Real Time Reporting - What and Why

What is Real-time reporting?

Real-time reporting provides you a view into what is happening at that very moment. In the context of Web Analytics, real-time reporting gives you a glimpse into what't happening on your website at . 

It provides you view into on how many visitors are on your site. Which campaigns, sites, search engines, social media sites etc. they are coming from, which pages they are looking at, what actions they are taking on on etc. 

How Real-time reporting can help

Though most of your insights are going to come from the not so real-time data. Real-time reporting can help in several scenarios. Below are some use cases for real-time reports:

• Campaign Launch - When you launch a new campaign e.g. paid search, email newsletter, TV ad etc. you want to see how people are reacting to those campaigns then real time makes sense but only for initial diagnosis. Wait for complete data to make any changes.
• New Promotion - When you add new promotions on your site and want to see how visitors are reacting to those promotions, so that you can tweak/ experiment new version of those promotions in real time, then yes you should look at real time data.
• New story/content - When you add new stories, links etc. and want to see if anybody is clicking on them so that you can make some changes based on instant feedback. I can see the usefulness of this feature for news and media sites.
• Site Changes - When you launch a new version of the site and want to see if new pages are being recorded in Google Analytics and if you users are interacting as expected then real time reports can help.
• Tracking Changes - When you roll out new tracking changes and want to see if those changes are working or not. For example, you just enabled Event Tracking via Google Tag Manager and want to see if the events are capturing the right data or not. In this case you will check the real time Events report in Google Analytics. I expect you to check the changes on a development and QA environment before rolling out.
• New Features - When you launch a new feature on your site, launched a video, deployed a new game and would like to know if your visitors are using it or not, real time reports can help.

Keep in mind that even if you are ready to make changes in real time, you might not have statistically significant results based on few data points that you get in real time reports. 

What do you use the real time reports for?

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Who owns your website, user data and digital assets?

Should you build your audience and pages only on 3rd party platforms such as Facebook, Twitter, YouTube etc.? This is a questions that I see quite frequently in various digital marketing forums.

In this post I am going to provide you my point of view on this subject.

These 3rd party platforms are huge with lots of traffic so first and foremost you should try to grab your share of the traffic from them. You should work hard to clearly figure out how to make the most of these platforms and how to leverage their reach to help your business grow.  However, you should not build your entire business on them. 

Why you might ask?  Because they have the power to shut you down anytime for no fault of your own.You don't want to be in a situation where you entire business comes crashing down one day.  You are at their mercy, you don't control their terms and polices, either you agree or disagree. If you disagree then you can't be part of that platform or network.

If for some reason you are found in violation of any of their terms and policies you could be completely shut out. Then all you are left with is to fight with back and forth emails, if you are lucky. In most cases you might not even get a timely response.

Some Examples:

Facebook blocked user accounts - Check out this post titled "What I Learned When Facebook Disabled My Account". This post has a lot of comments about people losing their access to Facebook and hence access to their pages and groups etc.

Twitter suspending accounts  - Below is an example tweet that shows you that once your account gets suspended then it becomes difficult to get it restored

My Experience:

I also had such experience recently where Google shut down my account for a few minutes. I am still not sure why that happened. All I got was an email that my account was suspended for not following Google policies but they did not give any clear indication.  The email was very generic in nature and I believe that was done automatically by an algorithm. Since the email was sent to my gmail account, I only got that after the account was restored. I was lucky that it got restored automatically in few mins. 

However this experience was scary as I have a lot of stuff on Google.  I have my emails on Gmail, my pictures on Google, Videos on YouTube, this blog is on Blogger (owned by Google), Google docs etc. Imagine if I was left without access to these things for days. 

Solution

Always keep a backup of important files, documents, emails and audience that your business depends on.

Businesses

1. Drive your  audience to your own websites and blogs (not a free platform as I do). Facebook pages, groups, twitter accounts are all great but you really don't own them so make sure to drives users to your own sites.
2. Build your own marketing lists - collect emails.
3. Own the customer information and data rather than just relying on a pixel that sends the data to Google and Facebook. 

