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Beyond Google Analytics – Making Sense of the Web Analytics, BI, and Big Data Space

How to bridge the advanced analytics knowledge gap

Today's marketing industry is becoming more metrics-driven by the day. If you're a marketer setting up a digital marketing campaign, one of your first major steps involves building a solid marketing strategy (see our toolkit that helps you do this), while becoming familiar with Google Analytics is a typical next step (see our GA toolkit).

But once you get your web strategy going and feel more comfortable with Google Analytics, you might notice that your day-to-day work demands a deeper understanding of user intentions, preferences, and usage patterns. You might begin to ask questions about your users that are more difficult to answer, such as which paths users take on your website, how to do advanced segmentation, how to correlate data outside of Google Analytics, and so on.

Marketers today are awash in customer data.  Knowing what an individual consumer is doing where and when is now table stakes, and the ability to integrate that data with knowledge of why they’re doing it… yields new insights into consumers’ needs and how to best meet them. This is according to a study by EffectiveBrands in partnership with the Association of National Advertisers, the World Federation of Advertisers, Spencer Stuart, Forbes, MetrixLab, and Adobe (summarized by HBR)

These complex questions can only be answered with the help of advanced Google Analytics features and additional tools, such as customer experience, session recording, heatmap, and BI tools. Getting to know these new technological areas is crucial in order to gain a deeper understanding of what users are doing on your website and how to improve business results. But there is a major knowledge gap between basic (or even proficient) Google Analytics usage and this additional set of technologies.

To move forward and grow as a digital marketer, your next step entails becoming more familiar with the entire space of web analytics, customer experience, BI/big data, and more. You need to get a feel for the different technologies and methodologies, which to choose, and how to utilize them correctly to answer your burning questions.

Here are 5 ways to help you bridge the knowledge gap:

Get started with web analytics:

Whether you eventually plan to branch out into a professional web analytics career or just need to become more knowledgeable about web analytics techniques and technologies, some basic first steps include picking your first web analytics tools, reading a few leading books and blogs (and possibly an official course), and getting some hands-on practice. See Avinash Kaushik's post on how to do this.

Learn about BI and Big Data:

While it's important to get an idea of the BI and big data space, finding comprehensive online reading material that offers an overview of BI/big data, as opposed to a tool-specific discussion, isn't easy. One solution might be to take a free course to get a feel for the main concepts, central questions, and basic terminology in these areas. See this list of free courses by edX and Coursera (including courses by the University of Colorado and the ESSEC Business School).

Become Familiar with Prominent BI Tools:

Even though BI technologies might seem overwhelming, becoming familiar with a few leading BI tools and understanding how they can be leveraged for marketing purposes might also be a way to get acquainted with the world of BI. See this article about BI tools for marketers with Technophobia.

Plan for data-driven marketing:

Becoming familiar with data-driven marketing is also an important piece of the puzzle. Based on a recent article by Marketing Land, marketers need to understand how to apply data science methods to available data, and trends such as automated data-driven engagement and using a combination of creativity and science might be the answer.

Understand the structure of the space:

Having a mental map of the topics and resources that exist in the space can be a big help in bridging the knowledge gap. Even if you can’t read everything, knowing which topics are important and which are the important resources for each topics can be a big time saver. One way to get started in this direction is to navigate the content tree of the Web Analytics & BI Wiki, which includes a structured list of topics and resources in areas such as digital marketing, web analytics, BI/big data, customer experience technologies, and so on.

 

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