Search Mania - SEO India » Web Analytics

How your Analytic Tool is calculating conversions for you? Is this what you are looking for?

admin — Fri, 08 Jul 2011 03:32:34 +0000

Well it was a very good discussion with Angie one of my client provides Hybrid Analytics solutions to their end client. As an Analytic consultant for them each time I have to be well prepared for various questions. But the most common question is of CONVERSION.

Its easy to explain end client, but it’s tough to explain Angie J. Angie this is something specially I am writing for you J.

Conversion Rate is a percentage that is defined as a Outcomes divided by the Unique Visitors (or Visits).

Conversion Rate = Outcomes/ Unique Visitors or Visits

Unique Visitor —In Real Time Tracking Unique Visitors = Unique Browsers who visits your website.
Visits — It’s a session or an Interaction between Browser and a User.

Each unique visitor might visit your website multiple times (i.e. Visits).

So here Angie I am coming to your questionJ, Conversion completely depends on the business mind set.

If we choose Visits as Denominator then we are assuming that every Visit to our website is a chance to get someone to place an order and get someone converted.
“To check this simple thing is to see the transactions if we have more then 80% transactions where minimum 2 products get purchased”, In this case we can think to keep visits as denominator.

If we choose unique visitors as a denominator then we have a mindset that it is okie for a person to visit our website multiple times before making a purchase. I feel this is a common user buying behavior.

Choosing the Denominator decides which business mental model is right for your company.

Angie you guys are using XiTi, and luckily GA and Omniture use visits by default. I think its a sufficient explanation for client to move to GA.

Google’s Data Viz Challenge

admin — Wed, 09 Mar 2011 02:52:39 +0000

If you’re reading this blog, chances are very high that you value data, and chances are also high that you appreciate the presentation of data. Going beyond a spreadsheet of rows and columns and creating a visualization is not only pleasing to the eye, but it can also help put meaning and context to the data and help surface important meanings. As practical as rows and columns of numbers are, sometimes a lot more can be divined a lot faster from a simple pie chart. Or a bar graph. Or an animated motion chart

Data visualization is becoming an art and a discipline. There are blogs and books devoted to it. And we’re obviously believers in visualizing data, and so is Google. That’s why we’re giving a shout out to another Google initiative, the Data Viz Challenge.

Google worked with a website called WhatWePayFor.com that shows the entire federal budget for the past several years, and breaks down spend by program, such as Social Security, national defense, transportation, medicare, etc., and how much is spent on each. It also allows you to enter an income amount and shows you how much of your own taxes goes to each program. Great data to make into a visualization.

WhatWePayFor has made their data available via an API to contestants who want to take a crack at visualizing this data, and Google is offering a $5,000 prize to the best visualization, as decided on by a panel of judges, as well as other prizes for cool entries. Deadline for entry is March 27, so get cracking – we want a Google Analytics data head to win this thing.

Posted by Jeff Gillis, Google Analytics Team

Evolution of Analytics Benchmarking Report

admin — Wed, 09 Mar 2011 02:52:38 +0000

This week, we are beginning a new way of providing benchmarking data to Google Analytics users. For almost three years, Google Analytics has provided a Benchmarking report for users who opt in for anonymous data sharing. In a few days, however, we will be removing the Benchmarking report from the Google Analytics interface, and replacing it with an expanded report that will be emailed directly to you.

In the coming few weeks, we’ll be delivering the new benchmarking report to all account administrators for accounts that are opted-in to anonymous data sharing. The report will expand on the type of data delivered to include broader trends, such as geographic or traffic source differences in visitor engagement. If you are interested in receiving the new benchmarking report, you can opt-in to anonymous data sharing.

Sign into your Google Analytics account
Select the account you want to opt-in from the account list
Select Edit account settings
Check the box next to Anonymously with Google and others

If you want one last look at the current reports make sure you visit them in the next few days. We’re looking forward to your feedback on the new format of the benchmarking report. Look out for it in the coming weeks.

Posted by Phil Mui, Google Analytics Team

On Social Media, Most People Don’t Want to Be Heard

admin — Wed, 09 Mar 2011 02:52:28 +0000

Seven ways to encourage social media contributions.

