Suburb Matchmaker - Best Student Entry Winner

Few weeks ago, two friends and I participated in a contest called Mashup Australia organized by The Government 2.0 Taskforce with the aim to help them ‘show why open access to Australian government information is good for our economy and society’.

Our application was called Suburb Matchmaker and won the Best Student Entry prize. How was Suburb matchmaker born? Our team was only formed at the Open Australia Hackfest at Google where people with different skills developed mashups using data from the government for the benefit of citizens. Although we all had a number of ideas, we had a common interest in the data related to crime statistics from http://data.australia.gov.au/.

We believe that information is only as powerful as the application that is given to it. We decided to use government data to help citizens find the best suburb for them by providing their preferences in a number of factors (more families with children, with no children, more single people, etc). At that point we had one week to finish the mashup. We also used crime data to provide information about the crime classification and incidents in each area of NSW.

One of the benefits of Suburbmatchmaker is that not only can people find the area of their dreams to live based on the suggestions from the application; but also, those who are not looking for a new suburb to live in can find out more information about their area and to connect with it. Such information and trends are displayed in a text mode and in more detail with a dashboard. Also, you can see the key findings of Crime victimization in Australia, based on results of a survey conducted by the Australian Institute of Criminology in 2004.

Another benefit of this mashup is that it allows citizens to interact with the information by providing a space to promote events and post pictures of their area. This part of this application could be of particular interest for isolated communities interested in attracting more visitors and people to settle in the community.

Go to visit Suburb Matchmaker and/or follow us on Facebook

Google Analytics - Intelligence Report 2nd Part

In the last post (Google Analytics - Intelligence Report) I started talking about the Business Intelligence report in Google Analytics. But I just highlighted the main features of that. However, that is not everything, now that you know that you can create custom alerts where you can specify to Google Analytics what to watch for, we would like to tell you how to create and manage custom alerts.

There are two ways to create custom alerts:

1. The easiest one is from the Intelligent report, clicking '+ Create a Custom Alert'.

That action will take you to a new page where you specify the conditions to trigger the alert.

1.1 Enter the alert name
1.2 Specify to the profiles that you want to apply the alert using the drop-down menu

1.3 Select a period (day,week,month) to apply the alert.

1.4 Select the check-box if you want to receive an email when the alert is triggered.
1.5 Create the conditions for the alert. The conditions are divided by dimensions and metrics.

Lets say that you launched a new campaign in three regions and you want to know if there is an impact for only the visits that come from a specific city, and when they exceed certain number. In order to do that you will select as dimension city and as condition the city you want to monitor.

And then you select the metric and value which will decide when to trigger the alert.

1.6 Finally you click 'Create Alert' and this would be displayed in your Intelligence report when the alert is triggered. A difference with the automatic alerts is that custom alerts are applied to the report since the moment that they are created. For example, if the number of visits for that city was greater than 1500 yesterday but the custom alert was created today, the user will not see that custom alert in the report. If the number of visits is exceed for the same conditions in a future and the custom alert is still applied to that profile they will be shown in the report.

2. The other way to create custom alerts is accessing the 'Manage Intelligence Alerts' panel found at the left hand of the screen under 'My Customizations' menu

In this panel you can not only create a new alert, but also import alerts from other profiles. See other alerts created under that account, and being there you can delete them, hide them or edit them.

2.1 To import an alert from other profiles click 'Import alerts from other profiles'. This action will display a dropdown list with other custom alerts created.

You will see the new alert imported and several action that can be applied to that alert.
As you can see in the image you can edit, copy, share, delete and hide from profile the alert imported. 'Avg. Time on Site > 10'.

NOTE: Delete an alert means that you are going to delete the alert not only from this profile, but also from all the others that it has been applied. While Hide From Profile in other words means delete the alert only from this profile.

2.2 You can also display Other Alerts for that account and add them to this profile.
2.3 Finally you can see the alert templates and copy and then edit them for our own purposes.

Google Analytics - Intelligence Report

This report shows a list of custom and automatic alerts for daily metrics in the date range selected. Although only the first phase of the Analytics intelligence feature has been launched, you can find great benefits for you business using this feature. So, what exactly does Analytics Intelligence? In a sentence it constantly monitors the information and alerts you when significant changes in data patterns have occurred. Such alerts are provided in three time dimensions: day, week and month.

