We are running a parent Google ad manager account. There's this one other agency who connects us to publishers. They also have their own Google ad manager account. As they would like to control numbers delivered, with GPT tags we set up on our GAM, they do not pass directly to pub, they place our tags on their GAM, then give their GPT tag to pub. Pub then put agency's tag on their GAM, and finally place their GPT tag on their sites.
Ad requests recorded by us and agency has a huge discrepancy. Agency record tens of thousands of requests while our report shows only hundreds. Not to mention fill rate for the request amount that reaches us is also incredibly low.
Theoretically speaking, I understand that calling tags multiple times via multiple GAMs like that causes the discrepancy as at each calling, a part of requests get disqualified. But I can't explain the low fill rate.
Has anyone experienced the same situation? Can you give me any advice on how to improve?
Thank you very much
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I am running google ads and having invalid click issues my ad serve only in Dubai, problem i face my competitor click bomb my ad from UK, FRACE and other countries mostly from Europe and Britain, I excluded all the world expect Dubai but my competitor still able to see my ad and clicking them with some kind of bot till Dawn to Dusk.
I talked with google and they said our system filter invalid clicks but still 30 to 50 percent clicks google consider legit.
I come up with a solution by installing a plugin in WordPress and filtering traffic by filtering URL with "/?gclid=" parameter. But now I have to do it manually.
My question is there any automate rule in WordPress so I can block an IP address automatically if he click on my ad more then a couple of times.
Wouldn't you consider this more a google ads problem than a webmaster problem? Your take to approach google is the best one imo.
Google ads should not count a person twice if the click on the same add twice in a row within a certain time period (from the same ip address) and this should be your argument with google. This logic is simple enough so that google ads should have it in order to ensure fair business even from google's perspective.
If you succeed with this, your competitor will think he is successful while doing you no harm.
Trying to block those ip addresses can again be bypassed by your competitor with the next version of his clickbomb trick.
I currently have more than 50 microsites on my main websites. That is I have one main top level domain and I have more than 50 microsites (and growing) in subfolders on that domain.
Previously I used separate GA web properties for the separate microsites (different GA tracking ID's), which worked fine and I was able to track each sites' activity well. However, I talked to a GA staffer over email and he told me I should switch to using a singular GA web property and use multiple profiles to segment the data by subfolder/microsite. That seemed logical for a lot of reasons, tracking users over the entirety of the website in one GA session being the main one.
Anyway, I have one subfolder which houses an array of microsites, numbering almost 40 right now. I don't necessarily need to have a profile for each one of these sites but there are a couple of important ones that I need to report on individually and on a regular basis I'd like to see how traffic to the other individual sites are doing.
So my question: Is there a way in a single profile to segment data to 40+ (and growing) microsites and see month to month stats on each site? Is there a way I can load a profile dashboard with the stats (Visits/pageviews) from each microsite? Is segmenting the data even what I should be looking at? How would you, a more advanced GA user, tackle this problem?
Many thanks for your input!
jimdo (http://www.jimdo.com) offers a Google Analytics based statistics tool for their DIY website creator. They put hundreds of the (usually low traffic) sites in one profile, set a custom var with a unique ID per site and query the results via the Google API, segmented by site id (at least that is what one of their founders told during a web analytics conference a few months ago). Given that the solution works for a couple of million of client sites (their claim is to host 7 million websites for their clients) segmentation based on a unique site id seems a pretty solid idea.
Updated: As custom vars are deprecated with Universal Analytics you'd now use a custom dimension instead if a custom var. Apart from that the approach should still work.
I have been asked to provide recommendations on "Verified Analytics" for the next iteration of my company's site. Verified to mean that when we sell ad space, it's based on a number of page-views, and the people who buy that space want a way to verify that the numbers we give them are the actual numbers we're delivering.
I have turned to The Google and the only services I can find for this sort of thing revolve around Google Analytics and the sale of a domain name. I export my analytics numbers to a PDF, have Google email the PDF to my auctioneer, and they look for signs of tampering. If no signs of tampering are found they put a little "Verified" badge on the domain auction. (Here)
Other than this, and something similar on another domain sales site, I haven't found anything like what I've been asked to find.
Currently we are using Google Analytics, however I've been also asked to recommend a replacement for that based on the ability to be verified. I'd rather just stick with Google Analytics since we also use Google for advertising.
Google analytics is a third party service, so you can't modify the stats data yourself anyway. If google is sending them the report directly there's not even scope for you to be editing the numbers so their concern is more paranoia than reasonable.
a) You can add another user in google analytics and give them report-only access. This way they can look at the stats themselves.
b) Add another hits tracking service such as http://www.hitslink.com/ and give the client access to these reports too.
Quantcast / Comscore / Compete all make estimates of site traffic based on limited amounts of data. As an ad buyer I would never take these stats as proof of anything really.
Online Audience Measurement is a term to search for - you're looking at providers like Quantcast, Comscore or Compete. These work alongside, rather than replace your current web analytics package.
Qauntcast actually measures traffic directly. You insert a tag, same as Google Analytics. Most ad agencies and advertisers accept Quantcast numbers for traffic validation.
After being stumped by an earlier quesiton: SO google-analytics-domain-data-without-filtering
I've been experimenting with a very basic analytics system of my own.
MySQL table:
hit_id, subsite_id, timestamp, ip, url
The subsite_id let's me drill down to a folder (as explained in the previous question).