Client Side Authorization in the API

admin — Sun, 06 Mar 2011 01:46:42 +0000

This post is inspired by Henrik who posted a comment on last week’s Mastering Unique Visitor blog post. His question was, “Most API users would not create web apps but rather easily access their data without account authentication. Is this possible? Could you describe it?”

Great question Henrik! While you do have to authenticate to the Google Analytics Data Export API in order to access data, your application doesn’t have to re-authenticate every time. In this post we show you an easy way to re-use tokens and give you a Python class to simplify the process.

(Note: we recommend you follow the actual sample code to see how all the pieces described below work together.)

Background
Just like you have to log in to view Google Analytics data, you also have to grant an application access to your Analytics data when you use the the API. This is called authorization and is done through the Google Accounts API.

Different Authorization Protocols
When you log into the Analytics interface, your login credentials are protected from being exposed. In the same way, you use the Google Accounts API to protect credentials by requesting an authorization token in place of actual user names and passwords. That authorization token is used in the header of each Google Analytics API request.

There are a two authorization routines that applications can choose in order to obtain this token:

Client Login – a legacy, Google proprietary, authorization routine. The user of your application must supply their user name and password in your application. Your application communicates to Analytics on the user’s behalf and retrieves an authentication token. This token only lasts for 14 days. The issue with this method is that if the token is stolen, others can use it and the user has no way to revoke it.

OAuth For Installed Apps – is Google-supported open standard. Client apps must send users to a web page where the user logs in and grants account access to the application. The web page presents the user with a verification code which they must input back into the application. The application can exchange this verification code for a long-lived token. The long-lived token lasts forever and can be revoked by the user through the Google Accounts interface. This routine is more secure because a user can revoke the token and prevent an application from accessing their data at any time.

Obviously OAuth For Installed Apps is a better way to generate authorization tokens.

Token Management
Because authorization tokens are valid for multiple requests, applications should reuse them until they become invalid. For a client-side app, this usually means saving the token to disk. Here’s the logic to handle this in python:

def GetAuthToken(self):
if self.auth_token:
return self.auth_token

self.auth_token =
self.auth_routine_util.LoadAuthToken(self.token_obj_name)

if not self.auth_token:
self.auth_token = self.RequestAuthToken()

self.auth_routine_util.SaveAuthToken(self.auth_token)
return self.auth_token

Here the code tries to load a token from disk. If it exists, the token is set in the client object that makes requests to Google Analytics. If the token does not exist, the code tries to obtain it from the Google Accounts API, then save it to disk…all pretty easy.

Retrieving a New OAuth Token

To get a new OAuth token, the code uses helper methods in the Python Client Library. The my_client parameter is a reference to the gdata.analytics.client.AnalyticsClient object provided by the Google Data Python Client Library. It handles all the logic to make requests to the Google Analytics API.

First, the my_client object is used retrieve the URL to the OAuth authorization end point. Next it retrieves a request_token from the Google Accounts API and use that token to generate a URL for the user to go to.

The URL is printed to the screen and the code tries to pop open a browser and take the user directly there. The user will be prompted to login and grant access to the application. Once complete, the web page gives the user a verification code.

The code prompts the user for the verification code, and once inputted, the application uses it to get a long-lived access token. This access token will be valid until the user revokes the token.

Here’s the sample code:

def GetAuthToken(self, my_client):
url = (‘%s?xoauth_displayname=%s’ %
(gdata.gauth.REQUEST_TOKEN_URL, self.my_client.source))

request_token = self.my_client.GetOAuthToken(
OAuthRoutine.OAUTH_SCOPES,
next=’oob’,
consumer_key=’anonymous’,
consumer_secret=’anonymous’,
url=url)

verify_url = request_token.generate_authorization_url(
google_apps_domain=’default’)

print ‘Please log in and/or grant access at: %s\n’ % verify_url
webbrowser.open(str(verify_url))

request_token.verifier =
raw_input(‘Please enter the verification code ‘
‘on the success page: ‘)

try:
return self.my_client.GetAccessToken(request_token)

except gdata.client.RequestError, err:
raise AuthError(msg=’Error upgrading token: %s’ % err)

Once we have the long-lived token, it’s returned and the GetAuthToken method above saves it to disk.

