Tuesday, June 16, 2009

Web Analytics Implementation Process

Web Analytics in an organization should be just like a development cycle starting from requirement gathering to validation. Below is a visualization of an ideal Web Analytics process. This process is more suited for tech organizations which already have defined KPIs and regular weekly/monthly releases of new features on their website.

1) Requirement Gathering: This is the start of the Web Analytics process and it deals with an Analyst collecting tracking requirements from stakeholders. Similarly this step will also involve review of feature specifications of new items that are part of a release cycle. An example of a new feature can be a new page being added on the website or a new outgoing/external link being added or even an A/B Test.

2) Creating a Tracking plan: Once all the requirements have been gauged, the Analyst will create a Tracking Plan/Analytics plan/Solution Design document to define the variables for Web Analytics vendor tools (custom variables, pagename variables etc) like Omniture SiteCatalyst, WebTrends, Clicktracks or Google Analytics. This is usually an excel document containing a matrix of all the variables and their corresponding values.

3) Development: In this step, the Analyst will usually work along side a developer to get the features implemented on the website. This step also requires the Analyst to assist the developer with any questions she has regarding the Web Analytics code or the Tracking plan. This applies especially to new developers who do not understand the Web Analytics snippet.

4) Data Validation: This step deals with the QA/testing of Web Analytics data that land up in the Web Analytics tool. I have written a comprehensive article detailing the importance of this step as this in itself is a separate process.

5) Reporting/Analysis/Recommendations/Next Steps: After the data is found to be clean, it is the responsibility of the Analyst to report numbers resulting from the feature which went live during the previous release cycle. The Analyst will also provide analysis (explaining the data or conversion etc) and possible recommendations/next steps to improve the website even more.

This, according to me is an ideal end to end process which organizations should be following to manage Web Analytics. It is vital for a big organization to incorporate these steps in their overall plan for Web Analytics to ensure smooth functioning.

Monday, June 1, 2009

My take on 404 Error Page Naming and Analytics

‘404 Error Pages’ are the pages displayed when someone is not able to find a link/URL on a website. There are usually 2 ways by which one can find the 404 page:

1) Typing in the wrong URL: If a visitor has typed a wrong URL, by default he will see a ‘The Page cannot be found’ page in case there is no custom 404 page present in the website. Below is a screenshot of such a page.

In order to fix this, the best practice is to create a custom 404 page which will be shown to visitors who try to access a page which has either been removed or doesn’t exist. This 404 page should contain links to the most important pages of your website and will play an important role in engaging visitors back to your website. You can also create 404 pages which have a funny message. Some examples of such pages can be found here.

2) Deleted or moved links: The same default page mentioned above will appear in case a visitor clicks on a link/page that has either been deleted or moved to a new location.

To fix this, implement 301 redirects which send visitors to the new page which has been moved to a new location.

As far as Web Analytics tracking is concerned, it is pivotal to accurately track how many people are looking at the 404 page and what URLs are they looking for. The method explained below will help you track 404 pages efficiently (Tracking impressions on the 404 page and the incorrect URL) through Omniture and Google Analytics.

1) Adobe Analytics: Capture the incorrect URL (JavaScript function document.location) in the s.pagename variable and append ‘404’ to it as shown below.
s.pageName="404:"+document.location (E.g. If the incorrect URL is http://www.undp.org/ss, then the pagename variable will capture it as ‘404:http://www.undp.org/ss’. This naming structure helps in gauging the amount of traffic going to incorrect pages as well as fixing broken links. Similarly pathing can be performed on the error page to find the flow of traffic to and from this page.
• Another mandatory variable which should be populated on error pages is s.pageType which should be populated as s.pageType="errorPage".
Below is a screenshot of the UNDP 404 page using similar Omniture snippet.

2) Google Analytics: Capture the incorrect URL in the trackPageview function as shown below:
pageTracker._trackPageview("404:" + document.location) (E.g. If the incorrect URL is http://seattleindian.com/seattle/xyz.asp, then the value captured in the ‘utmp’ variable will be ‘404:http://seattleindian.com/seattle/xyz.asp’.
Below is a screenshot of the SeattleIndian 404 page using similar Google Analytics snippet.

Below are some advantages of implementing custom 404 pages in your website:

1) Engaging visitors to pivotal pages of your website: If your 404 error page has links to important pages of your website, users can be sent to important pages of your website thereby increasing user engagement. You should also add a link to the sitemap page and a search box.
2) Leveraging Web Analytics to optimize your website: You can utilize Web Analytics tools by analyzing 404 URLs which users type and fix broken links on your website.
3) Reduces user frustration: Creating a custom 404 page eases user frustration caused due to not being able to find what they were looking for.

