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?


Thursday, October 27, 2016

2 Key Lessons From Facebook’s Video Views Metrics Fiasco

People have short term memory (or selective memory), when they can’t remember things they will resort to how they think something should be. Recently Facebook was in the hot seat because of this very reason. 

Facebook metrics definition issue

Facebook has a metrics called “Video View” for video ads.  In this metric they only counted the video as viewed if it was watched more than 3 seconds by the viewer.  In other words, if someone watches a video for 2 seconds then that video view won’t be counted as a view in this metric.

Facebook also has another metrics, called “Average duration of Video views”, the “standard” definition of it should be Total Time spent watching video divided by Total Viewers. However, that’s not how Facebook defined it.  In Sept Wall Street Journal reported that Facebook "vastly overestimated average viewing time for video ads on its platform for two years.”  This lead to an apology from Facebook

About a month ago, we found an error in the way we calculate one of the video metrics on our dashboard – average duration of video viewed. The metric should have reflected the total time spent watching a video divided by the total number of people who played the video. But it didn't – it reflected the total time spent watching a video divided by only the number of “views” of a video (that is, when the video was watched for three or more seconds). And so the miscalculation overstated this metric. While this is only one of the many metrics marketers look at, we take any mistake seriously.


As per DM News article, Facebook did state the definition when it rolled out this metric two years ago.  So it was not actually doing anything wrong.  It was a case of short term memory issue.

“The problem, as critics put it, is a problem of omission. While Facebook very clearly states that it's only counting views as any video-play event that lasts longer than three seconds, it does not go out of its way to explicitly beat readers over the head with the fact that this definition of a "video view" applies equally to the calculation of average duration of video views.”


If Facebook product team had read my posts from 2012 on “Creating a culture of analytics” then they might have likely avoided this “scandal”. The two issues that Facebook dealt with were the exact same ones I talked about in my posts. To recap, here are the gist of those two posts:
  • Make sure everybody understands clearly how metrics are defined.  I talked about this in my post in 2012, Standard Definitions of Metrics: Creating a Culture of Analytics. In that post I said 

  • Lack of standard definitions for the metrics causes people to report different numbers for supposedly same metrics, leading to confusion and total lack of trust in data.  No trust in data means that nobody is going to use the data to make strategic decisions and there goes all your efforts to create a culture of Analytics.

    Having standard definitions is not as easy as it sounds.  It starts from you and your team having a clear understanding on how to calculate various metrics.   Some seemingly simple metrics can be calculated in various different ways and all of those ways might be right but getting one standard way of calculating those removes any confusion and gets everybody on the same page.
  • People have short term memory.  In my 2012 post, titled  Dealing with Short-Term Memory: Creating a Culture of Analytics,  I wrote:

    We all make assumptions from time to time; sometime we state them clearly and sometimes we just assume in our own head. We then operate under those assumptions.  In context of Analytics, one such assumption is that everybody knows what the goals and KPIs are.  We might have defined them on the onset of the program, campaign, beginning of month, quarter, year etc., but once those are defined we start to assume that everybody knows about them and is operating keeping those goals in mind.

    Well the truth is that people have short term memory. They do forget and then start to interpret the KPIs, defined based on those goals, in their own way.  As the Analytics head/analyst/manager, it is your job to constantly remind stakeholders of the goals and KPIs. 

Two Lessons

This fiasco provides two great lesson for all the Digital Analytics teams.

1.       Clearly define your metrics and make sure the underlying metrics and calculations are clear in your definition.
2.       Don’t make any assumptions, people have short term memory. Just because you stated a definition of a KPI in past does not mean everybody will remember it and know how tit was calculated. It is your job to make sure anybody using your metrics/KPI can get to the definition and calculations right away. 


Questions? Comments?

Wednesday, October 19, 2016

Not personalizing? You are leaving money on the table.

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.

According to an eConsultancy report, 94% of the companies realize that personalization is critical to current and future success.



However many can't move forward with personalization because of many barriers they face in implementing personalization.  The biggest being IT, Technology and Budget. (see below).

Charts from eConsultancy Reports - The Realities of Online Personalization

Many marketers don't realize that personalization does not have to be complex. A recent study be Accenture shows that consumer are likely to buy from a retailer who provides some level of personalization (see below):


As you see in the chart above, simply recognizing the customers by name will get them to buy more. So start there if you are already not doing it, that won't require big IT infrastructure or budgets or data. Don't be bogged down by the hype created by press releases or marketing presentation about the sophisticated personalization few companies are doing. Many of the personalization techniques don't require big budgets or IT infrastructures.

Start simple, understand the value personalization brings, show case the value to your internal stakeholders and make a case for getting more funding for more sophisticated personalization tools and technologies. I will be writing more about personalization so subscribe to my blog if you are interested. If you need help feel free to reach out to me. I would also love to hear from those who are currently involved with personalization or have a good story to share.

Article referenced in this post



Personalization is no longer optional

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.

According to an eConsultancy report, 94% of the companies realize that personalization is critical to current and future success.



However many can't move forward with personalization because of many barriers they face in implementing personalization.  The biggest being IT, Technology and Budget. (see below).

Charts from eConsultancy Reports - The Realities of Online Personalization

Many marketers don't realize that personalization does not have to be complex. A recent study be Accenture shows that consumer are likely to buy from a retailer who provides some level of personalization (see below):


As you see in the chart above, simply recognizing the customers by name will get them to buy more. So start there if you are already not doing it, that won't require big IT infrastructure or budgets or data. Don't be bogged down by the hype created by press releases or marketing presentation about the sophisticated personalization few companies are doing. Many of the personalization techniques don't require big budgets or IT infrastructures.

Start simple, understand the value personalization brings, show case the value to your internal stakeholders and make a case for getting more funding for more sophisticated personalization tools and technologies. I will be writing more about personalization so subscribe to my blog if you are interested. If you need help feel free to reach out to me. I would also love to hear from those who are currently involved with personalization or have a good story to share.

Article referenced in this post