Making Google Analytics API Requests

To use the token retrieved above, we simply set it in the gdata.analytics.client.AnalyticsClient object:

try:
my_client.auth_token = my_auth.GetAuthToken()

except auth.AuthError, error:
print error.msg
sys.exit(1)

At this point an application can use the client object to retrieve data from the Google Analytics API. Because a user can revoke a token from the Google Accounts API and the code loads the token from disk, there can be a case where the token on the disk is invalid. In this case, the Google Analytics API returns a 401 status code and the client library raises a gdata.client.Unauthorized exception. If this happens, we need to catch the exception, delete the saved token and prompt the user to get a new token.

try:
feed = my_client.GetDataFeed(data_query)

except gdata.client.Unauthorized, error:
print ‘%s\nDeleting token file.’ % error
my_auth.DeleteTokenFile()
sys.exit(1)

So there you have it, a quick overview of client side authorization with the Google Analytics API. As we mentioned above, you can view and use the full sample code.

Submit your own questions
We’re thrilled to get feedback from our developers. You guys rock! If you have a question about our API, like Henrik, please leave it in our comments. We’ll go through them and try to highlight the code solutions.

Posted by Nick Mihailovski, Google Analytics API Team

Defining Success

admin — Fri, 04 Mar 2011 14:57:48 +0000

You cannot be successful in a project unless you have defined success. But who is allowed to declare success and who has the authority to pull the plug?

Taking Control of Piracy

admin — Fri, 04 Mar 2011 13:15:00 +0000

How do we protect against piracy, and how do we react to piracy? Start by knowing the terminology.

Adding Customization to Actions in YWA

admin — Wed, 02 Mar 2011 16:18:44 +0000

The following post is by Yahoo!’s Tim Hampshire, he is a YWA Account Manager and Support Specialist.

Actions are a powerful feature of YWA that allow you to track conversion events that take place on your site. Currently YWA allows you create up to 50 of these custom actions which you can quickly run out of if you do not define them with care. In this post we will demonstrate how to use Custom Fields to store additional information about your actions in order to avoid overusing the limited number of actions available in YWA.

How Not To Use Actions in YWA

Let’s suppose we are working on setting up YWA on a cooking site where the users can view flash video presentations for each of the recipes on the site. For the reporting, we are interested in seeing how often each one of these videos are viewed. One way of accomplishing this would be to define an action for each individual video:

Action 11: “apple pie desert recipe video view”
Action 12: “strawberry pie desert recipe video view”
Action 13: “custard pie desert recipe video view”
Action 14: “blueberry pie desert recipe video view”
Action 15: “raspberry pie desert recipe video view”

The number of actions used could also get compounded by cycling through the various forms of each recipe:

Action 16: “apple flan desert recipe video view”
Action 17: “strawberry flan desert recipe video view”
Action 18: “custard flan desert recipe video view”
Action 19: “blueberry flan desert recipe video view”
Action 20: “raspberry flan desert recipe video view”

Using this method of defining actions we would very quickly find ourselves running into YWA’s limit of 50 custom actions. We also might find that adding extra categories to these actions would be laborious and potentially error prone.

The Correct Usage of Actions in YWA

When creating actions in YWA, you will want to define them as broadly as possible so that they can be used on multiple locations of your site. We can then use Custom Fields to capture detailed information about the specifics of the action performed. Using Custom Fields with our actions in this way will add the detailed classification and grouping information we are looking for when running granular reports in YWA.

Continuing the cooking site example above, we could define one action to register the viewing of a recipe video, we’ll call it “recipe video view”:

Action Naming

Then we will want associate three Custom Fields with our action that will capture the details about the cooking video’s “course”, “form” and “flavour”:

CF Naming

When setting up these Custom Fields (CFs) we must be sure to use the correct type of association or scope for the CF. In this example we will want the CFs to be associated with the action, and so we will use ‘action scope’ so that the CF will be correctly associated with the action. We will also choose the ‘string’ types as we will want to store alphanumeric strings category groupings rather than just numeric.

Setting up the Tracking Code

Now that our action and Custom fields are setup, we will have to modify our tracking code in order to capture the data. Let’s say that we have a recipe for Apple Pie on our cooking site. Every time the video for this recipe is viewed we will want to execute the following tracking code:

YWATracker = YWA.getTracker(“10001234567890123”);
YWATracker.setCF( 17 , "desert");
YWATracker.setCF( 28 , "pie");
YWATracker.setCF( 29 , "apple”);
YWATracker.setAction("12");
YWATracker.submit_action();

Every time this tracking code is executed it will register a “recipe video view” action and associate “desert”, “pie” and “apple” with the action through the corresponding Custom Fields.