Individuals

1. Have a back email solution - keep important contacts and emails in multiple places
2.  Keep backup of your docs, photos, videos etc. in multiple places - I keep them in Google, Amazon, OneDrive etc.
3. If you want to keep them in one place then have multiple account access so even if you lose one account, you have other admin accounts that can access them.

Do you really own anything?

You rent domains names, host sites and data in cloud owned by other companies. They can decided to shut it down for violation of terms. Your emails service provider sends emails on your behalf, they can take away your ability to email to your customers if you have too many spam complaints or other service violations. Your business or personal digital assets are stored with someone else, there is a possibility of you losing access. Isn't it? 

Anything else you would like to add? Share you experience in the comments below.

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Check out our online courses at Optizent Academy

Enroll in Digital Analytics Association's Essentials Series – Fundamentals in Digital Analytics

I am excited to announce that I will be conducting Digital Analytics Association's Essentials Series – Fundamentals in Digital Analytics. This is a LIVE, interactive, discussion-based education program that will be offered completely online, and only once per year. You’ll have access to me and fellow classmates through DAA's learning platform.

Register at DAA

When you sign up for the first Essentials Series Online course, Fundamentals of Digital Analytics, you will learn key competencies, and gain knowledge and skills in the areas of: data capture and measurement, reporting and forecasting, analytical business culture, site optimization and marketing campaigns.

So, what can you expect from your LIVE learning experience:

Register at DAA

Course 1 - Fundamentals of Digital Analytics is a series of 6 LIVE classes that are prescheduled, and will begin on Tuesday, April 14th. The courses will be held on Tuesdays and Thursdays from 12:00pm EDT – 1:00pm EDT with me conducting an “online class” format, allowing students access to a SME for Q & A and/or class discussion.

This will consist of: Coursework/assignments that will be completed weekly prior to the online class . Zoom technology will be used, and sessions will be recorded for accessing on-demand. Never use Zoom technology for your learning before? Check out the software and technology requirements to support this learning format. It will require a PC, Tablet, iPad, etc. that has audio and video capability. This will allow for the full, LIVE, virtual learning classroom experience.

What you will learn in the Fundamentals of Digital Analytics course: Whether you are new to web analytics, new to web management, or just need to be sure that you are seeing the forest for the trees, this is the best place to get grounded in the basics. In this introductory workshop you will learn about:

• Metrics terminology and technology
• Most critical web metrics
• Performance Indicators
• How to derive business value from web analytics
• The skills you need (or need to look for in others) to build a web analytics powerhouse
• A process for creating a web analytics culture and making it stick in your organization
• How to gain executive buy-in
• Insight into optimizing your business with web analytics
• Getting started with visitor data analysis

Class dates/times will be:

• Tuesday, April 14th, 12:00 pm ET – 1:00 pm ET
• Thursday, April 16th, 12:00 pm ET – 1:00 pm ET
• Tuesday, April 21st, 12:00 pm ET – 1:00 pm ET
• Thursday, April 23rd, 12:00 pm ET – 1:00 pm ET
• Tuesday, April 28th, 12:00 pm ET – 1:00 pm ET
• Thursday, April 30th, 12:00 pm ET – 1:00 pm ET
• Tuesday, May 5th, 12:00 pm ET – 1:00 pm ET (Make-up class if needed)

Upon completion of the course, candidates/participants will receive:

1. Certificate of Completion in the Fundamentals of Digital Analytics.
2. Digital Badge to promote to others your successful completion of this course.
3. Evaluation of the course, so we can continue to improve for future learners.

Pricing for Essentials Series Course I: Fundamentals of Digital Analytics:

Member: $850
Non-Member: $1050

How do I get started?

Take your career to the next level by earning a Certificate in the Fundamentals of Digital Analytics

Watch the recorded, pre-launch webinar CLICK HERE

Register at DAA

Google Tag Manager Book

I am pleased to announce that my first ever book is now available on Amazon.

Google Tag Manager - Zero to Hero

This book teaches you everything you need to get started with Google Tag Manager. The book is based on my best selling Google Tag Manager Course.