I can now get the following metrics:
Page Views - Grouped by subsite_id and date
Unique Page Views - Grouped by subsite_id, date, url, IP (not nesecarily how Google does it!)
The usual "most visited page", "likely time to visit" etc etc.
I've now compared my data to that in Google Analytics and found that Google has lower values each metric. Ie, my own setup is counting more hits than Google.
So I've started discounting IP's from various web crawlers, Google, Yahoo & Dotbot so far.
Short Questions:
Is it worth me collating a list of
all major crawlers to discount, is
any list likely to change regularly?
Are there any other obvious filters
that Google will be applying to GA
data?
What other data would you
collect that might be of use further
down the line?
What variables does
Google use to work out entrance
search keywords to a site?
The data is only going to used internally for our own "subsite ranking system", but I would like to show my users some basic data (page views, most popular pages etc) for their reference.
Lots of people block Google Analytics for privacy reasons.
Under-reporting by the client-side rig versus server-side eems to be the usual outcome of these comparisons.
Here's how i've tried to reconcile the disparity when i've come across these studies:
Data Sources recorded in server-side collection but not client-side:
hits from
mobile devices that don't support javascript (this is probably a
significant source of disparity
between the two collection
techniques--e.g., Jan 07 comScore
study showed that 19% of UK
Internet Users access the Internet
from a mobile device)
hits from spiders, bots (which you
mentioned already)
Data Sources/Events that server-side collection tends to record with greater fidelity (much less false negatives) compared with javascript page tags:
hits from users behind firewalls,
particularly corporate
firewalls--firewalls block page tag,
plus some are configured to
reject/delete cookies.
hits from users who have disabled
javascript in their browsers--five
percent, according to the W3C
Data
hits from users who exit the page
before it loads. Again, this is a
larger source of disparity than you
might think. The most
frequently-cited study to
support this was conducted by Stone
Temple Consulting, which showed that
the difference in unique visitor
traffic between two identical sites
configured with the same web
analytics system, but which differed
only in that the js tracking code was
placed at the bottom of the pages
in one site, and at the top of
the pages in the other--was 4.3%
FWIW, here's the scheme i use to remove/identify spiders, bots, etc.:
monitor requests for our
robots.txt file: then of course filter all other requests from same
IP address + user agent (not all
spiders will request robots.txt of
course, but with miniscule error,
any request for this resource is
probably a bot.
compare user agent and ip addresses
against published lists: iab.net and
user-agents.org publish the two
lists that seem to be the most
widely used for this purpose
pattern analysis: nothing sophisticated here;
we look at (i) page views as a
function of time (i.e., clicking a
lot of links with 200 msec on each
page is probative); (ii) the path by
which the 'user' traverses out Site,
is it systematic and complete or
nearly so (like following a
back-tracking algorithm); and (iii)
precisely-timed visits (e.g., 3 am
each day).
Biggest reasons are users have to have JavaScript enabled and load the entire page as the code is often in the footer. Awstars, other serverside solutions like yours will get everything. Plus, analytics does a real good job identifying bots and scrapers.
It seems that each time I see an ad that is served by an ad manager application there is always a bunch of parameters added to the URL of the product.
Say for instance one random stackoverflow ad :
http://ads.stackoverflow.com/a.aspx?Task=Click&ZoneID=4&CampaignID=474&AdvertiserID=5&BannerID=408&SiteID=1&RandomNumber=464183249&Keywords=
or this one:
http://ads.stackoverflow.com/a.aspx?Task=Click&ZoneID=4&CampaignID=474&AdvertiserID=5&BannerID=408&SiteID=1&RandomNumber=2039490120&Keywords=http-1.1%2ccaching%2ccache%2chttp-header-fields%2cheader%2cx-user-registered
If I go with the logic of the things, when you register a click to a banner, you would normally need a few info : "how many times it has been clicked", "by who" (ip/registered account/...), "when".
Now if we look at the parameters there are a lot more informations to this. OpenX adds a lot more on top of that :
http://ox.jeuxonline.info/www/delivery/ck.php?oaparams=2&bannerid=244&zoneid=7&cb=1264705683&maxdest=http%3A%2F%2Fwww.smartadserver.com%2Fcall%2Fcliccommand%2F3141468%2F1264705683
The only reason I can think of this is to save call to the db, other than that I really can't see.
Any hint or ideas ?
Tracking.
The parameters are used to identify you, where you're clicking from, what you're clicking on, which ad campaign your click should go to, etc.
Usually ad requests contain a size code, sometimes a location code (where on the page the ad appears), and audience segmentation information, which is information the content provider knows (or has guessed) about you and is used by the network to figure out what kinds of ads should be served to you. Most audience segmentation is proprietary, either to the ad network or to the content provider. Some ad networks have special features to support segmentation based on content you've recently searched for (keywords, search_terms, etc.).
Most of the time the name/value pairs will be completely unintelligible to people not familiar with the segmentation rules. You could have something like il=5, which could mean income level is in category 5, which might mean $120,000/yr on some arbitrary network.
The actual image served may repeat some of the information in the original ad request, either for tracking actual ads served or, in some cases, because the image server needs some of the same information to serve the right image.
Well they also need to give analytics to their advertisers. You'll see that the URL identifies who the advertiser is, what campaign it's for, etc. All that stuff is used to know who to bill, and how effective the ad is (ie is the picture of the girl more effective then the unicorn).