Starting a Career in Web Analytics

Web Analytics is one of the hottest fields these days. A lot of people are planning to switch careers and many students are looking to start their career in Web Analytics. This article is to help people who are looking for a career in this field.

Skills required to be a Web Analyst

First and foremost you need desire and passion to be a web analyst. Desire and passion will get you where you want to go. I believe (and this is my opinion only), if you have the desire and passion then you can acquire other skills. Not everybody will agree with me but again that’s my view.

Other most important skill that you need is Analytical skill. If you are a person who always looks at the problem from a different angle than most of the other people, you have what it takes. If you can put different pieces of the puzzle together to form a complete picture you have the skills to be a web analyst. If you can critically look at things, you have the skills.

Other Skills and education that will come in handy are
1. Business
2. Marketing
3. Statistics
4. Technical

You don’t need a college degree but a lot of employers look for it and I look at it when hiring a candidate. Business, Marketing, Accounting, Statistics and Technical degrees will be very helpful in getting you the job but I have seen Web Analysts having diverse educational background.

Learning about web analytics

There are several resources available to learn about Web Analytics. There are several blogs on Web Analytics where you can get all levels of information on this subject.

First and foremost you should join WebAnalytics group on Yahoo. This forum is a great source of information. You will find all levels of web analysts in this forum. This is a free for all forum, even if you want to stay on sideline and just read message, you can learn a lot. If you have any question on this subject, feel free to ask at this forum.

Books that you should read:

1. Web Analytics Demystified
2. Web Analytics An Hour A Day
3. The Big Book of KPIs
4. Web Site Measurement
5. Advanced Web Metrics with Google Analytics
6. Always Be Testing: The Complete Guide to Google Website Optimizer

Note: I just added a list of books on Web Analytics, you can check them out at Web Analytics Bookstore

If you are prefer to learn in formal way then I recommend, the course offered by University of British Columbia. You can learn more about this course at http://www.tech.ubc.ca/metrics/curric.html. (I am one of the associate instructors for this course). This course is offered in partnership with Web Analytics Association (WAA)

Reading blogs, articles and whitepapers is another way to expand your knowledge. Most of the blogs are of advanced nature, so I would recommend you familiarize yourself with the Web Analytics field (see above) before reading these blog. Two of the blogs that I recommend are Occam’s Razor by Avinash Kaushik and Web Analytics Demystified by Eric Peterson, the author of the books mentioned above. Both of these blogs have a list of lots of other blogs on Web Analytics. The more you read the better you will understand this field. Also check out Post Rank for a list of Web Analytics Blogs.

Twitter: At twitter, you can find a list of web Analytics folks and topics by searching for #measure.  There is also a list of twitter users in the web analytics community at http://webanalysis.blogspot.com/2008/12/my-view-on-twitter.html.

Gaining Practical Experience

Google Analytics (http://www.google.com/analytics) has made it real easy for anybody to get a web analytics tool. This tool is completely free with all the documentation to help you get rolling. If you have a website, deploy this tool and play with it. This will help you understand how web analytics tools and reports work.
To gain further experience, tap into your network, I am sure somebody (a friend of a friend of a friend…) will allow you (especially if you are willing to do it for free) to provide reporting and analysis on their site (real site).

Another great resources is Analysis Exchange. Analysis Exchange has created a training ground for new analysts all around the world.

There are several companies who are looking for entry level analyst. You don’t need any experience, all you need is desire to learn and grow. They will hire you, train you and provide the support to help you grow in this position.

What is Abandonment Rate

Drop off or abandonment rate measures the number of visits/visitors who left a conversion process (funnel) without completing it.  Any  process with 2 or more actions on the site can be considered a conversion process, what you define as a conversion depends on the purpose of your site and your business objective. Some of the commonly used conversion funnel are shopping cart, newsletter signup and document downloads.

Abandonment rate helps identify the steps in the funnel that are causing the users to drop off.  Conducting analysis of those steps will help us take necessary steps to minimize the drop offs and optimize the conversions.
There are 2 ways to calculate Drop off rate and each of them provide the data in slightly different ways. Both of them are correct ways to calculate.