Now, the report looks pretty nice, full of elements and user interaction. So, how should I interpret and understand the intelligence report in a way that I can take strategic decisions for my business?

I will explain to you in detail the elements and usability of them in the Analytics Intelligence Report.

To make it easier for you, we visualize the report divided in 3 main sections, header, graphic section and Alert value section.

1. Header Section: The first section only contains the title of the report that identifies if the report shown is based on daily, weekly or monthly data. As in any of the other reports in Google Analytics, as soon as you change the date range, the report is updated to display the corresponding information. The way to move from a daily alerts report to weekly or monthly is using the left panel shown at the left hand of your screen.

2. Graphic Section: This section contains two graphics, the first one is a line chart and the second one a bar chart.
2.a Line Chart: By default this line chart shows as metric the number of visits in the date range selected. However, this graphic is linked to the other sections.
2.b Bar Chart: This chart will show information about custom and automatic alerts. It differentiates the type of alerts using blue colour for custom alerts and green for automatic alerts.

In this section:
- You are able to select both type of alerts to be displayed, or just one of them.
- You can select a specific bar to see in detail the number of alerts triggered and the day, week or month when it happens.
- You can move through the time dimension (e.g from day to day, week to week or month to month) selecting a specific bar or using the arrows below the graphics to go back or forward.

3. Alert Value Section: This section displays the custom and automatic alerts grouped by metric or dimension. It means, that it's up to you how to see the information of the alerts triggered in the day, week or month selected. By default the report shows the data grouped by metric; however, sometimes is easier to understand the information grouping that by Dimension.

The first part of this section will list the custom alerts triggered in a specific day, week or month and also it has a link to create new custom alerts. Custom alerts, differ in the way they are displayed with the automatic alerts. While automatic alerts display a set of elements that can be regrouped and where you can variate the level of sensitivity, custom alerts only display the name of the alert given when it was created and the option to edit it.

After the custom alert sub section, at the top-right hand of this section you can set the alert sensitivity level. Higher means that you will see more alerts.

Getting in more details, next to each metric result there are four elements that help you to comprehend why the alert was triggered.

a. Percentage of increasing or decreasing compared to the historic data. That percentage is accompanied by an arrow (up or down) and it is displayed green when it has a possitive impact or red when it has a negative impact. Remember, that not always increasing means positive. A common example of this is the bounce rate, when the bounce rate increase significantly could mean that the number of people who visit your site leaves it without visiting any other pages.

b. Value Expected. This value is useful to have an idea of the impact that has that significant change in our site. The value expected is based on the historical data; therefore, you can evaluate with the expected and actual value of the metric how critical is this change more accurate. Notice that there is another element (d) that will show you this evaluation graphically.

c. Graphic Button. Rememeber when in point 2 (Graphic Section) we mentioned the link between the graphics and the rest of the report? well, now you will see how opportune is this connection. Next to each metric result there's a button that interacts with the line chart. As we told you before, the default metric displayed is number of vistis; however, if you want to analyze in that date range the behaviour of a specific metric shown in the automatic alert sub-section you can do it clicking that button. Intermediately, the button will become darker, and the line chart will display the metric selected. see the image below as an example, where the metric selected for the total traffic was pageviews; therefore the graphic changed, the tab at the top of the graphic shows the new metric and the button that corresponds to that metric is darker.

d. The last element is 'Significance'. The significance of a metric is calculated by the comparison between the metric and the expected value for that metric. It means that a bigger difference between these values will show a higher significance.

Finally, there is an option to create custom segments from a specific automatic alert triggered. This functionality is useful when we are interested to see that information applied to other reports and then analyse in detail the reasons that make that this alert was triggered in that period.

Take this as your first step to meet the Business Report Intelligence, and when you feel ready check the second part of this post with more features.

