Wednesday, 29 September 2010

Last week, we saw how a website owner removed traffic from his latest promotion to study the effects of that promotion on his data. The blue line represents all visits over a 2-week period. The spike in the middle is due to a 50%-off referral-based promotion.

The yellow line is where it gets interesting. This line represents all traffic except traffic from the promotional site. Since the yellow line excludes the promotional referrals, why does it show a spike in traffic?










To find out, the store owner de-selected the All Visits segment so that only the Exclude Promo Site segment was active.






















Then, he looked at each of the reports in the Traffic Sources section -- the Direct Traffic report , Referring Sites report, and Search Engines report-- to find out where the non-promo traffic spike was coming from. Here’s the graph he saw when he looked at the Search Engines report.












It turns out the extra traffic was coming from search. Happily, the referral site promotion had been even more successful than expected. Because not only was there a big spike in traffic due to the referral, there was also a spike from search. As a result of the increased exposure, more people were searching for his store.

With that mystery solved, we’re ready for the next step. How can we find out how many extra searches resulted from the promotion? And, exactly which keywords were people searching on? We’ll take a look in Part 3, next week.

Tuesday, 28 September 2010

We always love to share news about integrations and applications built on the Google Analytics platform. Here’s one from Bazaarvoice.

Bazaarvoice helps e-commerce sites become social by providing a platform for visitors to leave comments and reviews about products. It's user-generated content right on an e-commerce website. With this new integration, Google Analytics users can now see visitor interaction with their Bazaarvoice social content. Here's what Andy Wolfe, Product Manager at Bazaarvoice said about the integration:
“With this integration, Bazaarvoice clients can now see, in Google Analytics, the metrics on things like the number of visitors paginating through reviews, or sharing user-generated content with social networks, or clicking on related products found in reviews. Advanced Segments can then be used to compare the behavior of visits that interact with Bazaarvoice generated content vs. those that don't.”
To illustrate how useful this can be, here’s a screen shot showing the Bazaarvoice integration:


Users are raving about this integration. According to Paul Dempsey, E-Marketing Manager at Alternative Apparel, one of many clients using the Google Analytics - Bazaarvoice integration, “Now, it's really easy to see the influence of user-generated content on our conversion goals. Did they increase now that we've enabled reviews? We can find out.”

And according to Kris Irizawa, Web Analytics Analyst, Logitech, “We love going into Google Analytics and, with a few clicks, segmenting out visits that interact with Bazaarvoice. I can look at all my reports to uncover additional value from user-generated content, such as location based stuff, new vs. returning, keywords, search terms, and more.”

For more information on this integration, check out the Bazaarvoice site.


Friday, 24 September 2010

Chrome version 6.0.472.55 was an incremental update to a new version of Chrome released on September 7 and announced here. There was a bug in the JavaScript engine that reported the wrong type of some JavaScript objects in a very specific case. This caused Chrome to incorrectly execute Google Analytics' JavaScript, providing an artificially high visitor count for some websites, for their visitors using that particular version of the Chrome browser. Note, not all Google Analytics accounts were affected. The affected period will vary for accounts but would not have appeared before September 7.

A fix was released for all versions of Google Chrome on Wednesday, September 22. Chrome users were automatically updated to version 6.0.472.63 over the last few days.

You can determine whether a profile was affected by comparing visit data from September 7 to approximately September 22 with a previous date range. If you think your account was affected and want to segment out visits from that date range from the affected Chrome release, you can create an advanced segment similar to this one.

We are working closely with the Chrome team to ensure that an issue like this does not happen again. While we believe this issue is fixed, we’ll be closely monitoring this issue over the weekend and beyond.

Google Analytics processes huge volumes of data for websites around the world everyday, thanks to Google’s globally renowned infrastructure. While we never stop focusing on system reliability and scalability (here's an example), we also want to make sure our users have an easy way to get the latest updates from us should there be a problem.

Today, we’re pleased to announce that we have launched the Google Analytics Status Dashboard. Now anyone can visit this Status Dashboard to check on the current status of components of the Google Analytics system.

