Just The Web Analytics Essentials, And Nothing Else

I think I’m on to something.

Ever since I was first introduced to search and digital marketing, I’ve been fascinated with analytics. Web analytics, media analytics, audience analytics, and most recently social analytics – I’ve become data-obsessed. There’s something strangely elegant about telling a communications story through data. Anyone who has ever walked into a meeting with a performance report full of glowing results knows exactly what I mean.

Since my column last week, which delved into the importance of whole customer analytics, I’ve continued to think about the types of data required for a comprehensive view of audience activity. My fear was, in advocating for multiplicity in analytics technologies, I may have come across as advocating for a bloated analytics stack. Not true.

Small Web marketing and data analyst teams don’t have the time to spend hours poring over data being generated by dozens of tools. It’s not practical, nor does it scale. However, there are a handful of data points, across each analytics tool, that are essential to accomplishing that goal of whole customer intelligence.



Specifically, I believe there are only a handful of data points across Web analytics that consistently need to be measured and understood. Given how Web analytics is often positioned, as the centerpiece to a larger data analytics suite of tools, maximizing its value is crucial.

So what's really essential about Web analytics? Across any website, in any industry vertical, what are the crucial elements to success with Web analytics? I think there are three:

1) Key Performance Indicators (KPIs) – The best analogy to smart KPI identification I’ve heard is, “You have to know where you’re going before you can know what to pack.”

It’s easy to dismiss KPI identification as a simple task. In reality, it’s challenging. It takes a deep understanding of an organization’s business goals, where it’s been and where it hopes to go. It also requires prioritization across product lines, business units, customer segments, and responses to competitive pressures. This complete understanding of the market, and an organization’s position in it, will enable marketers to determine website KPIs that are in line with overarching business objectives.

Having clear KPIs will then set the stage for meaningful Web analysis. Focus on KPIs; make them the center of analytics dashboards and metrics reports. Refine them as more is understood or the business environment changes.

2) Conversion “Events” – Conversion events are the range of micro- and macro-conversion activities present across a website. Key on-site actions operate as engagement “hooks” for visitors to indicate they are receptive to the content and offers presented across the website experience. Those hooks are typically identified once an organization has a clear understanding of website KPIs.

Conversion events represent actions that marketers care about. Track conversion events by referral source and spend time understanding the impact that micro-conversion events (for example, e-newsletter registration) have on macro-conversion events (such as ecommerce transactions). This will keep your data analysis sharp and focused, and allow you to avoid getting caught up in the tedium of detailed clickstream analysis.

3) Cohort-based Segmentation – The last component of focused, no-nonsense Web analysis is cohort-based segmentation. Cohorts are a way to discern insights based onWweb consumption patterns observed through segmentation experiments. I characterize these as “experiments” because of the assumption that some degree of segmentation has already occurred in the way a site was built (e.g. for professional and personal users), and how supporting digital media plans were crafted. Cohorts then, allow for further insights through segmentation.

Cohorts can take on many forms. How do last month’s visitors compare to this month’s? How do visitors from Texas compare to visitors from New York? Cohorts can even be built around the sequencing of referral sources (e.g., visitors who downloaded the mobile application before viewing the video, versus the other way around). Overall, cohorts examine segmentation criteria that are important to an organization.

For the time-pressed among us, committing to a thorough understanding of Web analytics essentials will uncover a majority of the actionable insights. And while I’m not ignorant of the benefits of using a Web analytics tool’s full feature set, I do believe that most Web analysts can safely place their primary focus on these three measurement areas.

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