In Rebuttal to 'The Cost of Free' workbook

If someone tells you “Free puppies can be messy”, I will tell you “Expensive puppies can be messy as well, it depends of you”. I’m talking about puppies in my IT blog because a few weeks ago I read a document presented by John Lovett from Omniture (The cost of Free). In that document he makes an analogy between free analytics tools and free puppies. He says “When you first encounter them, they are cute, inviting and the idea of having them sounds wonderful. When that irresistible urge strikes you, first consider how much work anything free may require. In the case of the puppy, that means food, walks, shelter, vet bills, etc”. Yes, I agree, but puppies that you pay for require that as well. Dogs are there to be loved (free or expensive ones), as tools are there to be used. With free analytics tools you don’t pay for the product you pay for experts that help you to increase the return of investment. With expensive analytics tools you pay for both.

John presents in his workbook a case study comparing Omniture SiteCatalyst (commercial tool) and Google Analytics (free tool). However, some of the items mentioned don’t apply anymore. For example, he mentioned that Google Analytics only offers 4 conversion goal funnels and 1 custom variable. Well, as I mentioned in my last post, Google Analytics now offers 4 sets of Goals where you can include in each one 5 goals, having a total of 20 goal funnels per profile, and up to 50000 custom variables (5 in each request), plus other great features such as the intelligence report and alarms. I won’t go in detail with the side by side comparison made by John but you can find that in the Mangold Sengers’ official blog.

What I most disagree with in John’s workbook is the fact that he is trying to make out that Omniture SiteCatalyst is a better product because is not free. First of all, each tool has different features and depending of the business’ requirements some of them may suit your business more than others. Secondly, the success of web analytics doesn’t remain in the tools. I’ve been following the 10/90 rule proposed by Avinash (Web Analytics an hour a day), which states that ‘10 percent of the budget should be spent on tools and 90 percent spent on people (brains) who will be responsible for insights’, this is exactly what free tools like Google Analytics offers you. You know your business, you know what your goals are, you choose the tool that fits your requirements, you get your free or not free tool and then you invest in expert people who will help you to get the best results from the data provided by the tool. Going back to the free puppy, you can pay for the puppy or you can get it for free, but at the end if you don’t want a messy puppy you will invest time or money to educate it, for sure if you do that you will love your puppy.

New and Tasty Features in Google Analytics

A bunch of new features were released yesterday, they are described in three words as Powerful, Flexible and Intelligent. Some of them are simple but very useful and others have lots of components that give us more tools to analyse and take strategic decisions to improve the performance of our websites.
I found very interesting the Analytics intelligence reports, although you will have to take your time to read about it and take the best taste of this feature. Other features include site engagement goals, mobile reporting, advance table filtering, share advanced segments and one of the best ones for me Custom Variables. Thanks a lot for the last one, I was waiting for that for long time. Hopefully with this new feature I'll leave away several custom scripts created to achieve my goals.
Well, if you want to find more information about the new features, access the official Google Analytics blog or the Mangold Sengers blog, you will find a description of this features in more detail.
Try them and enjoy them!

Google Analytics API new changes

For those who are using the Google Analytics API, around one week ago some changes were announced in the official blog of GA.
From the changes posted one of the most significant are:

• The possibility to get the timezone and currency from the account feed (http://www.google.com/analytics/feeds/accounts/user@gmail.com)
• The increased number of data that can be retrieved from the API at once. Currently we can request up to 10.000 rows of data.

For more information about the API go to the Google Code Page

Google Analytics and Social Media

Social networking can be used to increase traffic to your website, generate more sales and leads and enhance your visibility to potential and existing customers. In order to achieve these objectives you need to assign value to each initiative you undertake and align social networking with your business objectives. If you want to increase the number of visits or improve your visibility in the marketplace, you should focus on listening to clients and competitors (Google Alerts, Twitter), share content (Flickr, YouTube, Blogger, RSS, MySpace), build good relationships (Facebook, LinkedIn), dialogue with customers (Twitter) and generate buzz (Digg, Twitter) and participate in the community (Twitter, Facebook).

Once you are active within social networks you need to determine how you are performing and calculate your ROI (Return On Investment). Google Analytics allows you to measure metrics for visitors accessing your site from social networks in quantitative terms, but it is also important to understand the qualitative value of your efforts.

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Bearing in mind the metric that wants to be measured using Google Analytics, it's possible to determine how well we are performing; although with social media in quantitative terms we need to be careful and do not forget that also we are measuring qualitative results. Some of the best practices when measuring the results for social media traffic include the definition of goals associated with the traffic from social networks, and the loyalty reports.