Running the Reports

We can now generate a custom report using action based Custom Field or Custom Fields as groups and the action of viewing the recipe action as the metric.

Custom Report Wizard with Action Scope CFs and Action 12 Metric

If we are interested in just a single category type of one of our chosen classification CFs we can add a cross reference filter such as ‘Form’ equals ‘pie’ , where form is the action scope CF we labeled as form, to represent the sub type of food, and in this example ‘pie’ to filter for pies only.

Here is an example of such a report.

Custom Report: Video Views for Pies

In this report we are actually using several custom fields as group classifications and filtering for the form is ‘pie’ only. Alternatively we could choose to rearrange the group order in the custom report wizard to list flavours first such as:

Custom Report: Video Views for Pie Flavours

Filtering on Custom Fields used as categories

Once you have setup your custom fields CFs to customize your actions, you can then choose to filter on these categorizations added to some actionable user event. These CF filters are selected in the add filter section from the drop down list custom field, here is where these filters are found,

Custom Field Filters

Here is an example of these filters where we are ORing together strawberry and raspberry flavour filters and ANDing this with pie form to list raspberry or strawberry pie recipe video view numbers.

Custom Report: video views for strawberry or raspberry pies

Using Custom Fields to Add Timing Classification.

You can also use CFs for section of day reporting if wanted – down to the minute if needed – or even second.

This could be useful for example to tie in some radio or television advert specific time of day with user responses from the internet to the associated television or radio marketing campaign.

To do this you just need to set another CF to the time of day in sections of time of day rounded to sections of time your are interested in, for example 15 minutes or 30 minute sections.

So if you would want to know which quarter of an hour the action occurred in, then you can round the time down to quarter of an hour intervals and pass this to a CF. If this was to be used with the above example of an action of selecting a video view of a recipe, then again action scope and either string or numeric type would be chosen.

In this example we have chosen to use a string type as we want to store the time as an easily readable time in a group, rather than as a numeric 0,1,2,3,4…96 representing which 15 minute time slot of the 24 hours.

The tracking code for recipe video view with timing added for time of day in 15 minute steps could then be coded as (assuming that string type action scope CF 20 is used for timing and function (not listed here) exists called timeofday_in_15minutes() ):

function timeofday_in_15minutes() {
...
code to generate required timing (e.g. '08:00' or '09:15' or '21:45')
...
}

And then tracking code with extra timing information coded in such as:

var timing_info = timeofday_in_15minutes() ;
// sets timing_info to strings such as ’08:45’
YWATracker = YWA.getTracker(“10001234567890123”);
YWATracker.setCF( 17 , "desert");
YWATracker.setCF( 18 , "pie");
YWATracker.setCF( 19 , "apple”);
YWATracker.setCF( 20 , timing_info );
YWATracker.setAction("12");
YWATracker.submit_action();

This type of timing classification using Custom Fields can also be useful for online streaming media analtyics.

In this use usage we can periodically send tracking beacons to say that streaming media is continuing to be played at regular intervals and store this timing information in an action scope custom field along with an action to denote sub-section has been played. I will be producing a 3rd part to the YWA online video analytics posts that will demonstrate this usage mode (code link here).

Conclusion

I hope in this article we have shown how Custom Fields can be used to avoid falling in the trap of using more and more custom actions to label the conversion events that happen on your site. Besides using up the limited number of actions available in YWA, it also makes it very hard to create useful reports as each related action would need to listed in the report’s column metric. Additionally by associating Custom Fields with actions through the use of the ‘action scope’ we are able to add detailed classification and granularity that simplify and enhance the readability of our site’s reports.

How to use Custom fields with actions so we don’t use an excessive number of actions for some user actionable event type.

Instead of using just more and more actions from the limited set of 50 default actions to classify some analytics event, we can use custom fields CFs as well with the actions to help classify and group the particular user action.
Once we choose to have extra Custom Field CF parameters stored along with each occurrence of an action, we then can see more granularity, we can see categories and subcategories of user activity within a type of user action. When choosing which particular custom fields to use we must be sure to use the correct type of association or scope for the CF. In this example we will want the CFs to be associated with the action, and so we will use ‘Action scope’ so that the CF will be correctly associated with the action.

