Monday, October 02, 2017

Career in Web and Digital Analytics – Online Course



I recently developed an online course which provides information on the Career in Digital and Web analytics. The course is a result of the emails that I get from recent graduates and people who are looking to change their career.  This course "Career in Web & Digital Analytics" is currently available on Udemy 


The course covers following area:

  • Introduction to the filed
  • Salary Expectation – Industry surveys
  • Various Roles
  • Deep dive into the roles
  • Career progression
  • Education and Skills
  •  Resources for Learning

I will add more content based on the student feedback.  Here are some ideas of content that I will be adding soon (you will have access to the course forever, so any new content will be available to you as soon as I upload it).

  • Who hires – various types of companies
  • What a digital marketer needs to know
  • Step by step guide

If you are not able to afford $20 for the course but still want it, then let me know what you would like to pay and I will send you a link for the discounted offer. 



Tuesday, August 01, 2017

What is the difference between Segmentation and Personalization?


What is the difference between segmentation and personalization? This is the question that came up during one of the webinar on personalization by Optimizely. This blog post is for those who have the same question.

Basic definition of Segmentation is  - division into separate parts or sections.  For the purpose of marketing, it is a processing of grouping customer and prospects into similar groups based on various criteria such as demographic, geo, behavioral and psychographics.  You can use one or more of such attributes to define your segment.  The purpose of segmentation is to understand about a group (segment), and develop marketing strategy to better target those segments. 

Personalization is providing marketing messages and/or experience that is tailored based on a customer’s needs or preferences.  Personalization can be very basic that can start from simply recognizing the person by name or it can be very complex that includes all sorts of data about a particular customer combined with device and contextual data (1st party data + 3rd party data). Personalization is the action that you take based on the learning you have about the person (a segment of 1 individual).

So segment is a way to understand your customer based while personalization is the action you can take based on that understanding.

Let’s look at very basic example to clarify these two terms:
You look at your site visitors and identify that there are two main behaviors of your visitors:
1.       Visitors who mainly click on sports related content, that’s where they spend most of their time
2.       People who mainly read finance related content, that’s where they spend most of their time.
Using this information, you have two segments – 1. Sports Visitors and 2. Finance Visitors 
This is called Segmentation

When someone who fall into “Sports” segment comes back to your site, you rearrange the content to highlight latest sports stories so that these visitors can easily discover the content they love.  On the other hand, a visitor who falls into “financial” segment will see finance stories highlighted.

This is called Personalization. 

Now this is not 1:1 personalization but it better than no personalization at all.

Hope this clarifies the difference between the two terms.  

Questions? Comments?

Friday, July 07, 2017

Are Spiders and Bots your customers?



Those who know what internet bots and spiders are, know that know that spiders and bots visit your site very day and multiple times a day.  For those who don’t know here is the definition of bots according to Wikipedia

An Internet bot, also known as web robot, WWW robot or simply bot, is a software application that runs automated tasks (scripts) over the Internet. Typically, bots perform tasks that are both simple and structurally repetitive, at a much higher rate than would be possible for a human alone.

According to a recent survey, on an average about 51.8% of the website visitors are bots.



One assumption many digital analysts make is that the JavaScript based analytics solutions such as Google Analytics, Adobe etc. either stop bots from executing the script or filter them out before calculating the metrics.  Well, this assumption was true years ago, it was one of the selling points of JavaScript based solutions as compared to log file based solutions.  However, things have changed over past few years, many bots are now capable of running JavaScript and hence polluting your reports.  Likes of Google Analytics and Adobe Analytics will filter out the spiders and bots to an extent but considering the number of new bots that emerge every day, it is not an easy task, neither for them nor for you.  So what do you do?  Since you are not going to get 100% bot free report filter out as much as possible so the effect on your reporting and analysis is minimal.

I recently had a conversation with one of the attendees of my Digital Analytics Association (DAA) workshop at Chicago eMetrics. She told me that she gets a report every week from their digital analyst. When asked, Digital Analyst confirmed that the report does not filter out any activity from spiders and bot becuase he does not have time to remove them. She was wondering if she should worry about it and push to remove the bots from report or just accept it.

What do you think? Do you think the report she is getting is worth anything?

Unless they are selling to spiders and bots, she is not getting an accurate picture of website usage by real customers.

Make sure to ask your analytics team if they are removing bots from reporting. If not, then do not accept the reports till they have done cleanup and are paying attention to it on ongoing basis.

Comments? Questions?