Reviews:

If you know nothing about Google Tag Manager, this is THE very best place to start. If you've been working with Google Tag Manager for some time, this book will validate what you know and unpack the complexities you've tripped over. There is no fluff in this book. It jumps straight into the details in the proper order and at the right speed for understanding and mastery. There are no wasted words - no wasted time.

I've known Anil Batra for almost 20 years through our relationship in helping create the Digital Analytics Association (DAA) and his speaking at my Marketing Analytics Summit. He has given lectures, produced workshops, and delivered online courses for the DAA (and other organizations), teaching thousands of students. All of them have given Anil the highest scores for his lucidity and the depth of his knowledge. Anil is that rare combination of knowledgeable, forthcoming, and accessible. Clearly, I am a fan.

 - Jim Sterne, Founder Marketing Analytics Summit & Co-Founder Digital Analytics Association

I have been a member of Anil's Udemy classes and Facebook group for quite some time. I bought the book because it is a great resource to refer to. Plus, it makes me smarter! He is an excellent instructor, you will love his presentation style.
 - Brenda M.

In this book I take you through various features of Google Tag Manager and show you how you can implement various Tags.You will go from not knowing anything about Google Tag Manager and Data Layers to mastering them and using them with confidence.

The book will cover the following topics

• Fundamentals and Essentials of Tag Manger (Applies to any tag manager) 
• Signing up for Google Tag Manager 
•  Details of Google Tag Manager Interface 
• How to setup Google Tag Manager for Google Analytics and track page views 
• How to setup external link tracking as Events in Google Analytics via Google Tag Manager
• How to setup Button click tracking in Google Analytics 
• How to track JavaScript errors using Google Tag Manager ( GTM) 
• Deploy GTM in WordPress Understand and use Data Layer in Google Tag Manager 
• Pushing dynamic values and custom event in DataLayer

You can order your book at Amazon or on https://training.optizent.com.  Get a video course of the same book at https://training.optizent.com


Not interested in Book? Signup up free Google Tag Manager course.

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Artificial Intelligence (AI) for Marketing 101

These days there is a lot of buzz in the marketing community about use of Artificial Intelligence (AI) and Machine Learning (ML) in marketing.

In this post I will cover some basics of AI that you need to know before you can explore how AI and ML can help you in your marketing efforts.

What is Artificial Intelligence? 

There are several definitions of Artificial Intelligence or AI. The simplest one to understand is from Oracle.com: "Artificial intelligence (AI) refers to systems or machines that mimic human intelligence to perform tasks and can iteratively improve themselves based on the information they collect."

So in a nutshell AI refers to machine, which can learn and become intelligent like humans.

AI is an umbrella term that includes algorithms, concepts, tools, technologies etc. that perform these complex human like tasks.

One of such and widely used concept in AI is Machine Learning.  Keep in mind that all machine learning is AI but not all AI is Machine Learning as AI include much more than just Machine Learning (ML).

What is Machine Learning (ML)?

Machine learning is the practice of using statistics to parse large amount of data (structured and unstructured), find patterns in it, learn from it, and then make a determination or prediction about something in the world. So rather than hand-coding software routines with a specific set of instructions to accomplish a particular task, the machine is “trained” using large amounts of data and algorithms that give it the ability to learn how to perform the task. (definition modified and adopted from: Nvidia).

Machine learning builds a mathematical model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to perform the task. (source: https://en.wikipedia.org/wiki/Machine_learning)

There are three major types of learning used to train these models - Supervised learning, Unsupervised Learning and Reinforcement Learning.

Supervised Learning

In supervised learning, the algorithm builds a mathematical model from a set of data that contains both the inputs and the desired outputs.
(source: https://en.wikipedia.org/wiki/Machine_learning)

Example: Predict churn propensity of a customer.
You can provide training data that contains customers purchase data, past behavior data (input) and then each customer is labeled if they churned or not. Based on this data, model learns what purchase and behavior data will cause all the customers to be labeled as "Churn Risk" or "Not Churn Risk".