Q&A With YWA Product Manager Logan Lee

admin — Wed, 02 Mar 2011 16:18:41 +0000

We recently tracked down YWA Product Manager Logan Lee to get his thoughts on the current state and future of YWA, he graciously answered our questions and allowed us to share them here.

How did you come to be the Product Manager for Yahoo! Web Analytics?

I’ve worked across Yahoo!’s data solutions during the past 3 years, covering data pipelines, warehousing, targeting and content recommendations, as well as analytical business intelligence. This has given me a broad view into the markets and capabilities that drive the needs of our advertising customers and publishing partners. Yahoo! Web Analytics is a natural fit in a number of those cases, leading me early this year to take on responsibility for guiding product strategy.

What do you think of Yahoo! Web Analytics?

We are fortunate to have a product with the right balance between structured insights and flexible but approachable data architecture that solves varied and unique needs. We are able to deliver e-commerce analytics that informs thousands of merchants to get the most out of their Yahoo! Small Business virtual storefronts while at the same time supporting Yahoo! search and display advertisers to understand how to improve their ROI through sophisticated cross channel marketing.

What do you hope to achieve with Yahoo! Web Analytics?

Measured success. I hope to achieve an increased rate of growth in the revenue our Small Business Merchant services demonstrate for those who take advantage of the turn key analytics. I hope to achieve a higher rate of ROI for Yahoo! advertisers who can take advantage of our free solution to understand the most effective approach to full funnel, cross media and website engagement. And I hope to deliver increases in engagement and profitability for our publishing partners by helping them understand and focus their most engaging content and most important audiences advertisers want to reach.

Where do you expect Yahoo! Web Analytics to be in 3 years?

I expect Yahoo! Web Analytics to be at the center of educating our customers how to get the most value out of the leading advertising solutions from Yahoo! that span search and display without having to pay hundreds of thousands of dollars from 3rd party solutions. I equally expect it to be central to the engagement and monetization of our offerings to publishing partners when they participate in the Yahoo! Publisher Network. Lastly, I expect it to be central to how both advertisers and publishers understand and engage their audiences across the Yahoo! Network and beyond on our ad exchanges.

Why not make Yahoo! Web Analytics freely available like Google Analytics? What’s the strategy behind that decision?

I’m constantly impressed at Google’s commitment to deliver on the promise of universal accessibility of web and campaign analytics to businesses large and small. Serving such a long tail of search marketers, I’m sure it has been incredibly insightful in improving the search experience for users and the search marketing experience for advertisers by making it available to everyone. Our goals for Yahoo! Web Analytics are a little different. As a company Yahoo! does a lot of our business with large advertisers and publishers. Together with our services for small businesses, these are the core vertical and horizontal segments we try to focus on to add unique value instead of simply competing directly with Google to offer the same general feature set to the long tail.

How do you make decisions on product direction with Yahoo! Web Analytics?

I look for the highest value capabilities I think large percentages of Yahoo! customers can take advantage of and that fit with the services and solutions Yahoo! offers to its customers and partners. The ideal situation in when we find opportunities even the most diverse ranges of customers can all appreciate but when there are compelling solutions we can uniquely provide in specific parts of the world or to specific markets, we are prepared to focus deeper as needed.

How important is Yahoo! Web Analytics to Yahoo!?

Yahoo! Web Analytics is an ongoing area of investment for Yahoo!. Unlike other enterprise analytics solutions from 3rd party vendors, we are not in the business of selling analytics, so the product’s value is only as strong as our ability to help deliver a solution that adds value to the adverting and publishing solutions Yahoo! is uniquely capable of providing.

How will the Microsoft transition affect Yahoo! Web Analytics?

The Microsoft transition is a large effort for Yahoo! with many moving parts. Fortunately, Yahoo! Web Analytics is well positioned to continue to support Search Marketers as integration with Microsoft adCenter has been in place for some time. We will continue to ensure the campaigns you book in Microsoft are accessible to illustrating how cross media campaigns and full funnel analytics drives engagement and marketing ROI. At the same time, the audience insights Yahoo! understands based on what Yahoo! users search for and how that connects to the rest of our consumer offering remains a unique source for Yahoo! Web Analytics to highlight.

