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.