilla/5.0 (iPhone; CPU iPhone OS 6_0_1 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/6.0 Mobile/10A523 Safari/8536.25


76.120.158.211           [Netscape]----[Screen Size: 768x1024]----[Color Depth: 32 colors]
Mozilla/5.0 (iPad; CPU OS 6_0_1 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/6.0 Mobile/10A523 Safari/8536.25


131.229.23.68           [Netscape]----[Screen Size: 1440x900]----[Color Depth: 24 colors]
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_2) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.91 Safari/537.11


166.137.156.44           [Netscape]----[Screen Size: 320x396]----[Color Depth: 32 colors]
Mozilla/5.0 (iPhone; U; CPU iPhone OS 3_1_3 like Mac OS X; en-us) AppleWebKit/528.18 (KHTML, like Gecko) Version/4.0 Mobile/7E18 Safari/528.16

[TheMadScientist]

Run the IP Addresses, what you find might be interesting ;)

There's some I seriously doubt were actually sent by Google.
(It's simple to spoof a referrer.)

[xcoder]

^ i did run some ips, couldn't see anything conclusive. Do you see anything?

p.s.
check out all the tiny screens. They come in large groups sometimes. I will post more reports later on when i get to catch them in action.

[edited by: xcoder at 10:46 pm (utc) on Dec 6, 2012]

[TheMadScientist]

Yeah, what I got was 2 repeats that were foreign... One from Canada and one from Turkey (2 visits each, so -4 visits ... 24 bit color depth monitors for both, interesting at the least) ... 2 that had no info (always makes me suspicious and lean toward spoofed) (-2 visits) ... A bunch of 'tiny screens' (-9 visits)

If you 'filter those out' you're only left with 3 that appeared to be real, non-mobile, non-foreign visitors.

[xcoder]

@TheMadScientist what i suspected. This explains why most of the traffic is worthless.

Here are some more (last 6 minutes live):

173.105.200.90 [Netscape]----[Screen Size: 1024x768]----[Color Depth: 24 colors]
Mozilla/5.0 (Windows NT 5.1; rv:17.0) Gecko/20100101 Firefox/17.0
Referrer: [google.com...]

85.210.190.205 [Microsoft Internet Explorer]----[Screen Size: 1024x768]----[Color Depth: 32 colors]
Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 5.1; Trident/4.0; GTB7.4; .NET CLR 2.0.50727; .NET CLR 3.0.4506.2152; .NET CLR 3.5.30729; InfoPath.1)
Referrer: [google.co.uk...]

75.81.119.63 [Netscape]----[Screen Size: 1280x720]----[Color Depth: 24 colors]
Mozilla/5.0 (Windows NT 6.1; WOW64; rv:17.0) Gecko/20100101 Firefox/17.0
Referrer: [google.com...]

68.8.62.221 [Netscape]----[Screen Size: 1280x800]----[Color Depth: 24 colors]
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_5_8) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/21.0.1180.90 Safari/537.1
Referrer: not given

71.89.94.102 [Netscape]----[Screen Size: 768x1024]----[Color Depth: 32 colors]
Mozilla/5.0 (iPad; CPU OS 6_0_1 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/6.0 Mobile/10A523 Safari/8536.25
Referrer: not given

71.201.74.129 [Netscape]----[Screen Size: 320x480]----[Color Depth: 32 colors]
Mozilla/5.0 (iPhone; CPU iPhone OS 6_0 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/6.0 Mobile/10A403 Safari/8536.25
Referrer: not given

66.90.242.94 [Netscape]----[Screen Size: 320x480]----[Color Depth: 32 colors]
Mozilla/5.0 (iPhone; CPU iPhone OS 6_0_1 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/6.0 Mobile/10A523 Safari/8536.25
Referrer: not given

99.192.107.99 [Netscape]----[Screen Size: 320x480]----[Color Depth: 32 colors]
Mozilla/5.0 (iPhone; CPU iPhone OS 6_0_1 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/6.0 Mobile/10A523 Safari/8536.25
Referrer: [google.ca...]