Monday, May 25, 2009

Small Change with a Huge Impact

Recently I was involved in changing the layout of a website and measuring the impact of that change. We changed the Top navigation on this website and changed the color of a link to Red/Bold. It was a very minor change with respect to the whole website as the Top navigation menu only contributed to less than 5% of users engaging in the website. We wanted to make this change to enhance the Top navigation and entice more clicks on the edited link (Coupons). P.S. We leveraged Google Analytics to measure this change. Below is a screenshot of the previous Top Navigation menu:

After a week, I pulled the ‘Top Content’ report and filtered on the Top menu Coupons link. I was pleasantly shocked to notice the results. There was a 65% increase in User Engagement (Clicks) on the Top navigation Coupons link clearly due to changing the link color to Red. From the context of the website, this page amounts only to a small proportion of traffic but this change has paved the way for similar changes which can be replicated on others pages in the future. Below is a screenshot of the change we made on the Coupons link:

Immediately after noticing this change I sent a tweet in excitement: ‘Wow! Top menu navigation link text change resulted in over 60% increase in user clicks. Changed the font of the link to Red/Bold #ga #wa’. Surprisingly, I got a response from a Twitter user: ‘So funny. We also changed the nationalgeographic.com top nav to red/bold in Dec 07 for commerce promo. It stuck.’ The user mentioned that Nationalgeographic also made a similar change back on 2007 and they too noticed an increase in clicks on the button. Isn’t it coincidental?

Going forward we plan to replicate the same exercise on the Side menu. We will also be performing AB Tests on the Top navigation menu and compare it with newer menus. P.S. It is always a good practice to add a query string parameter in the URL. E.g. Add ‘menu=top’ (http://www.seattleindian.com/seattle/indian-restaurant-coupons.asp?menu=top) to distinguish this URL as a Top navigation link.

Hope you like this article. Please comment and let me know if you’ve done similar exercises and noticed a considerable impact.

Sunday, May 17, 2009

My take on Social Media Analytics

Social Media is one topic which I haven’t written about in the past. I am still coming to grips with Social Media as there’s so much to learn but am convinced that it is something which just cannot be ignored. I say this because websites like Facebook with 200 Million active users (Source: Facebook), LinkedIn with 39 Million users as of May 2009 (Source: Wikipedia) and Twitter with 7 Million users as of Feb 2009 (Source: Nielsen) are at the peak of their popularity with more users being added by the hour. P.S. Population of United States is 304 Million as of May, 2009. In this article I will write about my experience with Social Media Analytics and the mediums to track it. Twitter will be covered in detail.

Social Media measurement:

1) Twitter Campaign Analytics: It is very easy to measure traffic from Twitter with Campaign Tracking parameters. There is an article which I wrote on Email Marketing which brushed on the concept of Campaign tracking. Here is an example of a Twitter Campaign URL which can be measured in Google Analytics: http://rkapoor.blogspot.com/?utm_source=twitter&utm_medium=googleurlbuilder&utm_campaign=socialmediaarticletweet. This URL was created from the Google Analytics URL Builder. These campaigns can be attributed to Web Analytics metrics like Bounces, Time spent on Site, Visitor Type and Conversion once we start getting traffic from Twitter.

2) Short URL Analytics: There are also various short URL websites which can shorten the campaign URL to be placed on websites like Twitter (Maximum Twitter Tweet length is 140 characters so short URLs are very efficient). One of the websites is Clop.in which offers you an interface where you can easily create campaigns for Google Analytics, Omniture and WebTrends. This tool will allow you to create a custom campaign URL string and will shorten it. I leveraged this tool to shorten my Twitter campaign URL to http://clop.in/PWGCto. Other short URL websites are tinyURL, Cli.gs etc. Some of these websites will also report the total clicks, referrers and location of the users who clicked on the short URL along with measuring metrics on the destination website.

3) Reputation tracking tools: A new variety of tools have appeared which allow companies to analyze what consumers are saying about their brand (Customer Sentiment). I tried my hands on Radian6 and SM2 which offer a great interface built out of data captured from blogs, forums, review websites microblogging and news websites. These results are captured based on the keywords which users or companies search for. SM2 has a great graphical interface whereas Radian6 shows keyword search results via Widgets. For e.g. Microsoft can search for ‘Zune’ and analyze consumer feedback/mood for this product. The possible data points available from this search keyword can be segmentation of Media type with the location, sentiment and engagement. Based on this data, companies could even contact sources/people that have a negative taste about the brand to improve their reputation. Other reputation tracking tools are Buzzlogic and Buzzmetrics.