The dashboard reports on the three main components of Google Analytics:
  • Data Collection (whether data from websites are being collected by the Google Analytics servers correctly)
  • Web Report (whether users can view the reports correctly when they sign in to their Google Analytics accounts)
  • GData API (whether the Google Analytics APIs are working properly)
The Google Analytics Status Dashboard represents an additional layer of transparency that we believe will benefit all Google Analytics users, from Fortune 500 companies to personal websites. The Status Dashboard is the best place to check for service availability of Google Analytics anywhere in the world. You can also get the updates pushed to you by subscribing to the RSS Feed. And of course, you can always get updates from us here at this blog or by following us on Twitter (@googleanalytics) and get help from the Google Analytics Help Center or the User to User Forum.

Thursday, 23 September 2010

Lo and behold, it’s another episode of Web Analytics TV. In this exciting series with Avinash Kaushik and Nick Mihailovski, you ask and vote on your favorite web analytics questions via the Google Analytics Google Moderator site and we answer them.

In this episode, we are delighted to have Rod Jacka as our special guest on Web Analytics TV. Rod is the Managing Director of Panalysis, a specialist web business analytics company and GA Certified Partner, Rod has experience in every web analytics tools, and if you need any consulting help in Australia then Rod's your man.

Here is a list to last weeks questions.

In this action packed episode we discuss:
  • (1:45) Why does you own site show in the Referring Sites report?
  • (3:15) Is there any way to export more than 5 columns in a pivot report?
  • (4:15) Getting app integrations migrated to async tracking
  • (5:55) Is there a way to grant read-only access to Website Optimizer?
  • (6:50) How to cross IDs set in Custom Variables with other GA data
  • (8:50) In which report can you find the PPC search terms (not bid terms)?
  • (10:20) Tracking links from emails that point to sites not being tracked by GA
  • (12:25) Thoughts about optimizing the async code
  • (15:15) If a user keeps clicking every 29 minutes, can a session last for 9 days?
  • (16:50) What could cause advanced segments on reports to have different totals?
  • (18:28) Why should people use other web analytics products when GA is free?
  • (20:50) Does GA track transactions in the same session or across session?
  • (21:08) How to get the goal funnel data through the API?
  • (22:28) What does “other” mean in the traffic sources overview reports?
  • (24:18) Is it possible to get segment-able motion charts?
  • (25:42) Why do product revenue and transaction revenue show different values?
  • (27:36) Where you can find unique visitor data in Google Analytics
  • (29:35) Why do advanced segments that match pages return other pages?
  • (31:22) Is it possible to export data from one account into another account?
  • (33:08) How to link multiple AdWords accounts to one Google Analytics account
  • (34:15) How to distinguish website referrals from desktop applications




And here are the links to the topics we discuss:

As always, if you need help setting up Google Analytics or leveraging the advanced configuration options, we recommend hiring a Google Analytics Certified Partner.

If you found this post or video helpful, we'd love to hear your comments. Please share them via the comment form below. And, if you have a question you would like us to answer, please submit a question and vote for your favorite question in our public Google Moderator site. Avinash and I will answer your latest questions in a couple of weeks with yet another entertaining video.

Thanks!

Post content

Wednesday, 22 September 2010

I have a friend who owns a store in my neighborhood. He decided to run a 50%-off special on a site that specializes in one-day promotions to its members. His goal was to get wider exposure for his store and gain some new customers. If you look at the graph, you can see that the day that the promotion ran, traffic to his site spiked. Traffic then dropped off to normal the next day, but this was expected given the nature of this particular campaign.












The store owner was happy to see the spike in traffic, but he wanted to learn more. So he did something clever and created an advanced segment. But instead of creating an advanced segment for traffic from just the promotional site, he did the exact opposite. He created a segment that excluded all the promotional traffic.

Why? It’s a great example of what I call the power of exclusion. More about that in a minute, but first let’s look at how you would create a segment that excludes traffic from a specific site.

First, click the Advanced Segments drop down and click “Create a new advanced segment”.





















From the menu on the left, drag Source into the working area. Select the condition “Does not contain”. Enter the name of the site from which you want to exclude traffic, for example “example.com”. Then name and save the segment.











To apply the segment, click the Advanced Segments drop down again and select your newly created segment. (You’ll see it under Custom Segments.) In this case, I named this segment “exclude promo site”.














Take a look at the graph below and you’ll see why this was a smart idea. The blue line is all traffic. The orange line is all traffic except traffic from the promotional site. Notice something interesting? That’s right. The orange line also shows a spike, even though it doesn’t include any referrals from the promo site.