The next are some example of social media tools that have become famous for marketing strategies and with the use of Google Analytics we can see from which social media tool our visitors are referred (e.g twitter.com, digg.com, facebook.com)

1. Flickr

If you have an account in Flickr and do you want to use it for marketing, it's useful not only adding pictures but also making comments about them that contribute to a discussion about the product or service offered. It is recommended create groups for specific topics and invite clients to join them.

To help that people find you on Flickr when they use Search Engines, it is useful to tag the pictures with relevant keywords and descriptions. It is also important to create a profile that helps people to recognise you and find useful the information that you share.

2. Facebook

In the last years Facebook has become very useful for different purposes that are not limited to share pictures and update our status in a social meida site. Lots of businesses advertise in Facebook, and have created their own account to answer questions, keep in touch with clients and create online marketing comunities that can be classified by city, region, workplace, and school.

3. Twitter

Twitter helps to gain attention for the business, improve traffic, address people to your business and build partnerships in a easy and cheap way because everything you tweet (links, text, images) in your profile is seen by people that is following you. Having a twitter account increase the probability of being found in Search Engines.

Although by default GA shows that the source is comming from twitter.com, it's possible to add the GA's campaigns with the tracking parameter and convert it in a small URL using tools like tinyURL.com

Options to check social media traffic in Google Analytics

• By default GA recognise the source from the visitors are coming; therefore, making use of advanced segmentation is possible to compare metrics of all visits with those generated by social network tools (twitter.com, facebook.com, digg.com...). The next are the steps to follow:

1. Click in Manage Advanced Segments
2. Click in the linck +Create new custom segment
3. Drag the Dimension "Source" to the "add or segment"
   
4. In the condition choose "Matches Exaclty"
5. In the value field insert all the Social Media tools from where your site can get traffic (e.g. twitter.com)
6. Add "or" statment
7. Then repeat step 5 & 6 until you have entered all the Social Media sources.
8. Click in Test Segment
9. Click in Create Segment
10. Start comparing other metrics in your reports with this segment.
    

This option is easy to implement but every time that you identify a new social media traffic source, it has to be added to the segment. Can be possible to use the Condition "Contains" instead of "Matches exactly" because sometimes the traffic is generated from subdomains such as uk.facebook.com.

• Other option is to create filters for the social media traffic generated.
  

The advantage of creating a filter for the social media sites is that you can dintiguish from the other referral links. In order to create the filter that match all the social networks from where we want to group we need to use regular expressions (a little bit similar to the advanced segment).

1. Go to the profile where you want to add the filter (Remember the filters affects the profile where they are applied)
2. Click in Edit
3. In the section "Filters applied to Profile" click in +Add Filter
4. Select "add new Filter for Profile"
5. Enter a name for the filter (e.g. Social Media Traffic)
   
6. Select Filter Type "Custom Filter" Advanced
   
7. For Field A -> Extract A select Campaign Source and in the field text write all the social media sources you want to group in this filter divided by "|" (e.g. filckr.com|twitter.com|facebook.com)
8. For Otuput To -> Constructor select Campaign Medium and write the name that you want to re-label for this referral in the text field (e.g Social Media)
9. Click in Save Changes

• Another option is to add the plugin created by VKI Studios that reports automatically the social media sources.
  

The steps are very simmilar to the other Grasemonkey plugins.

1. Install Greasemonky in your Firefox (https://addons.mozilla.org/en-US/firefox/addon/748)
2. Restart Firefox
3. Install VKI script (http://blog.vkistudios.com/downloads/greasemonkey/smmPluginForGA/1.2/smmPluginForGA.user.js)
4. Log in to the GA account and check the Content Detail report for example.

Note that this option only works for firefox.

Google Analytics Seminars for Success in Australia

For those who are interested in improving their online marketing, a good option is to take the Seminar for Success designed by Google Analytics experts.

By attending this seminar you will learn how to monitor, measure and improve your website performance and identify online opportunities as well as new strategies. In addition, you will be familiarized with the Google Analytics tool, understanding the features and reports provided in the tool and how to take business decisions based on them.

