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Analytics In The Palm Of Your Hand

Friday, 29 October 2010

This weeks’ featured app on the Analytics App Gallery is the BAM Analytics Pro app for the iPhone. If you have ever needed to reference your site metrics in a meeting or situation where it wasn’t appropriate to fire up the laptop and open up your account, then you may find a Google Analytics smart phone app valuable.

This app, developed by Blast Advanced Media (one of our Certified Partners), uses the Google Analytics API to quickly and securely access all of your reports, apply your Advanced Segments, and even create Custom Reports right within the app. You can view common preset date ranges, set a custom date range, or compare to a previous date range for additional context. All the functionality you could need within a clean, user-friendly interface. Here's a sample of custom reports functionality:

BAM Analytics Pro can be purchased here on the iTunes app store for $1.99. Our Google Analytics Certified Partners are some of the most inventive users and developers of our free API. Many of their business-driven tools and applications make it to our Analytics App Gallery, where you can find a variety of solutions that compliment and enhance our product.

Swissotel's High Value Visitor Segment

Wednesday, 27 October 2010

Thanks to the Conversion Room Asia-Pacific Blog and Vinaoj's team in Singapore for this insightful, enterprise-class case study.

Need a little inspiration for ways to get a LOT our of Google Analytics? Well, Advanced Segments is a great place to start. As you might know, they allow you to dissect your traffic into audiences that you actually care and want to know more about. And here's a great example of use by a major hotelier.

Barbara Pezzi, Director Webmarketing, Fairmont Raffles Hotels International, is back to share with us how Swissotel properties in Singapore used advanced segments to better understand the needs of their UK and Australian visitors. By using advanced segments and her detective skills, Barbara was able to determine that Australian visitors were seeking deals, while her UK visitors were more interested in the quality of the rooms. She was able to optimise her AdWords campaigns and messaging based on these insights, and quickly managed to see a 68% increase in revenue and a 92% increase in conversion rates.

Next Week: Ad Tech New York

Tuesday, 26 October 2010

If you're an enthusiast of "Mad Men" (a television drama about advertising in New York in the 1960s), and Google Analytics, well then you're probably enjoying the dichotomy that is advertising today: a mix of decades-old media creatives and buys, and cutting edge online tracking and social graphing, and a ton in between. Getting a birds eye view is wildly interesting and educational. And the ad:tech Conference in New York City next week might be a good event for you to attend. And the best part is that it not only gives a bird's eye view, but also offers compelling and educational sessions for the savviest online marketer.

Happening on Wednesday and Thursday (November 3-4), it's a fun, relevant, informative conference, where "brands, agencies, publishers and service providers come together to share, network, learn and do business." You'll see traditional advertising agencies there, as well as the latest in online. Just take a look at the different conference seminar tracks titles:
  • Brand
  • Social Media
  • Digital Demographics
  • Media Strategy
  • Performance
And we'll be there as well with a sponsored workshop called "Improving Your Online Advertising with Insights from Google Analytics" on Thursday at 11:45am. In it, Phil Mui, our senior product manager, will present some developments in the product, as well as existing features, that will appeal especially to online marketers and advertisers. Register here. We hope to see you there.

PM POV: AdWords Reports Launch

Monday, 25 October 2010

This is the first of a new series of intermittent posts by Google Analytics Product Managers - the people leading the prioritization and production of features and improvements to GA. We wanted to add a little color to what you're seeing and let you know the how and why behind the process we take. In this first post, Jayanth Mysore tells what happened behind the scenes during the prioritization and development of the AdWords reports. Enjoy.

In June, we launched the new AdWords reports in Google Analytics. Today, I thought I’d share some of what goes on behind the scenes -- how we went from an idea to the actual reports that you see in Google Analytics today.

How did it begin? Many of you use Google Analytics expertly, and in innovative ways. You told us all the ways in which the product was lacking...in emails, blog posts, tweets, and in Q&A sessions and face-to-face meetings at conferences like SES and eMetrics. We’ve found that expert and innovative users are often the best at articulating what’s going to be most valuable to all users. So, we listen carefully to feedback, and one area we heard -- and learned -- a lot about was AdWords reporting.

For example, many of you told us that you were writing intelligent filters that would allow you to see actual search queries. Some of you were looking for ways to understand the effectiveness of campaigns on the content network. And many of you were struggling with how to make day parting decisions. We heard all this and said “We need to help here, here, here and there. Let’s go build!”