This is the power of exclusion: If you want to find out how effective something is -- whether it’s a traffic source, a promo, or a campaign -- try excluding its influence from your data. You might be surprised at what you find.

So, why is there a traffic spike in the “exclude promo site” segment? Tune in next week and find out. In the meantime, watch this short video tutorial to re-acquaint yourself with advanced segments.

Monday, 20 September 2010

Avinash Kaushik is the Analytics Evangelist here at Google. He is, without a doubt, our toughest, most vocal and valued critic and advisor - we couldn't be luckier to have him. He reminds me of a younger, more talkative Gandalf, the wizard from the The Lord of The Rings who just knows stuff. Lots of stuff. Basically everything. When it comes to analytics, Avinash is our Gandalf, except Avinash is a much more riveting public speaker.

So, when he lauds something, it should be noted. That's why his recent post, End of Dumb Tables in Web Analytics Tools! Hello: Weighted Sort, about the newly launched Google Analytics feature, weighted sort - which sorts table data according to its importance, not simply according to numerical value - is worth reading for this audience.

Here's a quote from Avinash's post:
Arthur C. Clarke said:

"Any sufficiently advanced technology is indistinguishable from magic."

That quote comes to mind when I think of a new feature in Google Analytics that carries the unassuming name of Weighted Sort. It is an advanced implementation of technology (mathematical algorithms in this case) and when used it very much feels like magic!

In this blog post I want to share with you why I am so incredibly excited about this feature, how it works and how going forward you will reject every tool that does not come built in with this feature (ok so maybe that's a stretch, but I promise you this is so cool that at least for a few minutes you'll think other tools are lame by comparison!).
We have a very long tail of data in web analytics. Tens of thousands of rows of keywords in the Search Report (even for this small blog!). Hundreds and hundreds of referring urls and campaigns and page names and so on and so forth.
Yet because we are humans we tend to look at just the top ten or twenty rows to try and find insights. The problem? The top ten of anything rarely changes (except in rare circumstances like a sale or on a pure content – think news – site).

Hence I have persistently evangelized the need for true Analysis Ninjas to move beyond the top ten rows of data to find insights.
He goes on to give great examples of use, and even gets into the math behind the feature. Love that! It's a must-read post for anyone interested in getting the most out of Google Analytics, or in web analytics as a whole.

We hope you're making use of this new feature. Feel free to let us know in the comments below.

Friday, 17 September 2010

Google Analytics is very pleased to announce the latest release of the Google Analytics SDK for iOS and Android, which now runs on devices using the latest version of Apple's mobile operating system, iOS 4. The new version of the SDK is 0.8 (ie. still beta) and it also includes fixes for Android.

If you are a current website administrator or Google Analytics developer and are beginning to branch out into Android or iOS development, the Google Analytics mobile SDKs can provide a familiar interface as you transition from tracking website visitors to mobile users.

These SDKs for iOS and Android enable you to track user activity directly in your native mobile apps -- for example, you can see what "pages" or panels of your application are the most popular or even how many clicks a particular button or control generates. As with Google Analytics for the web, this usage data can help provide insight on additions or enhancements necessary to boost user engagement or optimize your mobile ad spending. Even better, all "page view" and event tracking data is viewable in the same interface that you're already accustomed to for tracking website statistics, and integrating it into your app is as simple as adding a few lines to your iOS or Android source code. For example:

Sample code:

#import "GANTracker.h"

// ...

- (void)applicationDidFinishLaunching:(UIApplication *)application {
[[GANTracker sharedTracker] startTrackerWithAccountID:@"UA-0000000-1"
dispatchPeriod:kGANDispatchPeriodSec
delegate:nil];

// Track a page view
if (![[GANTracker sharedTracker] trackPageview:@"/app_entry_point"
withError:&error]) {
// ...
}
}

// ...

For more sample code for both iOS and Android, please see the developer documentation. Also keep in mind that you can use Google Analytics to track usage activity for mobile websites using the server-side code snippets for PHP, JSP, ASP.NET, and Perl, also available in the documentation.