  1. Total Drop off from First Step = (Visits to the current Conversion Step-Visits to the First Conversion Step)/Visits to the First Conversion Step.  Let’s assume that we want to use Product as the first step of the conversion process and that step gets 10,000 visits.  But of those 10,000 only 7,000 continued to the next step of adding the product to shopping cart.  Then in the next step only 200 out of total 10,00 that started the process continue to Registration form and finally 1,200 out of 10,000 got to the final confirmation page. This means we saw 30% abandonment between Step 1 and Step 2  ie. (7,000 -10,000)/1000.  Abandonment was 80%  from Step 1 to Step 3 (2,000 – 10,000)/10,000. Final abandonment rate was 88% (1,200 – 10,000)/10,000.  Though this calculation gives us a good idea of final drop off rate and conversion it is a little hard to understand.
  2. Step Abandonment Rate = (Visits to the current Conversion Step-Visits to the previous Conversion Step)/Visits to the Previous conversion Step. This calculates the abandonment rate between the two immediate steps.  Unlike the previous calculation it provides a better idea of abandonment as visitors move from one step to the other. As shown below, again out first step had 10,00 visits, of those 7,000 continued to next step resulting in an abandonment of 30% (same calculation as above).  However when the visitor moves from step 2 to step 3, our abandonment rate now is is 71% (2,000-7,000)/7000. The final step then shows an abandonment rate of 40% (1,200 – 2,000)/2,000 Using such a calculation you can easliy see which steps are causing the biggest drops, in this case it is step 2 and step 3, people are adding products to cart but not clicking on the checkout button to go to registration form.  Why? Maybe checkout button is not visible? Maybe it is the name of the button? Whatever the reason is, you have the data to show where the problem is and gives you an idea on what needs to be fixed.

Contributed by Rohan Kapoor based on his original post at Funnel Drop Off/Abandonment Rate

  1. the above formulas, it looks like the first one seems better in terms of Funnel visualization but personally I like the second formula better. I say this because in the second funnel we are only considering the respective Conversion steps in the calculation and not Step 1 (Homepage) because Step 1 is entirely a separate user experience. According to me the Drop off rate should be calculated based on the 2 Conversion Steps as they are independent of the user acquaintance on the other pages of a Funnel. These 2 pages alone can determine how we can improve the conversion rate at each step as these are not based on the Homepage experience. For e.g. The Registration form design and involvement is totally different than what it is on the Homepage. I hope you like this post and would really appreciate if you can share your opinions.

Contributed by Rohan Kapoor based on his original post at Funnel Drop Off/Abandonment Rate

Role of Search & Social Media in the Purchase Pathway

A recent study by GroupM studies the impact of Search and Social Media in purchase cycle. For this study Group partnered with Dell some key brands in telecommunications and consumer packaged goods (CPG) industries.

GroupM developed this study along with comScore to understand the relationship between Search and Social media as it puritans to online purchase pathway all they way to conversion and brand loyalty.

The results shows that both Search and Social are very critical for not only initial conversions but also for brand loyalty.

Here are some key stats from the study

  • 51% of the conversion users rely on search only while 48% rely on both Search and Social Media.
  • The study found that 58% of the “Paths to Purchase” start at search while only 18% start with social media.
  • 25% of the users conducted brand product searches after visiting a brand site (either the brands own site or a competitors site)
  • 1.86% of the respondents cites search as begin very important
  • 2. 45% of people use search throughout the purchase process
  • 2. 26% use search only at the beginning of research and shopping process
  • 3.18% use search only at towards the end of the purchase cycle.
  • 4. 67% of the people site quality and depth of the information as a reason for using search engines
  • 50% of people indicated that they use search for deals and/or sales more often than pricing or store location
  • The duration of purchase path can be as long as 60 days (multiple categories were studied)
  • In last 30 days of that period search behavior intensifies.
  • What aids the purchase decision? 30% said User reviews, 17% Facebook, YouTube and other video sharing 14 and Twitter 9%
  • 64% of the people said they are likely to follow a brand via social media after a purchase
  • 74% of the people said the desired format for future engagement is via Facebook brand page

You can download the full study athttp://www.scribd.com/doc/49442666/The-Virtuous-Circle-The-Role-of-Search-and-Social-Media-in-the-Purchase-Pathway-Research-from-GroupM-Search

How to Measure Online Advertising Success

I am amazed at how companies spend millions of dollars on online advertising but none to actually measure if it was successful or not. I have come across several companies in past few years so thought I will share my 10 step process to measuring the success and ultimately improving the ROI.

Below are two eye-opener real life examples that will show why I thought this was a subject that I should blog about:

  • A customer spent 8 million on a huge online campaign but had not clue weather they were getting their money’s worth or not. All they got was banner impressions and initial click through rate (CTR ) from their agency. This initial CTR was in line with what their agency had expected so they were contended with the results. As far as measuring beyond the initial CTR they had no idea. Their answer was that we do not sell anything so we can not see if this is generating money or not, all we need to do it generate brand awareness. Well were they generating brand awareness? In few minutes we were able to see that that they had 90% bounce rate (yes they had WA tool implemented but were not looking at it, yah I know what you are thinking). That is 90% of the money down the drain. It is true that everybody who gets to the site has been exposed to the brand but is that enough? 90% bounce rate was pretty substantial considering that initial click through was close to 1%. I don’t think they were able to generate brand awareness.
  • Another customer spent about 4 million on an online campaign but was very stingy when it came to using web analytics tool on their site to measure the success. Not sure if the marketing manger was not comfortable with the result that she would get or just did not consider it worthwhile to measure because she had extra money to spend.

