Web Analytics Career Advice – How to Become a Web Analyst

I get dozens of emails every week from people asking for career advice in web analytics.

The questions range from ‘where do I start?’, ‘which books should I read?’, ‘how do I prepare for GAIQ?’ to how do I become a good analyst?.

So I thought why not dedicate a whole article on answering these burning questions and also ask the top industry experts about it.

Here is a snapshot of what you will learn from this article and that too from Industry experts:

# Should I go into technical or non-technical side of web analytics?

# Should I charge a fixed fees per project or should I charge by the hour?

# What sort of skills and qualifications are required to become a good digital analyst?

# What makes a good analyst a great analyst?

# What is the difference between digital analytics & Google Analytics and digital analyst & business analyst?

# Which blogs, books and conferences do you recommend to enhance analytical skills?

I am often asked this question:

Can I take your web analytics training course without coding knowledge / background?

Yes you can. My course is non-technical.

There are two facets of web analytics, one is technical and one is non-technical.

The technical side of web analytics

The technical side deal with implementation stuff: installing/ fixing tracking on a website.

You need pretty good knowledge of HTML, DOM , JavaScript, JQuery and considerably good knowledge of Google Analytics development environment in order to work as a GA developer.

In addition to that, you would also need a good understanding of the development environment of each of your target data source, in order to extract data from it (with or without Google Tag Manager).

For example,

If you want to extract Facebook data (like ‘Facebook likes) from a website then you first need to have at least basic understanding of ‘Facebook JavaScript SDK for website’.

If you want to extract Facebook data from a IOS mobile app then you first need to have at least basic understanding of ‘Facebook SDK for IOS’.

If you want to extract Facebook data from a Android mobile app then you first need to have at least basic understanding of ‘Facebook SDK for Android’.

If you want to extract Youtube data (like video played) from a website then you first need to have at least basic understanding of YouTube Player API.

If you want to extract twitter data (like tweets) from a website then you first need to have at least basic understanding of ‘Twitter JavaScript SDK’.

For ‘N’ data sources there could be ‘N’ JavaScript libraries.

You may need to learn and remember these JavaScript libraries.

Working knowledge of a server side language (like PHP) is not required but a bonus.

The non-technical side of web analytics

The non-technical side involves creating strategies, framework, conversion optimization, data analysis and reporting.

The non-technical side include maths and stats for web analytics.

The technical and non-technical side of web analytics

When you have to really deal with both technical and non-technical side is, when you are dealing with data science which is used in business intelligence (BI).

Business Intelligence is not web analytics.

It is a completely different field.

So do not get confused here.

You do not need to learn ‘R, ‘supply chain analytics’, ‘stakeholder management’,‘predictive analytics’ etc in order to become a web analyst.

Those who give you such advice are confused.

They can’t differentiate between BI and Web Analytics.

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Should you go into the technical side of web analytics?

Ask yourself following questions:

Do I have a strong coding background?

Was I a developer before I moved into web analytics?

Do I have the inclination and/or the capacity to learn to code for the foreseeable future?

Do I want to provide ‘done for you’ services for the foreseeable future? Where I do all of the work for my client?

If your answer to any of this question is ‘No’ then don’t go technical.

If you do, you are going to struggle and most likely will never reach your true potential.

Let me give you a brief intro of my coding background.

I grew up learning programming languages like C, C++ and VC++.

I hold a bachelors degree in computer science; have 5 years of hand on experience in C and C++ and 1 year of teaching experience.

I have been involved in technical projects all of my working life.

I deal with developers all of the time.

But I also have developed strong marketing skills over the years and I am also a business owner.

My company OptimizeSmart is a Google Partner.

I believe in being a full stack marketer and not just being a one trick pony.

Because of that I can see the forest for the tree.

I can look at the big picture which many one trick ponies can’t.

All of the people who give you advice to “go technical’ in web analytics have got strong coding background and are more or less one trick ponies.

They can’t think beyond that.

That’s their limitation.

They can’t really fathom the non technical side of analytics.

Their world revolves around JavaScript and setting up and fixing tracking issues.

That’s all they have ever done.

They truly believe that, what they do is website analysis.

But what they are basically doing is, development work.

It is a different type of development work but it still a development work.

Even when you have got adequate knowledge of HTML, DOM and JavaScript, you would still need the help of client’s web developers/IT.

This is because, if you are not familiar with the server side language used by your client and/or the client’s development environment or database, then you will need the help of client’s IT/web developer, to add server side code to your data layers or to query their database for you.