Friday, February 10, 2017

11 Tips for Improving Customer Experience and Driving Conversions

Struggling to drive conversions?  The issue might be with customer experience. After having worked with several brands, big and small, I can assure you that you don't have to make sweeping changes to drive better results. Many times even small changes and little bit process can lead to happy customers and big impacts. In this post I have complied 11 tips that you can use today. If you need help then don't hesitate to reach out to me.
  1. Easy to fill forms – How many times have you come across a form field where you don’t remember what the field was about?  Many designers/developers use the default text in the form filed as the filed label. Once you tab into that field, the default text is gone and now you can’t figure out what that field was about.  That is a very bad design which will likely cause customer frustration and kill conversions.
  2. No more unnecessary form field formatting and validations - Other than Captcha validation, you are likely using form field validations in your online form to make sure visitors/customers enter the correct data.  You might also use validation to ensure that the format of the data fields such as email, phone, etc. is correct. Many of these validations are absolutely required to ensure data quality. However, some validations put unnecessary burden on your customer/visitor leading them to abandon your forms/checkout process. A lot of data formatting can be done via client side JavaScript or backend processing without putting the customer through a lot of pain. So go through your own forms, see if all form validations are absolutely required. If not, then remove them, also remove any validation/formatting requirements that you can handle via code in the front end or backend. Check out my post on Form validation and conversions
  3. No more convoluted captcha - Captcha are great to stop the spammers, bots and spiders from filling the forms, but some Captchas are so bad that they not only create a undesirable customer experience but also kill the conversions. Make sure you critically evaluate the captcha on your site and if it seems like something you yourself don’t want to encounter on another site then kill it. I wrote a blog post on Captcha, you can read it at  Is CAPTACH eating up your conversions 
  4. Easy Promotional Code and Discount Code redemption - Promotional Codes also known as Promo Codes, Discount Codes, Coupon Codes, Offer codes etc, are supposed to drive sales, right? However, they can have a reverse action and can actually kill your conversions, if not properly used.  In my post “Promotional Codes: Conversion Killers?, I showed one such example where Promo codes can hinder conversions.  If you are going to announce a promotional code on your site, in a ad etc. and you know that the customer clicked on the link to arrive to your site then go ahead and automatically apply the relevant promo code don’t make a customer think and take extra steps.  Godaddy is a great example of a site the automatically apply any relevant promo codes.
  5. Consistent experience across devices - Customers expect consistent experience across browsers and devices so don’t mess with their expectations.  Broken experience can lead to customer dissatisfaction and defection. I wrote about one such example in my post, 2 A/B Testing Lessons Learned from Amazon Video.  Read more: 2 A/B Testing Lessons Learned from Amazon Video 
  6. Easy to find customer support number  - Yes, phone support is expensive but bad customer experience is even more expensive.  If you do your cost analysis, you might find that phone support is actually profitable. A phone call provide you an opportunity to hear your customer and convert a dissatisfied customer into a satisfied customers. Make it easy for customers to contact you rather than complain on social media.
  7. Connected Channels, Customer Service, Support and Marketing - If I get a marketing material and I call the number listed on that then person picking up the phone on the other end should be able to answer question on that material. I have several experiences where customer support is not in sync with the marketing and customer has to waste his/her time. I talked about one such case of disconnected experience in my blog post titled, Are you Optimizing the Wrong Steps of the Conversion Process? 
  8. Easy to Find subscription cancellation link - Have you ever tried to cancel a paid App subscription on iPhone?  It is pretty bad. I always forget where the link is and have to spend several minutes to look for it. Not a good experience.  It might work for iPhone and Apple but likely won’t work for you. If customer wants to cancel a subscription, then go ahead and make it easy for them to find the cancellation button/links. I am not saying you let them go easily, you should have top notch experience, service etc, to make it hard for them cancel but hiding an option to cancel is not the solution.  If they can’t find that cancellation link the they are going to leave you bad reviews about you in social media. Use data to figure out how valuable the customer is, understand why he/she is leaving and provide proper personalized offer/incentive for them to stay.
  9. Easy to Unsubscribe from emails and other communications – Don’t end up in spam folders because your subscribers can’t find an unsubscribe link in your email. Spam complain will hurt more than the unsubscribes. If you do send relevant messages then unsubscribe should not be a big issue because people only unsubsribe from irrelevant stuff. Follow email best practices, send relevant messages and provide a link to unsubscribe.
  10. Ongoing Testing - Customer preferences change, their behavior changes and you site has to change to. The best way to change your site is to keep evolving and always trying to find out what works best for your customers. This is where ongoing testing (A/B testing, MVT testing) helps. Before rolling out a feature, page layout etc., test it and see if your customers like it.  If not, then try something else. As Bryan Eisenberg says “Always Be Testing”. 
  11. Personalized experience I started writing about personalization ever since I started this blog, back in 2006. I wrote extensively about privacy and how marketers should address it to engage in personalization. Consumers are now more at ease with online purchases, they have moved past initial privacy concerns of online tracking and now expect personalization.  Personalization is no longer optional. Many marketers don't realize that personalization does not have to be complex. You can start simple and build on it.  Reach out to me if you need help.
Thoughts? Questions? Comments? Need Help?  Contact me at batraonline at gmail or fill this form http://anilbatra.com/analytics/contact-me/