Next, we built a version of the reports and asked a few hundred of you to try it. This version did even more than what you see in the reports today because we wanted to test some promising, but challenging ideas. We can’t always put all the features we’d like into a product update. Sometimes we have to leave something out because it runs too slowly and making it run faster requires extensive design work. Other features simply won’t work for all Analytics users. Still, we wanted to test everything and determine which aspects of this we could offer everyone and how soon.

Our test users are terrific -- very innovative, highly trustworthy and they never hesitate to point out things that are too slow or too hard to use. We worked closely with these users and studied the usage data to figure out what we could and couldn’t do. It became amply clear that providing a list of AdWords dimensions to segment the reports was very very valuable. We wanted our users to have this right away. Other features were also valuable, but would require time to fully develop. In the end, we decided that we’d rather give users something significantly better immediately, and keep working to offer more down the road.

Finally, we rolled out the new reports gradually over weeks. We take user experience very seriously, no matter where in the world you are. During these initial weeks, we monitored usage, latency, bugs filed, tweets, e-mail feedback. The other thing we did was to translate the product so that all of you, across the world, could use the new reports.

Finally, when we were ready, we hit the go button, flipped a bit to expose the feature, blogged about it....and you all saw the new AdWords reports in the Traffic Sources section.

Work doesn’t stop after the release. We immediately started working on some of those hard problems I talked about and we’ve already made some progress. In August, we made the new AdWords dimensions available in Analytics Intelligence.

We continue to work on these reports, so stay tuned. And, thanks for your active usage of the product. You all make our day!

Web Analytics TV #13 - For the Ninjas

Friday, 22 October 2010

Well 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 introduce our new ninja award program (and ninja chop to go with it). Going forward, we will pick our favourite question and award the person the Analysis Ninja of the Episode award! They will get an autographed, personalized, copy of Web Analytics 2.0.

Our first winner is Sushant from New York for his excellent question on tabbed browsing and it’s impact on session level data. Congrats and please keep the great questions coming (and win!).

Here is the list of last weeks questions.

In this action packed episode we discuss:
  • (2:35) Combining (A AND B) OR (C AND D) in advanced segments
  • (4:03) Is there a way to tell how many people have opted out of being tracked by GA
  • (6:18) How does tracking Google Analytics and Urchin work together
  • (7:53) How is tabbed browsing tracked in Google Analytics?
  • (10:30) Do Website Optimizer A/B tests only track direct traffic?
  • (11:27) Are there any survey/voice of customer tools that integrate with GA?
  • (12:47) Does the async code execute faster than the traditional snippet?
  • (14:40) You can’t track users who have opted out of GA
  • (15:13) Why table report filters get removed when you navigate away from a page
  • (16:30) Why are there differences between Unique visitor reports? Which to use.
  • (18:00) Can Google Analytics track live chat forms?

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.

Post content

Harvard University And A Geo Analytics App

Monday, 18 October 2010

Back in Web Analytics TV episode 8, Cesar Brea asked if there was a way to use Advanced Segments to get performance metrics for a list of target cities. As Cesar Brea pointed out in the post comments, because Google Analytics only returns city names (e.g. "Paris"), you need to request both the city and region names to disambiguate between cities with the same name (e.g. "Paris, Texas" vs. "Paris, California" vs. "Paris, France").

The Advanced Segment builder in Google Analytics allow you to create expressions only in the following form:

(City A OR City B) AND (Region X OR Region Y)

But what Cesar really needed was to build an Advanced Segment of the form:

(City A AND Region X) OR (City B AND Region Y)

One option is to create individual segments through the interface, export to CSV then open all the CSV files, and merge the data into a single file. Lots of work. The other option is more elegant and powerful: automate the task with the API.

An Elegant Solution
So Cesar did exactly that and partnered with Newcircle Consulting to built the free Target Towns Google Analytics API solution. With Target Towns, you simply authorize the tool to access your Google Analytics account. You upload a list of regions and cities, and the tool runs a bunch of API requests for you to get performance data for your top target towns. Simple!

Business Impact
What’s really interesting is how analysts are using this tool to get better insight into the geo-breakdown of their marketing campaigns.

One geo-information user is Perry Hewitt, Director of Digital Communications and Communications Services at Harvard University. One of Perry’s goals is to increase non-branded search referrals to Harvard’s website. Specifically when senior university leaders and faculty speak at events, Perry can start to measure which new keywords people use to learn more about the topics and speakers.

Perry says, "At Harvard University, analytics have become an essential part of our digital communications strategy. Services like the Target Towns report help us understand what resonates where -- and are an interesting new complement to the Google Analytics capabilities we already use."

