Articles written in May, 2013

May 29 2013

“Big Data”: What is it? And, more importantly, what can I do with it?

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These are just a couple of the questions that have been plaguing industries and enterprises worldwide since the “Big Data” phenomenon surfaced. By now, most of us have heard this buzzword/phrase that has been penetrating the minds of IT and analytics professionals alike. However, many organizations are still unsure how to effectively analyze and gain new insights from it. Luckily, there are expert specialists in this field who are eager to join and guide them through their journey.

What is “Big Data?”

I’ll spare you the formal definition and put it simply: “Big Data” is everything, and it’s everywhere. “Big Data” is defined by (at least) three ‘Vs’: Volume, Velocity and Variety. And you might even hear about a fourth ‘V’ depending on which “Big Data” solution provider you’re talking to.

  • Volume: Explosive data sets that can translate into terabytes; petabytes; exabytes; zettabytes;
  • zettabytes = as much information as there are grains of sands on all the world’s beaches
  • Variety: Any type of data coming from a multitude of sources – structured, unstructured, semi-structured; numeric, non-numeric; traditional, non-traditional
  • Fourth ‘Vs’ you might come across:
  • Veracity (IBM) — Accurate, truthful and trustworthy data
  • Variability (SAS) — Data flows that may be unpredictable, inconsistent and anomalous

Now that we have a better grasp of what exactly “Big Data” is, I’d like to explore some of the complexities and challenges companies face because of it, as well, as the opportunities it presents.

Challenges & Complexities

The size, requirements, boundaries and resources of an organization, as well as the industry it’s in, can dictate the adoption of “Big Data” in addition to which obstacles will prevent them from extracting high-value impact and gaining new business insights that were previously unattainable.

However, there are a few common challenges despite the nature of the business:

  • Technology:
  • An abundance and variety of data sources and the information collected
  • Inherent complexity in processing, management and aggregation

I intentionally left out a fundamental part of the “Big Data” definition when I talked about the three or four ‘Vs’ of this concept, but this is a perfect place to sneak it in.

IDC’s definition of “Big Data” embraces the hardware, services and software that integrate, organize, manage, analyze and present the data that is characterized by the ‘Vs’ discussed at the beginning of this post.

This is why new technologies and architectures, advanced tools and platforms are needed and are continuing to be developed. These appliances will allow enterprises to leverage “Big Data” and (you guessed it) analytics.

  • Skills: Shortage of finding “expert” talent
  • Technical: Data scientists with an unparalleled level of skill to understand the interactions of a new class of technologies
  • Analytics: Data mining; statistics; business analytics; problem solving; creativity
  • Funds: Investing in new technologies & skill sets without a full awareness of what it takes

Although there are some hindrances to enterprises fully embracing this new era of “Big Data” and analytics, there are evolving approaches to conquer them. For example, the Google Analytics Premium and BigQuery integration that will be taking place toward the end of this year was just announced at the Google I/O a couple weeks ago. If you’re a GA Premium user, I’ll venture to guess that this made you smile — even if you’re not 100% sure what it’s going to mean for your business.

Check back next week when I’ll discuss what value, advantages, opportunities and possible use cases can arise from utilizing more advanced technologies, solutions, and analytics strategies such as the “Big Data” movement. Stay tuned!

May 21 2013

Google Analytics is Lying to You!

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Let’s cut right to the chase: Google Analytics (GA) is lying to you. Huh? How is GA lying to you, you ask?

Let me illustrate, via screenshot, my beef with my old friend Google Analytics:

Can you believe that? I know I can’t. What’s that you say? You don’t see the lie? Let’s try that again:

Yes that’s it! Goal Values are not “optional”!

We all know that Google Analytics is the best thing since sliced bread; what other product could give you so much business intelligence at its price point (free)? Unfortunately, to collect data with Google Analytics one must only copy and paste the Google Analytics tracking code (GATC) onto their site and that’s where most businesses stop. To get the most from Google Analytics, code customizations; including events and custom dimensions are probably required. But most importantly–your company must sit down and answer some tough questions. Some of these include:

  1. Why do we have a website? (Really, you have to answer this.)
  2. What do we want people to do when they get to our site? (Desired outcome.)
  3. How do we measure these outcomes? (Goals in Google Analytics.)
  4. How much are these desired outcomes worth to our business? (Goal Value.)

If you need help with the questions above, please visit Avinash Kaushik’s brilliant post on the Digital Marketing and Measurement Model.

Okay, so you’ve answered the questions above, your marketing efforts have clearly defined objectives and you now know your reason for being; it’s time to set up your goals WITH goal values.

Goal Values again? Yes! (That’s the theme of this post, remember?) Ninety percent of the new GA accounts we review as a Google Analytics Certified Partner either do not contain goals or goals are present but goal values are missing. You must commit to ALWAYS adding a value for your goals. With values added, two magical things happen.

1. Per visit goal value is calculated:

What’s Per Visit Goal Value tell me? Well, at a glance it can tell you:

a. How effective each of your campaigns, sources, affiliates, ads, ad groups, and more are in real dollars!

b. How much you should be bidding for each keyword. (Really. Look at per visit value in the goal set view of your keyword reports.)

2. Page Value (Content Reports) is calculated:

Page Value tells you how each of your pages perform in the context of helping people convert. Now this data requires more analysis than Per Visit Goal Value because checkout and home pages will always have a high value, but it can help you understand which middle of the funnel pages perform best and help your visitors to take your desired action.

In summary, Goal values are not optional. You should always endeavor to understand how much goals add to your bottom line and add the values into GA. That said; if for some reason you find it too difficult to determine the value of key interactions– any number is better than nothing. So start with $100 or $1 or some other arbitrary value. From there you can work toward some relative goal values (e.g. contact us submission = $100, newsletter subscription = $10) and then hopefully as you gather more data, real goal values for each outcome.

Finally, there is one exception to this rule. Goals for Ecommerce transactions are desirable for many reasons, but if you are using GA Ecommerce tracking, then your corresponding goal should never have a value as this will distort the calculated values we mentioned previously.

May 20 2013

Google Analytics Premium Gets Interactive with BigQuery Integration

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Google Analytics Premium customers smiled a little brighter yesterday after one specific announcement was made at the Google I/O. An additional feature, Google BigQuery, is planned to become available to Google Analytics Premium users later this year.

Talk about a game changer. This goes far beyond just Web Analytics and opens the doors to a tremendous scope of opportunities. But, the basics are just amazing enough to make me anxiously call out a couple of them.

Access and query your Google Analytics data alongside and in combination with any of the other data sets your company derives for its business intelligence needs; all in a matter of seconds. I’m talking about trillions of rows of data right at your fingertips. Really, you can export the data, print it out and touch it if you’d like.

As if Web Analytics data isn’t multifaceted enough, there is an abundance of other data sets companies collect that are just as intricate and essential to running their businesses. With more and more organizations aware of the “big data” phenomenon, key stakeholders are starting to ask more complex questions and are leaning on their analysts for the insights to make better-informed business decisions. And they should.

This exercise can be daunting; exhausting; frustrating and sometimes near impossible. And, chances are most time is spent trying to query, join, and report on the correct data which means less time for true analysis to provide actionable recommendations to decision-makers.

The Google Analytics Premium and BigQuery integration is planned to ease these pains. It will provide granular data access for you to:

  • Join and cross-tabulate multiple data sources
  • Understand complex queries
  • Create detailed custom analyses
  • Identify what’s really going to drive and improve the bottom line

With so many possibilities, you can get lost in exploring them all. But, before you meander off on your own, make sure you get back to the boss on that request from…

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