The Seminars for Success have been run in different countries and are sponsored by Google, which ensures the most reliable information about the best use for GA (Google Analytics) and GWO (Google Website Optimizer).

Today Google published in the official Google Analytics blog news about the next Seminars for Success that will be run in Melbourne, Phoenix and Toronto.
For more information access Analytics - Blog Post.

Swine Influenza 

The next is information received from the Macquarie University Staff Health.

Swine Influenza is a highly contagious acute respiratory disease of pigs, caused by one of several swine influenza A viruses. This strain of influenza virus is unique because it is a combination of swine, bird, and human influenza viruses and is directly transmitted from pigs to humans.

The virus is transmitted in a similar way as seasonal influenza is transmitted - that is through direct close contact with infected animals and people. For people in close contact with pigs, the recommendations to avoid infection are the same as for regular seasonal influenza - frequent hand washing, getting an annual flu shot, covering coughs and sneezes, and staying home when ill. Once contracted, the virus is spread by coughing and sneezing of infected people. It is not passed on by eating pork meat.

Human cases of swine influenza A (H1N1) virus infection have been identified in Mexico, the United States of America, Canada and New Zealand. There are reports that the virus has also been detected in the United Kingdom, Israel and France. At this stage no cases have been recorded in Australia.

The symptoms of swine flu are similar to seasonal influenza, with

infected individuals reporting flu-like symptoms of fever, aches and pains, sore throats, coughing and trouble breathing. Some people have also reported diarrhoea and vomiting.

There is no vaccine for Swine Influenza and treatment is the same as that of Seasonal Influenza.

At the moment, there are no restrictions on traveling to these

countries; however you may be asked questions related to your health status at border and immigration control in a number of countries, including entering Australia.

If you are planning travel to these areas, the following recommendations will help you to reduce your risk of infection.

1. Consider delaying your travel in areas of high infection.

2. Monitor the International Situation

3. Prepare for your trip before you leave

a. Make sure all your vaccinations are up to date, including seasonal

influenza vaccine if available.

b. Identify the health-care resources in the area(s) you will be

visiting.

4. If you are visiting an area affected by swine Influenza -

a. You are advised to reconsider travelling in areas affected by swine

influenza.

b. Pay attention to announcements from the local government.

c. Follow local public health guidelines, including any movement

restrictions and prevention recommendations.

5. Practice infection control measures to help stop the spread of

influenza -

a. Wash your hands often with soap and water. This removes germs from your skin and helps prevent diseases from spreading.

b. Use water less alcohol-based hand gels (containing at least 60% alcohol) when soap is not available and hands are not visibly dirty.

c. Cover your mouth and nose with a tissue when you cough or sneeze and put your used tissue in a wastebasket.

d. If you don't have a tissue, cough or sneeze into your upper sleeve, not your hands. Do not spit.

e. Wash your hands after coughing or sneezing, using soap and water or an alcohol-based hand gel.

coding errors

interesting article from ZDNet

Top 25 'most dangerous' coding errors revealed

By Tom Espiner, ZDNet UK
Wednesday, January 14, 2009 10:18 AM

Security experts from U.S. government agencies, multinational companies and academia have released a list of what they consider to be the 25 most critical errors made while coding software.

Participants from more than 30 organizations worked together to agree on the 25 "most dangerous" errors, the SANS Institute said in a statement on Monday. They included experts from the U.S. National Security Agency, the U.S. Computer Emergency Response Team (US-Cert), Mitre and the Sans Institute, as well as from Microsoft, Apple and Oracle.

The list was released so programmers can check their code for the most common errors that produce security vulnerabilities.

"[The list] is going to change the way organizations buy software, right away," Alan Paller, director of the Sans Institute, told ZDNet Asia sister's site ZDNet UK.

The top-two coding errors were improper input validation and improper encoding or escaping of output, according to Steven Christey of Mitre, who said those particular errors "earned the top rating for good reason".

"In 2008, hundreds of thousands of innocent, and generally trusted, Web pages were modified to serve malware by automated programs that burrowed into databases using SQL injection," Christey said in a statement. "The attack worked because countless programmers made the exact same [input validation and improper output encoding] mistakes in their software."

The full list of coding errors, and information on how to fix them, is available from the Sans Institute Web site.