4) Twitter specific tools: As Twitter is the hottest from of Social Media today, companies are putting in more effort to know about their competition and the most popular trends in real time on Twitter. Some tools which I have used and report data from Twitter are Tweetvolume (Competition comparison tool) and Twitscoop (Current buzz on Twitter). There are some websites like Tweetvalue which even assign a price to your Twitter profile and offer to buy your Twitter account (I haven’t really tried selling it yet).

5) Widget Analytics: Another form of Analytics which comes under the Social Media umbrella is Widget Analytics. Widget is a snippet of code which can be embedded in Web pages and can be used to display Videos, Ads, News, and Weather etc. Widget integration has recently exploded with Social networking sites, blogs, and Ecommerce websites etc. Some metrics which can be measured on Widgets are clicks, impressions, install conversion, widget stickiness, installs by country and time spent on widget etc. Some tools which provide widgets and an interface to measure them are Gigya and Clearspring etc.

Through this article I am able to share my experience with Social Media measurement but there are lots of other tools which I haven’t used or mentioned. Please let me know if I need to add any more tools as many might have been missed. I will be writing more about Social Media in the future.

Sunday, April 26, 2009

Should a Web Analyst have development skills? - Part 2

I wrote an article in 2007 about Web Analysts having development skills and my conclusion was that it would be an add-on to have basic skills. I got a comment from a user who thought that only having analytics skills are suffice and I somewhat still agree with him. I have seen a lot of Web Analysts who are perfect in analyzing data but don’t have development skills. They tend to do very well in their usual job but lack context pertaining to the implementation of code. This article will cover what I’ve learnt about the Web Analytics job market since then and what makes an ideal Web Analyst.

I have been analyzing the Web Analytics job market and have noticed that almost 90% of the listed profiles have a mention of Web languages like HTML, JavaScript or Flash. (P.S. I had predicted such a trend) This wasn’t so common a couple of years back when companies mostly looked for people who are simply ‘Analysts’. In my opinion, it is very important to know how the Web Analytics code works and the technology behind capturing data. My take on the Web Analytics data capture is explained here. In one of my assignments, I was involved in configuring the Web Analytics tracking code to track features which were not possible through the generic snippet. A JavaScript Wrapper had to be created and added in the code. This asset helps a Web Analyst to stand out and is often the path to rise in the organization as a multi-talented contributor. Apart from knowing programming, it is also helpful for a Web Analyst to know basic SQL as most companies have an in-house reporting system which might need to be extracted for analysis.

We can have hours of discussion on whether the above skills are really necessary for a Web Analyst but based on the current market situation, extra skills other than analysis will be more than useful. Below are a few skills which I think will be make a very good Web Analyst in the order of priority:

1) Analytical skills, drawing conclusion from data and offering recommendations to improve the business (Presentation skills and Excel knowledge included)

2) Client interaction and excellent interpersonal skills (Requirement gathering and building relationships)

3) Statistics knowledge (Ensuring whether data is ready for analysis and concepts like Confidence level)

4) Basic Programming skills (Understanding Web Analytics code and ability to enhance it)

5) Basic SQL skills (Ability to pull data from the backend databases if necessary)

I will appreciate if you can share your views in case you agree/disagree with this article.

Thursday, April 2, 2009

My take on Web Analytics Testing/Quality Assurance

When we discuss Web Analytics, we talk about Implementation, Reporting/Analysis and offering recommendations on how to improve a website. QA/Testing is something which is often put in the backburner. Companies focus on the Analysis of data but don’t usually concentrate on the validity of data. This often leads to reimplementation of code and the data being inaccurate. This is not good news for companies tagging their website with Web Analytics code and paying for Implementation and Analysis. This article at a high level explains some of the things which may help improve the Web Analytics QA process of organizations. These are some of the points which can be useful for Web Analysts looking to setup a Web Analytics QA process.

1) Spread the word: Spread awareness about Web Analytics QA benefits to your Manager/Stakeholders specifying how thorough Web Analytics QA can help them save cost in the future. For e.g. you can tell them that proper Web Analytics of the code/data can help companies reduce repetitive fixes/patches of code or resultant skewness of numbers while performing Analysis.
2) Include in release cycles: Try to incorporate Web Analytics QA in the weekly/monthly release cycles by bringing into perspective all stakeholders from QA Analysts, Developers to Program/Project Managers. It might involve lot of patience, persistence and convincing but it is worth the time. Come up with a process document/Flow chart depicting the QA process and share it with the concerned teams.
3) Performing QA/Knowledge Transfer: Once the Web Analytics QA process has been approved, start off by performing QA yourself and transition this responsibility to the resident QA Analysts as a Web Analyst should be involved more with Analysis/client interaction etc. Sharing tutorials about different Web Analytics tools might be helpful to pass on to the QA Analyst.
4) Create a reusable test document: Once the training has been imparted, the QA Analyst or Web Analyst can create a test document to perform Web Analytics testing. The QA document should leverage a Packet Sniffer (explained in my previous article) and should also validate data in the Web Analytics tool. For e.g. the below screenshot makes use of conditional formatting to color incorrect values (not matching requirement) as Red and correct values as green. This is a screenshot taken from a QA document which I created in one of my assignments where we were QA’ing Omniture data. This document helps in validating the code as well as checking the output and should be reusable.

