Analytics Report

section 1= Google Analytics.

A summary of implementation both client and server side analytic options: There are two different kind of setup we have done to set up client and server side analytics. Client side we have to set up an admin account and integrate our app. Whereas for the server side the standard code we have to add in our code.

Google Analytics: Client-side implementation:

The following steps shows the step by step client side analytics setup:

Step 1: Sign into the analytics account using the url: analytics.google.com

Step 2 : Being an admin, create an account.

Step 3: Account details setup by filling “account name”

Step 4: Choose the analytics for web application.

Step 5: Fill in the website name and for the website url- inserted our facebook application URL.

Step 6: After the setup, website tracking information can be seen in tracking code under admin, like tracking id and the piece of code should be added in all our .jsp pages. The tracking id is the one which links application to analytics account. Step 7: After connection, we will be able to see our application under an analytics a ccount.

Google Analytics: Server-side implementation: Create src/main/java/com/google/appengine/analytics/tracking/ in the project and now create java class file with name GoogleAnalyticsTracking copy and paste the code present in the link below. https://github.com/GoogleCloudPlatform/appengine-googleanalytics-java/blob/master/src/main/java/com/google/appengine/analytics/tracking/GoogleAnalyticsTracking.java

Metric 1: Realtime->content

1.1.a: metric 1- provide a graphs/plots/visualizations:

1.1.b: Interpret the metric 1's trends:

This metric provides below information

• Number of active users at the point of time - In our case, there were 6 active users using our application.
• Number of page views per minute in the form of bar chart - when multiple users using it shows at that minute how many pages have been viewed.
• Number of page views per second in the form of bar chart.
• Name of the active pages with page title and count of pageviews for each page at the point of time- In our case, we can know friends tweet page (means 2 users are viewing friends tweets ) and 1 user is seeing top tweets.
• Name of the active pages with their page title with number of pageviews for each page in the last 30 mins from that point of time.

The above information provides a number of active users using our application along with the active pages with a number of hits. It also provides information on active pages on our facebook app for last 30 mins with their page titles and number of hits per each page.

All this information is useful for a developer to understand what are the pages that are being viewed most and at what time.

1.1.c: limitations of metric

When there are many active users and hitting multiple pages tracking information is hard as it keeps on updating. Real time is limited to only page view options.

Metric 2: Audience->behaviour-> new vs returning

1.2.a: metric 2- provide a graphs/plots/visualizations:

Depicts Overall view of “Audience”

Depicts the New vs Returning user behaviour graph for day and table

1.2.b: interpret the metric 2's trends:

This metric provides comparison between new user and returning user. Metrics depict the following information.

• It provides a number of users in day- In our case, the more number of users using the application in the later part of day(around night time).
• 33.3% of returned users have been using application and the other 70% are new users.
• Comparison between new users and returning users for the below metrics.
  1. Sessions: Total number of Sessions within the date range. A session is the period time a user is actively engaged with your website, app, etc. All usage data (Screen Views, Events, Ecommerce, etc.) is associated with a session.
  2. Bounce Rate: The percentage of single-page sessions in which there was no interaction with the page. A bounced session has a duration of 0 seconds.
  3. Page/Session: Pages/Session (Average Page Depth) is the average number of pages viewed during a session. Repeated views of a single page are counted.
  4. Average Session Duration: The average length of the session.
  5. Goal Conversion Rate: The sum of all individual goal conversion rates.
  6. Goal Completions: The sum of all individual goal conversion rates.
  7. Goal Value: Total Goal Value is the total value produced by goal conversions on your site. This value is calculated by multiplying the number of goal conversions by the value that you assigned to each goal.

The above information is used in our facebook app to understand the new user and returning user by using the metrics provided. This metric is generally helpful to understand new visitors and returning visitors for their site by using the above values. It gives the speculation of how users use the application timely, and in which time more number traffics can be occured.

1.2.c: limitations of metric 2

At a particular point of time we cannot specifically find the number of new users as the returning users count is already added to the new user count.

Metric 3 : Audience-> behaviour -> engagement

1.3.a: metric 3- provide a graphs/plots/visualizations:

1.3.b: Interpret the metric 3's trends:

The above metric depicts how long the user is using our application. The bar graph above provides the below information.