Without adding server side code to GTM data layers, you can’t implement / debug many of the sophisticated trackings like ‘enhanced ecommerce tracking’ in GA via GTM.

Thus you must also have the ability to communicate with developers in the language they understand.

When you work with them, they are going to ask you lot of technical questions under the assumption that you are already familiar with the technology they use.

Lot of seasoned developers from all over the world, are on their way to become GA developer.

And it is not very hard for them to quickly acquire the skills necessary because of their strong coding background.

As a ‘would-be Google Analytics developer’, you would be directly or indirectly competing with seasoned developers with decades of experience in coding from all over the world.

As a GA developer you are not very hard to replace, as skilled and cheap labor is easily available in other parts of the world.

You would be doing the work which can be easily outsourced to the third world for rock bottom price.

Therefore you will have hard time commanding a disproportionately large salary.

Other than that, technical projects usually do not last for more than couple of weeks.

Thus there is little to no possibility of generating monthly recurring revenue from a client.

You would need a constant flow of new clients each month.

As a GA developer, the only way you can scale your business is by hiring more GA developers.

But even after that, you will most likely max out after 10-20 clients unless you hire yet another person just to manage your employees / contractors.

Managing employees is a full time job in itself.

Long story short, if you can’t handle the headache of managing employees and/or running a big agency then you can’t grow/scale beyond certain point.

Should you go into the non-technical side of web analytics?

If you want a career which is both intellectually stimulating and financially rewarding, then learn and master the non-technical side of web analytics where you analyze data, carry out A/B tests, conversion optimization etc.

Because that kind of work is directly tied to improving the business bottomline and has got tremendous market value.

This is the kind of work which can not be easily outsourced to some guy in Philippines.

You will face less competition (in comparison to GA developers) and get more opportunities, as good web analysts / optimizers are still short in supply and great in demand.

No one is going to pay you tens of thousands of dollars for setting up enhanced ecommerce tracking.

Just forget about that.

But you might get a conversion optimization project, where you can charge say $40k.

The money is really in the non-technical side of analytics.

For majority of people, you would be better off, sticking to the non-technical side.

If you have to choose between working on your strength or working on your weakness then choose strength.

“It is far more lucrative and fun to leverage your strengths instead of attempting to fix all the chinks in your armor.

The choice is between multiplication of results using strengths or incremental improvement fixing weaknesses that will, at best, become mediocre.

Focus on better use of your best weapons instead of constant repair.”

– Tim Ferriss (4 hours work week)

Should you charge a fixed fees per project or should you charge hourly?

Allow me to tell you a little bit more about how I charge and why I charge that way esp. for technical projects.

I charge for my expertise and not for my time.

I charge a fixed fees from the client which is for producing the result they want and give them an approx. timeframe of the delivery of results (usually measured in weeks) without mentioning the number of hours it is going to take to complete the project.

It is not that I don’t care about the time involved but most of the time I already know the number of hours it may take to complete a particular task.

I have been in this business for more than a decade now and have worked with countless clients on countless projects.

And I never charged any client by the hour from the very beginning of my career to this date.

Billing by the hour is just as nonsensical to me as billing by the pixel, or by the line of code, or by the color.

They are arbitrary units of measure that have nothing whatsoever to do with the outcome of the work.

No client cares, how many hours you worked.

All they care about is the end result.

Besides, a client has no way of knowing whether you really worked that many hours and whether the task really takes that many hours.

Some people are able to complete the task within a hour which others may take days or weeks.

And I have seen first hand, how some developers are able to complete a particular task in few minutes while others take weeks to complete the same task.

It all depends upon their level of experience and expertise.

It is in your best interest to bill as many hours as possible.

And it is in client’s best interest not that to happen.

So you see there is a conflict of interest here which could result in dispute regarding the number of hours being billed.

I try to avoid all such headache by not charging by the hour.

It also limit my earning potential, if I charge by the hour.

For example, if I charge by the hour, I cannot justify charging hundreds or thousands of dollars for a 10 minute work.

If I do not charge by the hour, I can easily justify charging hundreds or thousands of dollars for a 10 minute work because then I am charging for my expertise and not for my time.

If I do not charge by the hour, I can take on more projects than I can realistically handle all at once.

I get the time freedom because I can give the timeframe of delivering results in weeks even if it is just few hours/days work (if done in one sitting) and the clients do not care how long it takes because they are not being billed every hour.