Hope you like this post. Please comment in case you agree/disagree with my analogy about Web Analytics QA process being an integral part of a Web Analytics assignment.

Sunday, March 1, 2009

My take on Email Marketing

Emails have been an integral part of communication since a long time on the Web. It is scary to even think of a world without emails. "Over 50% of Internet users check or send e-mail on a typical day" (Source: http://en.wikipedia.org/wiki/E-mail_marketing). In the world of Web Analytics, emails plays a very important role in advertising, bringing in fresh traffic to a website or enhancing customer relationship. This particular branch of direct Online Marketing/Web Analytics is known as Email marketing.

Just like Affiliate marketing, Contextual marketing, Offline marketing etc, there are huge advantages of leveraging email as a powerful medium for advertising purposes.

Advantages of using Email marketing:

1) Low Cost and Reach: Email campaigns are much cheaper to implement in comparison to Banner campaigns or contextual ads. Its accessibility and reach make it a front runner in inciting traffic and creating awareness about your website.
2) Quick and Easy: Email campaign/newsletter is usually very easy to implement and is the fastest medium to send a message across. Email Campaigns can be easily customized with graphics, video etc.
3) Tracking is Simple: There are many tools available which are specifically designed to track email campaigns. You can also track email campaigns yourself. I will be explaining how we can track email campaigns ourselves.
4) Test email for best results: Email campaigns can also be subjected to AB tests incorporating different subject lines, different content of email or different call to actions. You can measure the open rates or Click through rate of each test email campaign and measure efficiency.

Disadvantage of Email marketing:

Prone to Spam and Phishing attacks: Emails are often notorious with spam/junk sent to your inbox which causes frustration among customers. Hopefully the Spam filters of email clients do a good job to an extent but usually good emails might get filtered too. So there is always a trade-off. Similarly spammers/hackers might create Phishing/Fake email campaigns and incite you to go to a different website which might look like a legitimate website.

Email Marketing Metrics:

There are many metrics that we can measure to gauge the success of an Email campaign. Let’s try to understand this from a conversion perspective as shown below.
  • Emails sent
  • Emails sent successfully (Non bounce emails)
  • Bounces
  • Unsubscribes
  • Emails opened (Open Rate: emails viewed/emails sent)
  • Clicks on link in the email (CTR: Total Clicks/Emails Opened)
  • Visitors redirected to target website from email campaign (Landing page Visitors or Visits/Emails sent)
  • Conversion rate on target website (Confirmation page Visitors or Visits/Emails Sent)

Email Marketing deep dive and best practices:

1) Open rate is considered to be an important metric while measuring an email campaign but tracking it has some constraints. Mostly all email campaigns are created in HTML and tagging them with a JavaScript snippet of Google Analytics/Omniture will not cause the image pixel to be fired. The reason why it happens is because email clients don’t run JavaScript. A potential workaround that can be to include a .gif image call in the HTML email to get the impressions of the email/opens. Based on the read emails, calculate the Open rate: opens/emails sent.

2) The target outbound link embedded in the email should always contain respective URL parameters to track that the campaign is email specific. Visitors landing on the target website should be attributed to the email campaign based on these tracking parameters. A perfect method for tracking emails yourself can be tried with the Google URL Builder tool found here:

As shown in the image above, when we click on the ‘Generate URL’ button the URL generated is http://rkapoor.blogspot.com/?utm_source=rohanblog&utm_medium=email&utm_content=textlink&utm_campaign=testemails which can be placed as a text link in your email campaign to track a particular campaign. You can then go to Google Analytics and view your Campaigns report.

3) If you do not want to use tracking parameters in your URL, then you can create separate landing pages only specific to your email newsletters. Once you start getting traffic, then you can measure the Visits on the unique email landing page to measure your campaign response to get data for the newsletter clickthroughs.

4) Opt-in is another metric that you can measure to gauge success/response of email opt-in links present on your website. You can measure how many visitors click on a check box to opt-in for an email newsletters. The metric here can be Email Opt-ins/Page Views.

There are various tools available to track email campaigns in the market. Some of those are Madmimi, Aweber, Icontact and Jangomail. Please let me know if I need to add more.

It was really nice writing about a successful, yet underrated topic of Email marketing. I hope you like this post and will highly appreciate if you can share your feedback on this topic.