Unsupervised Learning

In unsupervised learning, the algorithm builds a mathematical model from a set of data which contains only inputs and no desired output labels. Unsupervised learning algorithms are used to find structure in the data, like grouping or clustering of data points. Unsupervised learning can discover patterns in the data, and can group the inputs into categories. (source: https://en.wikipedia.org/wiki/Machine_learning)

Example: Uncover customer segments.
Unsupervised learning can help find various customer segments in your customer data using customer attributes, sales, onsite behavior etc.. This can then be used to drive better customer engagement and better marketing performance.

Reinforcement Learning

In Reinforcement learning, the agent (also called Machine, model or AI) is given a problem to solve and faces a game-like situation. It is given rewards for positive behavior and punished for negative behavior as it tries to solve the problem.. These rewards are provided by the developer of AI. The machine uses trial and error to come up with a solution to the problem. The developer does not provide the model any hints or suggestions for how to solve the game. It’s up to the model to figure out how to solve the problem and maximize the reward. The end goal is to make the model learn desired behavior that maximizes the total reward.

Example: Provide recommended products to customers.
Reinforcement leaning can be used to develop a online product recommendation engine.

Other Terms that you should be aware of

Structured Data

Data that can be organized in rows and columns such as Customer Demographics, Sales data, onsite behavior data etc.

Unstructured Data

Free form data such as word documents, call scripts, pdf, images etc. Anything that is not structured is classified as Unstructured data.

Marketing Uses of AI

There are several ways AI can be used in Marketing.  Here are some examples, this is not a complete list. I will add more articles in future to cover several use cases.

• Customer Segmentation
• Ad budget allocation across channels or by channel
• Content creation
• Chatbots - Which understands humans questions and then responds with appropriate response.
• Churn Prediction/Customer Retention
• Product recommendation engine

Hopefully this article provides some clarity to the confusion around AI in Marketing.

Your turn now. Are you using AI for marketing? If yes, how? If not then why not? What are the challenges. Let's talk.

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Search Engine Optimization with Google Analytics

There are several tools in the market for Search Engine Optimization (SEO). Some are free and some are paid. Google Analytics is one such tool, which is free.

I have developed an online course, that will teach how to use Google Analytics to get better at Search Engine Optimization (SEO).

Google Analytics provide lots of valuable information that you can use to your advantage and have higher ranking sites on Google, Bing etc.
This course also gives you an overview of Google Webmaster Tools also called Search Console and show you how you can get that data into Google Analytics.

What will you learn:

1. Understand which Google Analytics reports to use to get insights to improve SEO
2. Get insight into (not provided) keywords that show up in Google Analytics keyword report.
3. Get a quick overview of Google Web Master Tools (Google Search Console) and connect it to Google Analytics
4. Understand and use Landing Pages, Devices, Countries and Keyword reports from Google Search Console
5. Learn how to compare various traffic drivers showing up in Google Analytics reports.
6. Segment Organic traffic in your reports.
7. Get a free SEO Custom Dashboard template that you can use to develop your own dashboard and use it right away and wow your boss.

Sign up for this course at Udemy

or get access to all of Optizent courses (50% off First month) at https://training.optizent.com/p/full-access-to-all-courses/?product_id=1025897&coupon_code=FREETRIAL

Advanced Digital Analytics workshop at DA Hub on Oct 17th

I will be conducting a full day advanced digital analytics class at DA Hub in Austin on Oct 17th.

Do you have experience with influencing business change? Are you ready to move into reflective analysis that drives real return on investment for your company? Want to advance your career prospects? This course will help you deliver all of that.

This interactive full day advanced digital analytics course will give you practical tools to elevate your analytics skills. It will also help you transition into a thought leader within your organization. 

Building upon the Fundamentals of Digital Analytics, this course encourages participants to critically examine methods and metrics in ways appropriate for their specific business model.

Learn how to effectively communicate analytical data, best practices for site and campaign design, and examine campaign performance standards from the CFO perspective using control groups and simple predictive models.