Web analytics career advice from top industry experts

Today I have the great honour of interviewing three of the most respected and well known authorities in the field of web Analytics: Jim Sterne, Neil Patel and Gary Angel:

Jim-Sterne

Jim Sterne

Neil Patel

gary-angel

Gary Angel

 

 

 

 

 

 

About Jim Sterne

Jim Sterne is the founder of the eMetrics Marketing Optimization Summit and co-founder of Digital Analytics Association.

He is an internationally known speaker and consultant to Fortune 500 companies and Internet entrepreneurs.

Sterne focuses his 20+ years in sales and marketing on measuring the value of a web site as a medium for creating and strengthening customer relationships.

He has written several books on Internet advertising, marketing, customer service, email marketing and web analytics.

About Neil Patel

Neil Patel is the co-founder of two internet companies: Crazy Egg and KISSmetrics.

Through his entrepreneurial career he has helped large corporations such as Amazon, AOL, GM, HP and Viacom make more money from the web.

By the age of 21 not only was he named one of the top influencers on the web according to the Wall Street Journal, but he was also named one of the top entrepreneurs in the nation by Entrepreneur Magazine.

He has also been recognised as a top 100 entrepreneur under the age of 30 by former US President Barack Obama.

About Gary Angel

Gary Angel is the CEO and Founder at Digital Mortar.

His ground-breaking work in hands-on web analytics includes the development of Functionalism, pioneering work in the creation of SEM analytics as a discipline and numerous methodological improvements to the field of web analytics and the study of online behavior.

He is the recipient of the Digital Analytics Association’s Award for Excellence as the Most Influential Industry Contributor.

What sort of skills and qualifications are required to become a good digital analyst?

Jim Sterne:

A good digital analyst needs three primary skills:

1. An understanding of the data. Where did the bits come from? What do they really represent? How trustworthy are they?

2. An understanding of the problem to be solved. What insights are useful rather than merely interesting?

3. An ability to communicate well. Valuable, useful insights are worthless if they are not shared convincingly.

Neil Patel:

If you want to be a good digital analyst, you have to be good with numbers. Your job would be to analyze the effectiveness of any digital marketing channel such as social media, mobile, or even email.

If you can’t figure out if a channel is profitable for a company and you can’t predict how it will grow 30, 60, or even 90 days out, you aren’t cut out to be a digital analyst.

Other than being good with numbers, you need to know how to use Excel and PowerPoint so you can help create a marketing plan for your director or VP.

Lastly you need to be able to provide insights. Marketers already have enough reports… they are looking for insights.

As an analyst you need to help the company gauge it’s overall performance when it comes to digital marketing.

Gary Angel:

If you’re just starting out, I don’t think there is a specific set of skills and qualifications that are required.

We hire a lot of “fresh out of college” employees to train and they have a wide range of backgrounds.

We’ve hired people with CS backgrounds, Econ, Math, Genetics, Psychology and even History. My degree is in Philosophy.

There are a couple of core skills we do look for.

We give our employees an Excel exercise and we give them access to SC or GA to do an analysis of our site (sans any training).

So we assume that people can learn how to navigate software on their own.

We assume that if they don’t know how to do something (and most don’t know how to do the Excel exercise at first), they can figure it out using the Internet and Help.

Figuring things out like that is definitely a core skill for an analyst!

In terms of the presentation, we look for people who can use the data to draw conclusions not just parrot back reports.

They nearly always get the inferences wrong (digital data is complex), but we’re much more concerned that they have the inclination to do that.

So from a starting perspective, the requirements and qualifications are very low.

But to become a “good” digital analyst? You have to know your tools fairly deeply.

Analytics is a craft and tools are the key to craft. You certainly have to understand the digital channel.

It’s a huge advantage to have built a Website, run a Google Adwords campaign, or created a social presence.

Effective measurement requires a largely intuitive understanding of these things that’s very difficult to create except by actual use.

Probably the most important thing is developing a feel for how the numbers work, which are important, and what doesn’t feel right.

The best way to develop that skill is repetition – lots and lots of analysis.

Finally, I think it’s very hard to become a really skilled analyst without having at least a few framework methodologies.

We teach our analysts stuff like Functionalism, Use-case Analysis, and 2-Tiered Segmentation not because they cover every situation (though they are frequently useful), but because they provide handy ways to think about digital behavioral measurement.

All my other answers are shorter… promise!

What makes a good analyst a great analyst?

Jim Sterne:

A good analyst becomes a great analyst when he or she is able to creatively put two and two together.

They understand the data and the problem well enough to invent new ways of respectively using them to solve it.

