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Women make up more than half the global population, but hold fewer than a third of the world’s engineering jobs. In the U.S., female students comprise fewer than 15 percent of all Advanced Placement computer science test takers. Even in high-tech Israel, few girls choose computer science. Not only is this a loss to companies like Google and everyone who benefits from a continually developing web; it’s also a lost opportunity for girls.

Beginning in 2008, a group of female engineers at Google in Israel decided to tackle this problem. We established the “Mind the Gap!” program, aimed at encouraging girls to pursue math, science and technology education. In collaboration with the Israeli National Center for Computer Science Teachers, we began organizing monthly school visits for different groups of girls to the Google office and annual tech conferences at local universities and institutes. The girls learn about computer science and technology and get excited about its applications, as well as have a chance to talk with female engineers in an informal setting and see what the working environment is like for them.

Since we started this program over three years ago, we’ve hosted more than 1,100 teenage girls at our office, and an additional 1,400 girls at three annual conferences held in leading universities. These 2,500 students represent 100 schools from all sectors and from all over the country: Tel Aviv, Haifa, Tira, Beer-Sheva, Jerusalem, Nazareth and more; what they have in common is the potential to become great computer scientists.

The results are encouraging. For instance, some 40 percent of the girls who participated in last year’s conference later chose computer science as a high school major.

We encourage people in other countries, at other companies and in other scientific disciplines to see how they could replicate this program. You can read more at the project site. Currently, we are working with the Google in Education group to expand the program to more offices globally and get even more young women excited about computer science. The difference we can make is real: At one of our first visits three years ago, we met a 10th grade student named Keren who enjoyed math but had never considered computer science as a high school major. Last month, Keren informed us that the visit made such an impact on her, she decided to change her major to computer science. “Talking to women in the field helped me change my mind,” she said.


The Official Google Blog

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Many of the tasks we’ve traditionally undertaken have been moving over to mobile over the past few years thanks to devices like the iPhone that have shifted our expectations.

Email usage is one of those tasks, with email marketing company Campaign Monitor revealing some interesting patterns from the last two years of data it has collected from — and here’s a sample size for you — over 2 billion recipients.

The percentage of emails opened on a mobile device has risen from just 4% in May 2009 to 20% in May 2011 while desktop client usage has declined by 11%. Webmail has shown the least change over two years, with a 4% decline.

As one might expect, among mobile devices the iPhone is leading the pack with a whopping 71.98% lead. The iPad actually appears next at 14.95% before other smartphones such as Android, which makes up 8.24% of the mobile email use.

One of the points that David Greiner, co-founder of Campaign Monitor, makes is that CSS support on mobile devices is generally far superior to support in desktop clients. If these trends continue and clients with CSS support become the norm we could be moving toward a golden age for email design, like the one we’ve seen on the web this year as HTML5 and CSS3 support has become more widespread.

TNW Aggregated Feed

The following is a guest post from Julie Ferrara-Brown, Director of Quantitative Analysis for WebShare. WebShare is one of our Website Optimizer Authorized Consultants. The case focuses on exploring more than just a single conversion.

Often, optimizing a site means more than optimizing for a single conversion. Understanding how your test pages and sections affect bounce rate, ecommerce revenue, time on site, and all the other metrics provided by Google Analytics can be even more useful than a single conversion rate in painting a picture of how your site is used.
Good news! You can use Google Website Optimizer and Google Analytics together to open up a whole new world of optimization and testing for your site.
A Single Conversion is Not Enough
Catalogs.com worked with WebShare, a Google Analytics & Website Optimizer Authorized Consultancy, to plan and run a test that integrated both tools to collect and analyze a wealth of data. With a number of different monetization paths, the Catalogs.com website wanted to know not only whether alternative versions increase overall conversions, but also what impact would these versions have on specific types of conversions and the revenue associated with them.
During this test, while Website Optimizer as a standalone tool was able to show that overall conversions had increased by 6.8%, the integration with Google Analytics showed much more granular and relevant improvements:
  • Specifically, catalog orders rose by almost 11%
  • Total revenue from all conversion types was up 7.4%
“It’s great to know that the changes we tested gave us an increase in our overall conversions, but all of our different conversion actions are not equal in terms of the revenue they bring in,” explains Matt Craine of Catalogs.com. “It’s possible that the increase in overall conversion rate could actually lose us money because it was due to a design enticing visitors toward a low value conversion at the expense of our higher value actions.”
Setting up the Test
The aim of this experiment was to test different layouts across all of the sites’ merchant pages. The experiment was set up as a single variable, four-state MVT, encompassing every one of these merchant pages.
Three variations were created, and each merchant page was available in one of its three formats by using different file extensions (.alpha, .beta, and .gamma). The test variable was actually just a piece of script that controlled which version of merchant pages a visitor would see.
Running the Analysis – Website Optimizer
Over the course of a few weeks, almost 70,000 unique visitors participated in the experiment and performed almost 30,000 overall conversion actions. We could see in the Website Optimizer experiment reports that we had found a winner in the Beta version:
This, however, simply told us that Beta was more likely to result in a conversion, regardless of type or associated revenue. Enter Google Analytics.
Getting Additional Data From Google Analytics
In this case, the easiest way to see the Google Analytics data for each variation is by using Advanced Segments. Since each template had its own extension, we can create an advanced segment that matches the “Page” dimension with a specific extension. The result is that the segment will only include data for sessions that included a pageview on one or more pages that matched that condition. Below is an example for the Alpha variation:
After creating a segment for each of the variations, it’s simply a matter of applying those segments to any report in Google Analytics and setting the appropriate date range. Now we can see, side-by-side, data for all the variations in any of Google Analytics’ reports.
Running the Numbers
As an analytics platform (and not a testing platform), Google Analytics was not designed to perform the necessary statistical analysis to evaluate this data, but with the numbers it provides, you can perform an enormous amount of offline analysis. Let’s take the case of the bottom line, be-all, end-all metric: Total Revenue.
For all the statisticians out there, in this particular case an F test blocked by day was performed to compare means. The results can be seen in the following analysis.
What this boils down to is that circles that do not overlap or barely overlap represent a significant difference, and in this case the Beta variation is statistically our best variation in terms of generating revenue.
Why Look at Lots of Metrics?
Although we’ve only shown revenue analysis here, it’s important to note that performing this kind of analysis on a number of different metrics can really help you understand your visitors and their experience.
For example, during this test we also found that the Beta version (the version that provided more conversions, more high value conversions, and more revenue) also had the worst bounce rate!
Just because a visitor doesn’t leave a site from the first page they land on does not mean they are going to convert.
Get Integrated!
Depending upon your test type and implementation, there are a number of different ways to integrate Website Optimizer experiments with Google Analytics, and hopefully this post has helped to demonstrate the power of having all that wonderful data available in your testing.
“Looking at a puzzle piece by itself is a good way to start toward a solution, but it doesn’t tell you the full story,” says Catalogs.com owner Leslie Linevsky. “Putting all those pieces together shows me how small changes are impacting my business as a whole.”
Thanks to WebShare and Catalogs.com for sharing this case study.


Google Website Optimizer Blog

UTI revved up their conversion rate with Google Website Optimizer. By conducting rigorous testing, making design improvements to their landing pages, and increasing AdWords investment to capitalize on their higher conversion rates, UTI cut their cost-per-application request in half and increased their request volume by more than 700% in in marketing campaigns that used the new landing pages. Read more to learn how they did it!

Posted by Trevor Claiborne, Website Optimizer team


Google Website Optimizer Blog

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