Upon completion of this course, participants will be able to:

• Define gaps between measurement practices and business goals for the company 
• Create a framework for standardizing the evaluation of current performance measurements for website, search, display, email, affiliate and social channels.
• Understand how to effectively measure campaigns
• Understand how to find right opportunities for improvement and optimize them
• Provide feedback on the design, execution, and outcomes of testing efforts 
• Manage a results-oriented analytical culture adept at driving business change 

The course follows the Digital Analytics Association's syllabus and is endorsed by it. Participants will be awarded six Professional Development Units (PDU) towards their DAA Certified Web Analyst certification renewal credit.

This works shop will be held in Austin, TX on Oct 17th along with DA Hub. Register at https://www.digitalanalyticshub.com/us_2018/anil_batra?reg_type_id=19719

About DA Hub

DA Hub is bringing together top analytics professionals for in-depth idea exchange. Leading digital analytics and optimization practitioners come from across the US to discuss and share the latest developments, challenges and opportunities in the industry. It is a unique opportunity to be part of the conversation. With over 50 huddles to pick from, run by the industry’s foremost practitioners and only 160 places available, you should book your place for this year’s event to meet, learn, share and network.  Get details at https://www.digitalanalyticshub.com/us_2018/home?reg_type_id=19719

Register for this workshop

21 Metrics for Measuring Online Display Advertising

In this post I am listing the 21 metrics to measure the success of your display advertising.  Most of these are also applicable, with some variation, to other forms of advertising such as Paid Search, Social Media Ads, Print and email. I will cover these other channels and mediums in the future posts.

Note: This post was originally posted on 5/18/2014.
On demand by readers, I have converted this post into an eBook that can be downloaded at Global Analytics Academy  - Download eBook at https://global-analytics-academy.teachable.com/p/21-metrics-for-measuring-online-display-advertising

1. Impressions – It is the number of times your ad is displayed. The number by itself does not hold much value but it is a metric used to calculate other metrics and KPIs. Keep in mind that an impression does not mean that someone actually saw the ad, it just that the ad was shown on a web page/app.
2. Reach –This is the number of unique people (generally identified by cookies) that were reached by your ad. This number is always lower than the impressions because your ad is generally shown to same person (cookie) multiple times.
3. Cost – The total cost of running the ad campaigns.  This is calculated differently by different tools and organizations. Some use actual media cost while other use a fully load number that includes the agency cost, creative cost etc. Whichever number you use, be consistent in your approach. If you are going to do comparisons with CPC models such as Paid Search then I suggest using the actual media cost. Most of the publicly available benchmarks are based on actual media cost and are expressed in CPM (explained later in this list).
4. Engagement Rate or Interaction Rate– This applies to the Rich Media Ads, where a user can interact with the ad without leaving the Ad unit/widget.  Engagement Rate is the percentage of interactions per impression of the ad unit and is calculated as (Number of Interactions/Total Impressions)*100%.
5. CPM – This is the cost for 1000 Impressions of the ad unit. Display advertising is generally sold on CPM basis. (For more information on CPM, see  Cost of Advertising: CPM, CPC and eCPM Demystified).
6. Clicks – Number of clicks on an ad unit that lead to a person leaving the ad unit.  Keep in mind that a click does not mean that a person landed on the intended destination of the banner ad click. There are multiple factors that could lead to a click but not a visit to the destination (I won’t cover those here but am happy to discuss over email or a call).
7. CTR (Click though rate) – It is the number of Clicks generated per impression of a banner ad. This number is expressed as a percentage. CTR = (click/impressions)*100%
8. CPC – Cost per Clicks is the cost that you pay for each click.  Generally, display advertising is sold by CMP (see above), you can easily convert the cost in to Cost Per Click to compare it against other channels such as paid search. Cost per click is the effective amount you paid to get a click.  It is calculated by dividing the cost with number of clicks.  CPC = Cost/Clicks. Sometime this number is also referred as eCPC (effective Cost per Click).
9. Visits – As stated above in the definition of clicks, not every click turns into a person landing on your destination (generally your website). Visits measures the clicks that did end up on your site.  (For more definition of visits, please see Page Views, Visitors, Visits and Hits Demystified)
10. Visitors – Visitors metric goes one step ahead of the visits and calculates the number of people (as identified by cookies) who ended up on your site as a results of the clicks on the banner ads.
11. Bounce Rate – Is the percentage of visits that left without taking any actions on your site. It is calculated as Number of Visits with one page view /Total number of visits resulting from the display ads. (Bounce Rate Demystified for further explanation).
12. Engaged Visit Rate – Generally this is opposite of bounce rate (though you can have your own definitions of engagement).  It measure the quality of the visits arriving from your display advertising. You can calculate Engaged Visits as  (100 – Bounce Rate expressed as percentage).
13. Cost/Engaged Visit – This is effective cost of each engaged visits. It is calculated as total Cost divided by number of engaged visits.
14. Page Views/Visit – Page views the number of pages on your site viewed by each visit. With a lot interactions happening on one single page, this metrics is losing its value. However, for now, it is still a valuable metric for ad supported sites.
15. Cost/Page View – As above, this is valuable metrics for ad supported site to figure out the cost of generating on extra page view.
16. Conversions – Conversion is defined as the count of action that you want the visitors to take when they arrive from you display ads. Some examples of conversions are – purchase, signup for newsletter, download a whitepaper, sign up for an event, Lead from completions etc.
17. Conversion Rate  – This is the percentage of visits that resulted in the desired conversion actions.  Conversion Rate = Total conversions/visits*100. If you have more than one conversion actions then you should do this calculation for each one of the action as well for all the actions combined.  In case of Leads, you can take it one step further and calculate not only the “Leads Generation Rate” (Online Conversion Rate) but also Lead Conversion Rate, which is, Leads that convert to a customer divided by total leads generated.
18. Cost per Conversion – This is the Total Cost divided by the number of conversions achieved from visits coming via display ads.
19. Revenue – This is total revenue that is directly attributed to the visits coming from display advertising. It is pretty straightforward to calculate in eCommerce but gets a little tricky when you have offline conversions.
20. Revenue per Visit   – Shows the direct revenue achieved per visit originating from the display advertising. It is calculated as Revenue Generated from Display Ads divided by the total Visits.
21. Revenue per Page – This is useful for ad supported business models. This is sometimes expressed as RPM (Revenue per thousand impressions of ads) = (Total Ad Revenue/Number of page views) * 1000