• For each length of a session in seconds, a session lasts as long as there is continued activity, it gives the sessions and pageviews. Where session is the total number of Sessions within the date range. A session is the period time a user is actively engaged with our web app. All usage data (Screen Views, Events, Ecommerce, etc.) is associated with a session.
• Pageviews is the total number of pages viewed. Repeated views of a single page are counted. In our case, there are a total 86 page views from all users and 20% of page views are from returning users.

This metric is mainly useful for understanding marketing strategy and application development features. It gives a number of seconds the session lasts. With the help of this metric it helps developers to understand and make changes to application features/pages to retain and engage users for more time in the website.

1.3.c: limitations of metric 3:

This metric gives an idea on the number of sessions in the duration but it did not specifically mention on what page did the user spend time on. Specific information in timely manners can be viewed.

section 2= Facebook Analytics

Facebook developers account has an easy step of analytics and the option directly can be viewed in application developer account. Our app page-> View Analytics button on the top right corner.

Overview of our application can be seen like this.

Metric 1- Growth Metrics-> Active Users : Last 24 hours->Unique User

2.1.a: metric 1- provide a graphs/plots/visualizations:

Unique user--Hourly

2.1.b: Interpret the metric 1's trends:

The view of this chart shows the number of unique users, also known as active users, who are using our facebook application. This metric helps us to understand at what time period in a day/week/month are people using our application at maximum.

2.1.c: limitations of metric 1:

With this metric we can get knowledge about the time range unique users are using this app the most. But at the time we cannot predict that there would be a high number of generic users at that point in the future.

Metric 2- engagement metric: Active users by hour

2.2.a: metric 2- provide a graphs/plots/visualizations:

2.2.b: Interpret the metric 2's trends:

Each cell shows the number of people that used our application by hour on a particular day. All data is shown in the time zone specified in our Settings. The cell is colored in varied shades depending upon the number of users at that particular time. In our case, 12am depicts the most active hour of our application. This metric is useful to know the number of people who use our application on a particular day in an hourly manner. The traffic can be controlled by seeing the timely manner management.

2.2.c: limitations of metric 2:

With this metric we can get a knowledge about the time range active users are using this app the most. But at the time we cannot predict that there would be a high number of generic users at that point in the future. It doesn't specify the location at which hours more number of users are using.

Metric 3- Sessions->Metric : Average Session Length:

2.3.a: metric 3- provide a graphs/plots/visualizations:

2.3.b: Interpret the metric 3's trends:

Shows the average amount of time unique users spend on our application per session. Session length is calculated by taking the time of the last event logged in a session and subtracting the time of the first event logged in the session. In our case, the highest average session lasts 45.8minutes at 4pm. This metric is useful to understand the time that users are spending on our app each time they visit our app. It helps us to know how much time users are spending time on being on our application. Helps to enhance our application with adding other features to attract users to use our application.

2.3.c: limitations of metric 3:

This metric shows the average time spent on the product but it's not specific to which page or feature of our application. The in-depth feature to know session has average users to login.

section 3: compare Google & Facebook analytics

By the metrics both Google Analytics and Facebook Analytics offers also in terms of view and its dimensions we think Google Analytics has a much broader spectrum of customizations with full-flavoured metrics. For enhanced checking like comparing returning vs new user i was able to customize the comparison model of graph plot with putting all my own conditions which i needed to know for my application, so google analytics allows custom models. Whereas with Facebook Analytics it gives us the basic metric attributes, but it doesn’t let us expand a lot of that nor customize the model based on our customer dimension. It’s not really something that can be used as a stand alone tool to analyze our application. Well for basic application Facebook Analytics is best to use because Google analytics are free to use only for limited time.

Favourite metric in Google Analytics : Realtime-> Locations

This metric gives the cities of users, derived from IP addresses. Additionally we can also know the users Geo location based on the countries of website users, the region of users and Latitude, Longitude. We actually knew which part of cities interested in using our application. Well in future this can be used to enhance the interest of people's mindsets of cities to grab more number of users to hit our application.

Favourite metric in Facebook Analytics : Active Users-> Average Session Length

Average Session Length: Shows the average amount of time unique users spend on our application per session. The metric can be viewed for Hour, Monthly and Daily. However we liked seeing the session length of hours as in the below picture. So for our application we could easily know how long the users used our application. Based on the session length we can speculate the information like to add extra feature to have users stay longer so the longer session can be noted for future analytics.