The great analyst has a strong imagination and enjoys playing with ideas.

Neil Patel:

As a great analyst, first and foremost you need to learn how to make decisions based off of data versus your gut.

In addition to that you have to understand how marketing can ramp up or down or maybe even be cyclical in some cases.

All of these factors affect how profitable a channel is and you need to determine if they are worth pursuing.

For example, if the marketing team started email marketing campaigns and you know that they are losing you money, you may want to cut the program, but before you do so you need to analyze the channel to get a good understand of when the data shows it can break even and what your long term return on investment will be.

Gary Angel:

The ability to focus on what’s important from a business perspective and the very elusive ability to leap from data to solution.

It’s simply mistaken to believe that data suggests action. Data suggests behavior.

The appropriate business action must be inferred and that inference is guided by but not the same as analysis.

What is the difference between digital analytics & Google Analytics and digital analyst & business analyst?

Jim Sterne:

Digital Analyst answers to questions about the success of all of the marketing efforts; not only which campaigns were getting the most attention, but which resulted in the most long-term value to the company.

They share analytics tricks with the business intelligence community, addressing more and more data streams from an optimization angle.

They use panel data, survey data, customer satisfaction data, retail sales figures, and even weather reports to create predictive marketing models and marketing dashboards for senior executives.

My conclusion: So according to Jim, you need to do lot more than Google Analytics in order to become proficient in digital analytics.

Neil Patel:

In a nutshell, digital analytics is the use of data and metrics to gauge the overall performance of a business in regards to their digital marketing efforts.

You can do some of the things with Google Analytics, but not all of them.

For example, Google Analytics can’t tell you the lifetime value of your customer, or the ROI of your social media spend.

With a lot of modifications/custom work to Google Analytics you can get it to provide you with some of that data… but it isn’t an easy task.

Gary Angel:

Confusing GA with Digital Analytics is like confusing a saw with carpentry.

As for the difference between a digital analyst and business analyst, I think the distinction is much less clear.

There are quite a number of analytic disciplines.

I know supply-chain analysts, health-science analysts, and trading systems analysts. Each has to have deep domain knowledge and they work with a somewhat different set of tools.

Digital analysts have a specific domain with all that implies, but I’m not sure there is any deeper divide.

Which blogs, books and conferences do you recommend to enhance analytical skills?

Jim Sterne:

The eMetrics Summit, of course!

Neil Patel:

One blog that I recommend reading is: http://www.kaushik.net/avinash/.

Avinash know the analytics space like the back of his hand and he has written some great books on it such as: Web Analytics: An Hour A Day, or Web Analytics 2.0.

You can also check out the KISSmetrics blog as we discuss digital analytics.

Gary Angel:

It’s not so easy to improve your analytical skills with any of these – though all are peripheral sources of interest. To really improve your skills you have to practice.

I really do think of analytics as a craft. If I was learning carpentry, it’s a safe bet that books, blogs, and conferences would be far down on the list of top learning activities.

I tend to think that books that are somewhat broader and outside our discipline are most likely to be interesting and useful.

I’m very partial to Stephen Jay Gould and a book like Full House is good reading for an analyst.

I’d also recommend the Fog of War – a documentary about Robert McNamara.

I think he was a brilliant analyst, and it’s fascinating to see how, with primitive tools, he was able to consistently make the leap to the vitally important points.

It’s also, of course, a commentary on all that go wrong with even brilliant analysis.

If your more literary, Zen and the Art of Motorcycle Maintenance is an interesting reflection on the importance of craftsmanship.

I’ve made these recommendations before – but they hold up because they are fundamentally about analysis and craftsmanship not short-term technologies or industry trends.

Naturally I’m partial to the X Change Conference as well. It’s a great place to really get to know fellow practitioners and talk at a pretty deep level.

I keep hammering the craft analogy, but the Conference is really designed to facilitate the kind of conversation, mentoring, and sharing that are necessary to craftsmanship.

What do you think were the most important developments in digital analytics?

Jim Sterne:

The popularization of Big Data. We’ve been doing it for years and now we have a name for it!

Neil Patel:

In 2012 software companies have been focusing on providing much more detailed insight on each individual customer.

For example, at KISSmetrics we don’t focus on tracking vanity metrics like bounce rates, instead we focus on tracking people.

This way you can get a better understanding of the lifetime value of your customers, or churn, or average time before a customer purchases.

If we didn’t have tracking that was based on individual people versus “visitors” we, as well as other software companies, wouldn’t be able to provide you with that data.