Note: In addition to Clicks, you can also looks at View Through and calculate your other related metrics by view through.  View Through is sum of all the cookies that visited a page that showed your ad on it, and then landed on your site. The assumption, in this calculation, is that you landed on the brands site because of that ad exposure.

 Where can you get these metrics from?

• Impressions, Reach, Cost, Engagement Rate, Clicks, CTR and CPC data is available from your agency or ad server tool.
• Visits, Visitors, Page Views, Bounce Rate, Engaged Visit Rate, Conversion, and Conversion Rate are available in your Web Analytics tool.
• Revenue is available in either your Web Analytics tool or other offline sales database.
• Cost/Conversion, Cost/Engaged Visits, Cost/Page view and Revenue/page are calculated using data from multiple tools.

Questions/Comments?

Post Your Web Analytics Job

Digital Marketing Acronyms and Abbreviations Demystified

Marketing is full of acronyms and abbreviations, it gets confusing even for an experienced marketer to keep track of all these terms. So help you navigate through all these words, I have developed a mini-course that explains what various Digital Marketing Acronyms and Abbreviations mean (the short course cover acronyms and abbreviations starting with A, B and C). In this short course I am covering the following terms

• A/B testing
• AOV
• AI
• AIM
• AIDA
• AOR
• AOV
• ATD
• B2B
• B2C
• BR
• CAC
• CLV
• CMS
• CPA
• CPC
• CPL
• CPM
• CTR
• CR
• CRO
• CRM
• CTA
• CTR
• CX

Signup for the course at Global Analytics Academy

If you like my style of teaching and want to learn about more terms then signup for the full course, which is available for a discounted price for a limited time.
Sign up for Digital Marketing Acronyms and Abbreviations Demystified

I have various other great course and in the process of adding more. I also develop custom training for organizations and educational institutions. If you are interested in buying a licence for your organization then contact me at batraonline@gmail.com

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?