Does this sound familiar? If yes and you are marketing manger or marketing exec, I would strongly suggest putting some money aside for measuring your campaigns performance beyond the initial CTR. You will be able to learn a lot more about how your campaign is performing and improve your ROI by simple A/B testing. If you are an analyst then please work with the marketing department and sell them the benefits of measurement.
Below are my 10 steps for measuring the online advertising success, nothing fancy, a simple straight forward process that will improve your bottom line.

  1. Determine the goals and objectives of your campaign. – Knowing why you are running the campaign is first and foremost step. Unless you know why you are running the campaign you will never know if was successful or not. Marketing manager and web analyst should be in sync on this. Infect all the stakeholder should be on the same page. A clear understanding of the goals helps everybody focus on same things.
  2. Determine success criteria and KPI’s for your online campaign. – Once you know the goals of the campaign, next step is to determine the Key Performance Indicators (KPIs) of the campaigns. These key metrics will allow you to see how the campaign is performing. If you already have a baseline measures from your previous campaign then you can compare your metrics against them or if you don’t have one then within weeks or a months (depending on the duration of the campaign) you should be able to develop one.
  3. Create a campaign attributes framework – It is very important to build a campaign attributes framework from the beginning. Deciding what attributes to measure the campaign against early on will make sure you capture them from the beginning. Also upfront thinking will allow you to get a buy-in from agency, as most likely they will be responsible to for providing you with all the campaign attributes. Some examples of the attributes are placement, creative, message, publisher.
  4. Implement proper web analytics tracking code on your site and landing page(s) – After you have the framework in place and know which metrics to capture, next step is to get together with you implementation team to implement proper tracking code on the landing pages and site. As you already know if the tracking codes are not implemented properly you will not be able to track your campaigns. I suggest running a test before you go live, so that you can resolve any issues upfront else it will be too late.
  5. Configure web analytics tool to measure your KPIs – Another area to pay close attention to is tool configuration. Too many times I have seen disconnect where KPIs are determined but the tool configuration is so messed up that you can not measure anything. Determine what reports you will need and how they will be configured. Work with your implementation team; make sure they understand the goals and what you are trying to measure. I was recently involved with a campaign measurement configuration where we had to reanalyze the data because the implementation guy messed up one configuration. Luckily point no.4 above was correct so all the data was there it just had to be reanalyzed. Pay extra attention.
  6. Tip – Configuration of the tools (reports) should be such that you can compare overall user (or user driven organically) with those driven by the campaign. I have found that this kind of insight helps you better understand your visitors and determine where you should be spending your money and effort. The more you can segment your user base the better insight you will get.

  7. Build a scorecard or dashboard that will allow stakeholders to focus on the KPIs – The temptation by stakeholders is to look at every single data point weather they understand the impact of those or not. I have been in meetings were they will try to argue on things that don’t even matter. Why? Because they had access to the data and like to argue. The scorecard or dashboard should allow them to focus on things that matter instead of every data element that a web analytics tool can provide.
  8. Tag all your ads with appropriate campaign identifiers – You have determined the KPIs, setup the reports and a nice scorecard is waiting for the data and analysis, but guess what? The agency did not add the proper campaign identifier. All your efforts are down the drain. The problem occurs because people setting up the campaigns in ad servers have zillion other things to worry about and if they are not ingrained in the process they will forget or won’t give due attention to campaign tracking. As I mentioned above in point number 3, if you create the attribute framework and involve the agency then this should not be an issue.
  9. Analyze the data in few hours of launching the campaign, fill the scorecard and learn from the data. Few hours might be too early to learning anything meaningful (depending on the magnitude of the campaign) but can show you if something is really screwed up. Tune as necessary.
  10. Periodic reporting and analysis (will depended on the length of campaign but start with daily then weekly/monthly). – Periodic reporting and analysis is an important aspect of this process, this is where you will actually know if the campaign is achieving its goals or are there things that should be changed. Don’t stop at reporting only analyze the data (see my article titled Are you doing Web Reporting or Web Analytics. Provide actionable recommendations. Provide your analysis back to the stakeholder. Discuss them, debate them and determine what to test. (I am not going to go in detail on A/B or multivariate testing in this article)
  11. Put this process in place and share with all the stakeholders. Buy-in from all the stakeholders is necessary for any process to work. Put some timelines so that key stakeholder can be involved in the process in timely fashion.

The above process will help you measure the true success of your campaigns. Learn from the data and optimize as necessary. Remember there is always room some for incremental improvement. You will be amazed how you can improve your ROI by following above 10 steps.

Contributed by Anil Batra: 10 steps for measuring online advertising success – Web Analytics, Behavioral Targeting and Optimization by Anil Batra http://webanalysis.blogspot.com/2007/06/10-steps-for-measuring-online.html#ixzz1FNi3zbHH