We’ve just released Version 9.6 of Yahoo! Web Analytics – what do you think are the most significant changes?

The most significant change is the introduction of the assist metric. We see many examples in the industry of convergence on campaign attribution going beyond first/last click. The assist metric reveals which campaigns (of any type) most often indirectly contribute to the conversions you value in order to better evaluate marketing opportunities. We feel that a combination of tracking campaigns by any media source combine with assists will tell a more complete story about how your marketing is working together and where to focus your money to drive the highest ROI.

What about future development – are there any plans you can share?

As a matter of policy, we won’t be commenting externally on future development plans. But we are interested in hearing more from users of YWA about what they’d like to see in the product down the road.

Data Hygiene and Reporting for Insights

admin — Wed, 02 Mar 2011 16:18:41 +0000

The following is a guest post from YWA Client Services Engineer Carl Rowlands.

Yahoo! Web Analytics does have the ability to collect a remarkable amount of data, and a massive number of values in relation to your website. It imposes far less restrictions than many other similar web analytics solutions. Not only this, but the data collected historically is available for reporting today. YWA gives access to an unrestricted calendar, capable of reporting on any reasonable time period, from whenever a given project started tracking.

However, a large amount of unique values may not actually help YWA users find the insights, identify the segments and analyze the traffic patterns, in order to improve the scope and optimize the reach of digital marketing or publishing. Adding a large number of unique values may only confuse and obscure identification of the characteristics of a user base, how they interact with the content and how successfully marketing processes are generating conversions and revenue.

Some users of YWA may find that the default values for Page Title don’t provide enough detail, and that the ‘setDocumentGroup’ and ‘setDocumentName’ variables can be used in order to further categorize and order the content.

YWATracker.setDocumentGroup(“Pictures”);

YWATracker.setDocumentName(“Pictures of Lake Balaton”);

Similarly, there may also a point where the default URLs, as collected by YWA, are providing too much data, which is ineffective, and doesn’t add value to reports. Both report users and YWA have a role to play in data hygiene, and ensuring that the power of Yahoo! Web Analytics is available to users and is based on relevant data.

An example of user-focused data hygiene may be the use of the ‘setUrl’ variable, to manage what may be a an unwieldy and complex URL, including session parameters and other chunks of data which would be useless from an insights perspective.

For example, a URL could be collected by default as:

http://mysite.com?cmp=eread&sid=47633FSR&id=37373625&gid=eururuhsksk

Using setUrl this can be truncated to the most useful parts of the URL:

YWATracker.setUrl(“http://mysite.com?cmp=eread“);

Another example of user-based data hygiene might be managing the use of custom fields, extracting the required values from the URL or the web page itself, so that only the most relevant segments of these variables are stored within the YWA database.

YWA’s role in this process of data hygiene is twofold. YWA offers the chance to use string- or number-type custom fields, and pre-defined variables, to avoid flooding your reports with unique yet worthless strings. We have also defined the scope in which this data cleansing can occur, in developing the ‘Limited String Processor,’ which protects accounts from being flooded by unique values, and ensures the fast and reliable operation of our system. The LSP actively monitors the number of daily unique strings in the user’s YWA project. If the limits are not reached then users do not notice a difference. But if the limits are exceeded, users may see ‘{Deleted}’ listed in their report groupings, aggregating the affected values. This can be regarded as a call to action, to start cleaning the data being passed to YWA.

We also offer the ability to use URL Rewriting, where users can specify which URL parameters to drop. String patterns in a URL can therefore be easily excluded from the YWA database.

Giving some attention to these issues of data hygiene – and then making the necessary adjustments to YWA settings and data collection – can often be seen as a necessary part of identifying and demarcating the real insights that can be extracted from the use of web analytics. YWA is a tool which can be used to discover valuable insights. As we all know, it generally needs valuable data in order to achieve this.

In Summary: The YWA Limited String Processor

The Page URL field has a limit of 100,000 (one hundred thousand) unique strings in one day.
String-based custom fields have an extended limit of 500,000 (five hundred thousand) unique strings in one day.
Member ID, Document Name (Page Title), Product ID, Search Phrases, Order ID, Search Listings, Referrer Domain have an extended limit of 1,000,000 (one million) unique strings per day.