Sunday, December 11, 2016

2 A/B Testing Lessons Learned from Amazon Video

It is no secret that Amazon is a data driven organization.  The culture of testing is ingrained into pretty much everything Amazon does. However, a company like Amazon also makes mistake as I learned from my recent experience with Amazon Videos.
I have two Amazon Fire TV Sticks, one attached to each TV that I have. Both are tied to the same Amazon account.  Using my Amazon Video account, I started watching a movie on one TV, turned it off halfway through and then a day later tried to watch it on the other TV. Guess what? I could not find that movie in any of the obvious menu options. I was expecting it to show up in my stream or at least in the same place where I found it last time.  Nope.  Amazon changed the order of movies on me. It’s not like it added new movies to the lineup and this movie got pushed down. They just reordered the existing movie selection. It appeared to me that some kind of movie display sorting experiments was going on. However, that experiment, ruined the experience for me as I spent a lot of time looking for that particular movie.
In another instance on Amazon Video, I found the movie but as I soon as I clicked on it, it vanished and the movie list was reordered. Weird, right? Again, my suspicion is that some movie sorting/ordering algorithm experiment (A/B test) was going. So, what can you learn from this experience?  There are two A/B testing (experimentation) lessons that you can learn from this mistake by Amazon:
  1. Keep version consistency across devices – Everybody uses multiple devices these days, multiple TVs, Tablets, Phones etc. Make sure you provide same version of your layout/algorithm to the same user across devices. Which means that you must do testing at the customer level instead of session or visitor level.
  2. Do not change customer experience midstream – Make sure all touch points are in sync and you’re A/B test does not change customer experience as customer interacts with the interface. In this particular case, if the movie was right in front of me on the home screen then pressing the button on the movie should not have triggered a test that rearranged the order of the movies displayed on my screen. The ordering/sorting should have been done before it was presented to me.
Questions? Comments?
Need help with A/B testing and Personalization? Reach me at batraonline@gmail.com.

Monday, November 07, 2016

Difference between Web Analytics and Digital Analytics


Web Analytics and Digital Analytics are quite often used interchangeably.  I have been asked, by my students and some clients, about the difference in these two, so I decided to write this short post to clarify the terms.

As you can see from the Google Trends graph, Google searches for “Digital Analytics” were nonexistent till Web Analytics Association changed its name to Digital Analytics Association. Since then the term "Digital Analytics" has started to pick up.



In early days of internet, companies started to analyze website data such as users, visitors, visits, page views etc. and the term used to describe this analysis was called “ Web Analytics”.

Then came other forms of online (digital channels) such as email, search, social, mobile etc. and increasingly Digital Analytics folks were including this data and analysis of all these channels to provide a complete view of the “Digital” channels, marketing and customers. To fully include the scope of work of “Web Analysts” a new term “Digital Analytics” was coined.

“Web Analytics” companies like WebTrends, Omniture (now Adobe), Google Analytics etc. also started including data from other online channels and transformed from Web Analytics tools to Digital Analytics tools.

When I was on the board of “Web Analytics Association” from 2009 – 2011, we had several discussions regarding the name of the association. The general consensus was that our members were doing much more than traditional “Web Analytics” and association needs to change the name and scope to include the changing role of "Web Analytics". Association finally changed the name to "Digital Analytics Association" on March 5th, 2012.

So back to the original question - What is the difference between Web Analytics and Digital Analytics?

Web Analytics is analysis of the website data.

Digital Analytics includes analysis of data from all digital channels that includes websites. Data from search, display advertising, social, email, mobile etc. is included to provide a complete view of the digital marketing and customers.

Though usage of Digital Analytics is picking up, “Web Analytics” is still searched more often than “Digital Analytics” as shown in the following Google Trends chart


Thoughts? Comments?