72.11.65.170 [Netscape]----[Screen Size: 1280x800]----[Color Depth: 24 colors]
Mozilla/5.0 (Windows NT 6.1; WOW64; rv:8.0.1) Gecko/20100101 Firefox/8.0.1
Referrer: not given

70.89.199.237 [Microsoft Internet Explorer]----[Screen Size: 1600x900]----[Color Depth: 24 colors]
Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Trident/5.0)
Referrer: not given

184.70.108.50 [Netscape]----[Screen Size: 1920x1080]----[Color Depth: 24 colors]
Mozilla/5.0 (Windows NT 6.1; WOW64; rv:17.0) Gecko/20100101 Firefox/17.0
Referrer: not given

143.197.222.231 [Microsoft Internet Explorer]----[Screen Size: 1280x960]----[Color Depth: 32 colors]
Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.1; Trident/4.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; .NET CLR 1.1.4322; .NET4.0C; .NET4.0E; Tablet PC 2.0)
Referrer: [google.com...]

[taberstruths]

So a quick question here. If G is indeed splitting up visitors based on search intent, what affect do you think having Amazon text links in your informational content cause? Not a lot but 1 link or maybe 2. Would this cause G to have a brain meltdown and not be able to discern what type of site you are?

[bluntforce]

@xcoder

That first list is duplicated. After 166.137.156.44 it repeats the first portion. Thanks for putting it up though, it's at least something to work with.

What's with the "Netscape"? I see Netscape rarely throughout a day.

[xcoder]

Check out that one. Googlebot here executing and responding to JavaScript (number of) queries including referrer and current page url and page title...(omitted for obvious reasons).


66.249.73.208 [Netscape]----[Screen Size: 320x480]----[Color Depth: 24 colors]
Mozilla/5.0 (compatible; Googlebot/2.1; [google.com...]





PM if you want to check your own site.

[edited by: xcoder at 3:58 am (utc) on Dec 7, 2012]

[xcoder]

@bluntforce

Netscape = user browser response to JS query "navigator.appName;"

Apparently the response from all Gecko based browsers is "Netscape"

[xcoder]

Last six minutes... check out this cluster...


166.205.68.44           [Netscape]----[Screen Size: 320x480]----[Color Depth: 32 colors]
Mozilla/5.0 (iPhone; CPU iPhone OS 6_0 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/6.0 Mobile/10A403 Safari/8536.25

Referrer: Unknown


112.204.9.159           [Netscape]----[Screen Size: 1360x768]----[Color Depth: 32 colors]
Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.95 Safari/537.11

Referrer: [google.com.ph...]


173.21.249.58           [Netscape]----[Screen Size: 720x1280]----[Color Depth: 32 colors]
Mozilla/5.0 (Linux; U; Android 4.0.4; en-us; SCH-R530U Build/IMM76D) AppleWebKit/534.30 (KHTML, like Gecko) Version/4.0 Mobile Safari/534.30

Referrer: [google.com...]


75.73.126.244           [Netscape]----[Screen Size: 320x480]----[Color Depth: 32 colors]
Mozilla/5.0 (iPhone; CPU iPhone OS 6_0_1 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/6.0 Mobile/10A523 Safari/8536.25

Referrer: Unknown


166.205.68.48           [Netscape]----[Screen Size: 320x480]----[Color Depth: 32 colors]
Mozilla/5.0 (iPhone; CPU iPhone OS 6_0 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/6.0 Mobile/10A403 Safari/8536.25

Referrer: Unknown

[xcoder]

Apparently iPhones hardly ever give the referrer info, is it only me?

[SevenCubed]

I see iPhones coming from Yahoo! search coughing up referrers and search term in my logs.

[xcoder]

I see iPhones coming from Yahoo! search coughing up referrers and search term in my logs.

Actually i do get the referrer now for a number of iphones that i'm watching. There are times that i don't though. They kind of come in clusters. Sometimes all of them will have a referrer and sometimes most of them dont. Could be coincidence... back to watching.

[chalkywhite]

5 out of the lats 9 days, ive had 1066 visitors per day exactly, the rest 5-10 visitngs either way. What are the chances?