We’re thrilled to see developers overcoming challenges and solving business problems with the API. If you have done some exciting work with the Google Analytics platform, lets us know in the comments. We love to hear your stories.

Introducing In-Page Analytics: Visual context for your Analytics data

Friday, 15 October 2010

When looking at Google Analytics reports, sometimes it’s difficult to visualize how visitors navigate on a given website page. To make this visualization easier, some users keep the website open in another browser tab so they can reference it while looking through reports. Others rely on the Site Overlay report in Google Analytics, which, admittedly, hasn’t worked as well it could.

Today, we’re happy to share with you a bit of what we’ve been working on to address this problem. We’re releasing a new feature into beta: In-Page Analytics. With In-Page Analytics, you can see your Google Analytics data superimposed on your website as you browse.

Take In-Page for a spin and let us know what you think. In-Page Analytics is still in beta, so some things in the report may not work perfectly yet. There’s a lot left to do, but there’s even more that we want to build going forward. In-Page is currently available for all English users of Google Analytics. We also have a demo video that walks you through the feature and how you might use it.

You’ll find the In-Page Analytics report in the Content section in your Google Analytics account, and it replaces Site Overlay. You can read more about In-Page in the Google Analytics Help Center. Let us know what you think and how you’re using it!

Back-to-Basics: Non-Brand Keywords

Wednesday, 13 October 2010

The majority of search referrals to the Google Store come from brand related searches -- searches that include brand references like “google store”, “android t-shirt”, or “youtube jacket”. But, as I dug into the data, I was surprised to find that googlestore.com gets many non-brand related search referrals as well.

Take a look at the non-brand searches that send traffic to your own site -- I think you’ll find the data interesting. By isolating non-brand keywords, you take brand recognition out of the equation and focus on the products that people look for -- and click over to find on your site.

Here’s a quick way to see your non-brand keyword traffic. Under Traffic Sources, go to the Keywords report. Then, in the Filter Keyword box at the bottom of the table, select Excluding, and type in your brand name.

If you have multiple brands, type them all in separated by the | sign. Here’s how this looks for googlestore.com:


You’ll notice that I also excluded the word “content”. This is because the report includes “content targeting” and I don’t want to include content targeting referrals.

Click Go to see the filtered keywords. If there’s anything else you’ve missed, just add it to your exclude list and click Go again. Here are the results for the Google Store.

That’s all there is to it. Try it on your own data and leave us a comment letting us know what you find!

Back To Basics: Part 3 - The Power of Exclusion

Wednesday, 6 October 2010

In Part 2, we saw that a store owner gained an unexpected lift in search traffic to his website after running a promotion on a referring site. The questions we left until this week to answer are these: How many extra searches resulted from the promotion? And, what keywords did people search on?

To answer these questions, we need to compare what usually happens versus what actually happened after the promotion. A good way to do this is to use the Compare to Past feature on the date range selector. If we compare the previous week with the promotion week, we can see how much of a lift there was after the promotion.

Notice that we use the exact same days, Monday through Sunday, so that the days of the week line up. Here is the resulting graph. The green line is the search traffic leading up to the promotion (what he would ordinarily expect without a promotion); the blue line is the search traffic during and after the promotion.

From the report below, you can see the specific increase for each keyword.

The promotion resulted in a 209.68% increase in searches on the first keyword and an increase of 1,242.86% in searches on the second keyword. That’s good to know. It looks like one day promotions are the way to go for this business.

This is good example of how to use Compare to Past. You might also want to check out this tip on how to line up your date ranges when using Compare to Past.

Python Library for the Management API

Friday, 1 October 2010

It’s been only 7 weeks since we’ve launched the Google Analytics Management API and we’ve heard a lot of great feedback. Thanks!

Since Python is one of our more popular languages, we’ve updated the Google Analytics Python Client Library to access all 5 feeds of the Management API. Now it’s easier than ever to get your configuration data from the API. Awesome.

To show you how simple it is to use the library, here is an example which returns all the goal names for a profile:
import gdata.analytics.client

APP_NAME = 'goal_names_demo'
my_client = gdata.analytics.client.AnalyticsClient(source=APP_NAME)

# Authorize

# Make a query.
query = gdata.analytics.client.GoalQuery(

# Get and print results.
results = my_client.GetManagementFeed(query)
for entry in results.entry:
print 'Goal number = %s' % entry.goal.number
print 'Goal name = %s' % entry.goal.name
print 'Goal value = %s' % entry.goal.value

To get you started, we wrote a reference example which accesses all the important information for each feed. We also added links to the source and PyDoc from the Management API Libraries and Examples page. Have a look and let us know what you think!


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