Tuesday, 14 September 2010

Back in Episode 10 of Web Analytics TV, (32:00), Lisa C from Melbourne asked how to pull a trending report from Google Analytics for the top organic search landing pages. This was such a great question, that we wrote 2 articles and released sample code describing how you can automate retrieving this data from Google Analytics Data Export API. But first let’s look at the results.

Here is a graph plotting traffic to the top 100 landing pages for organic search for all of June for www.googlestore.com.

Let’s Analyze. This is the typical trend graph you can find across the Google Analytics web interface. By itself, all you can tell is that something happened during the spike. What you can’t figure out is which page actually increased in traffic; to do so would require lots more digging.

Now let’s try again. Here is a stacked area graph of each of the top 100 landing pages for organic search.

This approach dramatically reduces the amount of quota required. In the best case, only 2 queries are required.

Monday, 13 September 2010

Do you need self-hosted analytics software? In some cases, particularly with intranets and other behind-the-firewall web services, running your own internal analytics application is the only way to access to usage data. In other cases, company or agency policy may prohibit the use of hosted analytics.

But whatever the reason, if you need self-hosted web analytics software, you need Urchin.
And like Google Analytics, it keeps getting better. Case in point: now available, a new version: Urchin 7. Urchin 7 represents the pinnacle of web analytics software, with a feature set only Google Analytics can compete with.

Check out these new features:
  • 64-bit CPU support
  • Parallel log processing
  • 1000 domains/unlimited logs
  • 100% new UI
  • Advanced Segmentation
  • Event Tracking
  • Permalinks
  • API v. 2
  • Price: US$9995
Please see the Urchin 7 Features page for more information, or download Urchin 7 today. Please note that Urchin 7 is sold exclusively through the global network of Urchin Certified Partners.

Friday, 10 September 2010

Since this week’s launch of Instant Search, we’ve been asked how to track Instant Search in Google Analytics, and in particular, whether it’s possible to see partial Instant Search queries in your reports.

You actually don’t need to do anything to track Instant Search queries in Google Analytics. All search referrals are tracked just as they’ve always been.

We’ve seen several clever profile filters in the blogosphere that are designed to parse out the values of the “oq” parameter so that partial queries can be easily seen in Google Analytics. However, the “oq” parameter is not related to Instant Search and is often not passed in the request.

Some answers to your other questions:

Should I change my search advertising strategy to serve ads on to partial keywords (e.g. if I sell flowers, should I advertise on “flow”)?
This is not a productive strategy. Please note that ads are triggered based on the “predicted query” and not the stem that the users types in. So, in this example, the partial query “flow” triggers results for the predicted query of “flowers”. The only way someone can see your ad for “flow” is if they specifically searched for that word and hit enter or clicked search. And since you sell flowers, it’s not likely that your ad for flowers will be served alongside such a generic and irrelevant word.

Does this change impact the ranking of search results?
No, this change does not impact the ranking of search results.

What term will I see in Google Analytics if a visitor comes on a partial query?
The keyword analytics sends is not the partial one but the predicted query. If a user was typing "web metrics" but got the search result she wanted at “web met” with the predicted term being "web metrics", then you will see “web metrics” in your Google Analytics reports.

How will this affect my AdWords impression count?
When someone searches using Google Instant, ad impressions are counted in these situations:
  • The user begins to type a query on Google and clicks anywhere on the page (a search result, an ad, a spell correction, a related search).
  • The user chooses a particular query by clicking the Search button, pressing Enter, or selecting one of the predicted queries.
  • The user stops typing, and the results are displayed for a minimum of three seconds.”
Many of your questions related to ads can be answered here.

We hope this helps. Feel free to comment below.

Wednesday, 8 September 2010


Last week’s back-to-basics post illustrated the dramatic growth in mobile with an example from googlestore.com. This week, let’s look at how to create a mobile trend graph from your own data.

You’ll start by creating an advanced segment. Go to your reports in Google Analytics. In the left navigation, you’ll see a grey box called My Customizations. In this box, click Advanced Segments. On the next screen, click “Create new custom segment”. This will take you to the segment builder screen.

Under Dimensions (in green), expand Systems and drag “Operating System” into the work area and create this definition:




Operating System Matches Exactly Android

Now, add an OR condition and add another definition:

Operating System Matches Exactly iPhone

Keep adding as many OR conditions and definitions as you like.















