Digital Analytics As a Career Evolution for BI Analysts

Business Intelligence and web analytics have historically operated in separate spheres – BI systems and analysts focused on data from CRM, ERP, and POS transactional systems that has been fed into an enterprise data warehouse, while web analysts have lived in their own silo of semi-anonymous site visitors. Many companies have some sort of link between their web site and their backend systems – be it site registrations fed into the CRM or eCommerce transactions fed into the backend fulfillment and billing systems. But, because much of the traditional data warehouse data in an enterprise is focused on the identification and analysis of individual customers and prospects, and because web analytics systems are historically content-centric, the two worlds exist as separate planets in the same universe.

This is all starting to change, and, for this very reason, a background in BI and customer analytics is a great launching pad for a career in digital analytics.

What the BI Analyst Has in Common with a Digital Analyst

In many ways, all successful data analysts are similar, regardless of whether they’re working with traditional BI data or if they’re working with web analytics data. They’re similar to each other, but they’re unique with respect to non-analysts, in that they have a combination of key skills and talents:

  • They’re inherently curious and seek out problems that need solving and questions that need to be answered
  • They’re able to translate business problems into hypotheses that can be tested using data
  • They’re able to take the results of an analysis and make tangible, implementable recommendations that impact the business
  • They’re comfortable with data technology and data terminology – working with tools that are designed for data exploration, and, in most cases, working with a combination of tools to extract and analyze data
  • They understand the basics of relational databases and easily see opportunities to join data across different data sources and different dimensions
  • They understand that data is never pristine, and they’re able to make appropriate judgments between material and non-material data discrepancies

These are critical traits for successful analysts to have regardless of the type of data being analyzed, yet the people who possess them remain scarce.

The Valuable Perspective that a BI Analyst Brings to Digital Analytics

At the same time, BI analysts bring unique expertise that many pure web analysts have not had the opportunity to develop:

  • They’re used to working with true “enterprise data” – the data that successful organizations pump into their enterprise data warehouses from their CRM, ERP, POS, and other transactional systems
  • Because they are used to working with truly cross-functional data, they often have a more complete view of “the business,” including interrelated offline and online marketing and sales processes
  • They’re likely to be comfortable working directly with customer data – customer lifetime value, householding, loyalty program drivers, in-store purchase behavior, customer segmentation, and so on

While web analysts are certainly capable of developing this knowledge, they often “grew up” in their careers with a very web site-centric view of the business, so, for them to develop that knowledge requires the evolution of their company’s organization (to bring digital analytics into the realm of BI) and/or finding business users who are looking to solve business problems that clearly require cutting across data silos. All too often, neither of these situations present themselves, and even the most highly motivated of digital analysts is often not able to broaden their exposure.

Gaps a BI Analyst May Need to Fill

While BI analysts bring a lot of value to the world of digital analytics, there is still some degree of a learning curve for them to ascend (the innate curiosity of any good analyst makes this an exciting challenge rather than a foreboding prospect):

  • They’ll need to learn “the physics of the internet” and the mechanics of the different ways that digital activity can be captured – how a web page actually passes from a company’s web server through the internet to then be rendered in a user’s browser, how cookies work, how Javascript collects data and passes it to the web analytics platform (in a tag-based solution), and so on (the emergence of social media sites has not changed the underlying fundamentals of how the internet works, so, for the foreseeable future, a solid grounding in the under-the-hood mechanics of web sites and web analytics will remain a key foundational skill)
  • They’ll need to become comfortable with rapidly shifting processes – while a call center process may see a major change every 2-5 years, a web site can constantly evolve, which is both challenge for data continuity and an opportunity for the analyst to drive the collection of new and valuable data
  • They’ll need to get comfortable with messy and fluid “person” data – while web analytics platforms track individual visitors (the degree to which individual visitor data is available varies by platform), that tracking across sessions relies on well-aligned stars (read: persistent cross-session cookies), and the types of common keys that can link a CRM system to a POS system rarely exist when linking digital analytics data across digital channels and across devices
  • They’ll need to get comfortable with data that the company doesn’t own or generate through company-driven processes – social media has opened up a world of additional digital data for analysts to dig into, but the structure, nature, and availability of that data varies widely across different social platforms

None of these are particularly difficult capabilities for BI analysts to develop. After all, even traditional analysts who start out their analytics careers in web analytics had to develop these competencies.

Surfing the Tsunami

The volume of data being generated by companies and consumers alike continues to grow exponentially, and the need to integrate data across channels is an imperative that is visible on the horizon and approaching rapidly. As companies increasingly begin to combine their site-side behavioral (web analytics) and attitudinal (voice of the customer) data with their backend systems, the opportunity for BI analysts to step forward and embrace this wave of digital data while bringing their unique expertise to the table is growing.

By Tim Wilson
Director of Measurement and Analytics

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2 Responses to Digital Analytics As a Career Evolution for BI Analysts

  1. April Wilson says:

    Great article, Tim. One thing I’d like to add is putting the BI Analyst through some kind of customer service or marketing training. A lot of what we do as web analysts is advocate for the customer experience, which is a skill that’s also less developed in BI analysts.

  2. Vinita Deo says:

    I am a traditional market researcher with a lot of expereince in custom research as well as secondary research and data analysis. I am also very familiar with the output of on-line listening tools. i would like to become a digital analyst – what do i need to do? i was considering signing up for the Google Analytics 101 seminar. Would that be the right next step?

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