Gary Angel:

The emergence of a set of tools and systems for digital personalization.

For analytics to matter, it has to drive business change.

There’s many ways that can happen, but in digital none is more impactful or ubiquitous than personalization.

So while you could make a strong case for something like Hadoop being more important to analytics, in the long run, I think it’s the application of analytics and the opportunities created by personalization systems that is most important.

What do you think will be the key trends and challenges for digital analytics?

Jim Sterne:

The practical application of Big Data that will make people realize that, while the hype was fun, the actual, practical, tactical use of it is important.

Neil Patel:

As for trends I think there will be much more evolution to people tracking and how digital analytics are tracking individuals and showing that data in an easy to understand as well as actionable format.

As for challenges, I think companies are going to have data overload.

This means analyst need to do a better job of crunching data for others within the company, and software solutions need to do a better job of providing actionable insights so that analysts have an easier job.

Gary Angel:

Of a piece with my answer above, I think deciding who/what owns the customer profile in digital is going to be the decisive technology battleground .

The decision organizations make around that question will ultimately determine the whole shape of their technology stack and much of their organizational structure.

My views and tips

First of all I used the words ‘web analytics’ and ‘digital analytics’ interchangeably in this article. They are not really the same thing.

Web analytics is the subset of digital analytics.

When we talk about digital analytics we talk about digital measurement not just on our website but beyond it: mobile, social media, offline impact etc.

There is an old saying “you can’t manage what you can’t measure”.

For example you can’t manage marketing campaigns, if you can’t measure its performance. But what I have found after my stint in the world of digital analytics is that

you can’t effectively measure what you can’t manage”.

For example, if you are measuring the performance of a SEO campaigns, you must know how SEO works in the first place.

You must know about the latest and greatest in the field of Search. You must know all about: Google Panda, Penguin, Link Building, Authorship, semantic markups, best practices etc.

If you don’t then this lack of knowledge reflects in your recommendations which are the most important part of any analysis.

Without solid recommendations any analysis has no commercial value as it can’t move the corporate needle.

I have talked more about giving solid recommendations in the article: Excellent Analytics Tip #101: Getting your things done right now

Needless to say, marketing and analytics complement each other.

You can’t be good in either without a great understanding of both disciplines.

I also believe that you need a great understanding of statistics in order to be good in analytics.

I was suggested to learn the basics of accounting once, in order to hone my analytics skills. But I think this skill is more relevant to people who are into business intelligence.

Regarding preparation for GAIQ test, the best place to learn is Analytics Academy,  the second best place is Google Analytics itself.

Without practical knowledge you will have hard time passing this test.

Related Article: GAIQ Test Preparation – Tips from the Veteran + GAIQ Sample Questions

Blogs and books on web analytics

Following is the list of analytics blogs I recommend:

1. Official Google Analytics blog – must read blog to know the latest in the field of Google Analytics.

2. OptimizeSmart – I am biased here. But the blog is all about analytics.

Following is the list of analytics books I recommend:

1. Microsoft Excel Data Analysis and Business Modeling – This is my favourite book on data science. This is a great book to learn the statistics which really matter for digital analytics professionals. I highly recommend it to any existing/aspiring analyst.

2. Maths and Stats for Web Analytics and Conversion OptimizationI am biased here, as I am the author of this book. But this is only book ever published which explains maths and stats in the context of Web Analytics and Conversion Optimization.

3Attribution Modelling in Google Analytics and Beyond  – I am biased here, as I am the author of this book. But this is only book ever published on Attribution Modelling.

Where to start learning about Google Analytics?

Check out this resource page: Google Analytics Training Resources and Tutorials which list the articles you need to read, in order to quickly learn Google Analytics.

Another relevant article on a career in anaytics: One tip that will skyrocket your analytics career

Other article you will find useful: Beginners Guide to Maths and Stats behind Web Analytics

Learn about the Google Analytics Usage Trends Tool

The Google Analytics usage trend is a new tool which is used to visualise trends in your Google Analytics data and to perform trend analysis.


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Himanshu Sharma

Certified web analyst and founder of OptimizeSmart.com

My name is Himanshu Sharma and I help businesses find and fix their Google Analytics and conversion issues. If you have any questions or comments please contact me.

  • Over eleven years' experience in SEO, PPC and web analytics
  • Google Analytics certified
  • Google AdWords certified
  • Nominated for Digital Analytics Association Award for Excellence
  • Bachelors degree in Internet Science
  • Founder of OptimizeSmart.com and EventEducation.com

I am also the author of three books:

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