Name the segment (for example, “mobile phones”) and save it. You can now use the Advanced Segments dropdown (at top right of most reports) to apply the segment. For last week’s graph, I selected only “mobile phones” and de-selected “All Visits”. This allowed me to only see traffic from the mobile phone types in my segment.














Now, to see your trend graph, go to any report that graphs visits (for example, the Dashboard will work fine for this). Set your date range to include the last 18 months or 2 years. The trend will be most clear if you select the Graph by Month icon (at top right of the graph):












How much growth are you seeing over the past year or more? Post a comment and let us know what you’ve found!

Also, if you’re rusty with advanced segments, be sure to watch this short video tutorial.

Today, we announced the launch of Google Instant, a new Google.com interface that shows relevant results while the user types. This exciting new search interface applies to both search results and related ads. We expect Google Instant will help users find what they’re looking for faster. With this change, you might notice some fluctuations in AdWords impression volume and in the distribution of organic keywords. For example, you may find that certain keywords receive significantly more or fewer impressions moving forward.

To read more about how this change affects AdWords advertisers, please visit the Inside AdWords Blog. Users of Webmaster Tools should also see their post about Google Instant.

Update at 5:10pm PST: Clarified that you may see a change in the distribution of traffic of organic keywords.

Tuesday, 7 September 2010

Are you eager to optimize your conversion rate, but feel a little bit overwhelmed by all of the tools available to help you? Introducing ‘Improving Online Conversions for Dummies’!

We have just released a simple, easy to follow mini book, in conjunction with John Wiley Publications, to help you get a better grasp of the conversion improvement tools offered by Google. Improving Online Conversions for Dummies explains how you can make sure your ads show on searches that are most likely to convert into sales. Understand which ad clicks and impressions lead to conversions, better apportion your marketing spend and even develop your own conversion attribution model. Discover the secrets to getting more bang for your buck with this ebook!



For more information, visit www.google.com/conversion/fordummies

Friday, 3 September 2010

On the Google Analytics API Team, we’re fascinated with what people create using the Data Export API. You guys come up with some really amazing stuff! Lately, we’ve also been paying a lot of attention to how people use it. We looked at whether the API has stumbling points (and where they are), what common features every developer wants in their GA applications, and what tricky areas need deeper explanations than we can give by replying to posts in our discussion group.

As a result of identifying these areas, we’ve written a few in-depth articles. Each article is meant as a “Deep Dive” into a specific topic, and is paired with open-source, sample reference code.

In no particular order, the articles are as follows:

Visualizing Google Analytics Data with Google Chart Tools
This article describes how you can use JavaScript to pull data from the Export API to dynamically create and embed chart images in a web page. To do this, it shows you how to use the Data Export API and Google Chart Tools to create visualizations of your Google Analytics Data.

Outputting Data from the Data Export API to CSV Format
If you use Google Analytics, chances are that your data eventually makes its way into a spreadsheet. This article shows you how to automate all the manual work by printing data from the Data Export API in CSV, the most ubiquitous file format for table data.

Filling in Missing Values In Date Requests
If you want to request data displayed over a time series, you will find that there might be missing dates in your series requests. When requesting multiple dimensions, the Data Export API only returns entries for dates that have collected data. This can lead to missing dates in a time series, but this article describes how to fill in these missing dates.


We think this article format makes for a perfect jumping off point. Download the code, follow along in the article, and when you’re done absorbing the material, treat the code as a starting point and hack away to see what you can come up with!

And if you’ve got some more ideas for areas you’d like us to expound upon, let us know!

Wednesday, 1 September 2010

More and more people are surfing the Internet from their phones these days. Take a look at the following graph. It shows the number of monthly visits to googlestore.com from Android, iPhone, and BlackBerry devices over the past 2 years. There were 277 visits in Sep, 2008. But in July of 2010, there were over 13,000 visits!










Given this kind of growth, it makes sense for many businesses to set up a mobile device-friendly site. If you’ve been considering whether to create a mobile site, you may want to check out the Mobile Devices report in the Visitors section. You can see how many visits you received from each mobile operating system, how many pages they visit on average, how much time they spend on your site, as well as see conversion and ecommerce information.































In next week’s Back to Basics, I’ll show you how to create your own trend graph like the one in this article, so you can really dig into the numbers for your own site.