3 Key Trends for Web Analytics in 2012

Web Analytics Trends

Cardinal Path articleLast year, around this date, I contributed to Klaas Knook's Four Web Analytics gurus on key trends in 2011 at Search Engine Land. I caught myself referring back to this article in a recent conversation and thought it might be worth revisiting it. It also struck me how privileged I was of sharing my thoughts alongside the likes of Avinash Kaushik, Jim Sterne and Dennis Mortensen, for whom I have utmost respect.

1. There is no such thing as Social media ROI

Social Media ROI

In early 2011, my rant was about the risks of a "social media bubble" and I think it holds true to this date. ROI of social media remains mostly anecdotal; yet, disproportional resources are spent trying to improve such soft metrics as brand awareness, reach, resonance, generosity, influence... and a boatload of unstandardized, secret formula metrics. All this energy spent while on-site business processes often fall short of being optimized.

I have done several workshops on social media ROI and honestly, for most organizations, social media remains an acquisition channel leading traffic to the website. Simply put, I believe social media ROI can only exist when measured and clearly correlated against clearly defined business outcomes, be it on the website or offline. I'm a big proponent of online process optimization, so I often wish focus would be a little less social and a little more about process efficiencies.

2. Big Data & more than Big

Big Data

"Big data" is a buzzword which emerged in the 3rd quarter of 2010 and gained momentum by mid-2011 (as can be seen in the chart below, extracted from Google Trends). Traditional business intelligence (BI) is too cumbersome and tedious; on the other hand, web analytics in itself lacks core business data integration. In the coming months, expect all web analytics vendors to sprinkle "Big Data" everywhere they can & it has already started and sometimes it's a long stretch.

Big Data Trend

More seriously, the ecosystem of data integration tools, powerful & flexible analysis, visualization and effective communications that are being built around Big Data will significantly impact the online analytics space. It won't matter if your dataset is "big" or not, what matters the most is your ability to analyze and tie back your recommendations to the business.

I believe the slow death of traditional BI and web analytics as a distinct discipline is inevitable & expect more discussions around the fading frontiers of web analytics and the growth of business analytics.

  • If the comments on The Ultimate Definition of Analytics I wrote at Online Behavior is any indication, it is clear web analytics isn't well defined and is in search of a more appropriate home.
  • John Lucker, Principal and Global Advanced Analytics & Modeling Market Offering Leader, wrote a very good piece entitled Business analytics: fad or fundamental? (link to pdf). Definitely worth a read.

3. Privacy - let ME tell you what I want YOU to know

Online Privacy

The third trending topic is bound to be Privacy. While a lot of attention is justifiably spent on protecting user privacy - think EU directive - many a lot are happily sharing personal details through social media & think of the FTC probing of Facebook (article from Pierre DeBois, December 29th).

We can expect a growing number of biased, one sided views from the press where facts are intertwined with sensationalistic statements (think of headlines such as How companies learn your secrets). We can keep winning, trying to educate our audience, but ultimately, our responsibility as analysts is to abide by strict ethics of transparency and respect of our audience desire.

I envision innovation at both ends of the spectrum: cookieless tracking through browser footprints on one end, and greater transparency and user control through innovative solutions such as the one proposed by The Cookie Collective (thanks to Dave Chaffey for his excellent post on the topic at Smart Insights).

If we thought web analytics raised privacy concerns, you can expect more articles raising concerns over Big Data. As McKinsey puts it:

Several issues will have to be addressed to capture the full potential of big data. Policies related to privacy, security, intellectual property, and even liability will need to be addressed in a big data world. (Big data: The next frontier for innovation, competition, and productivity, McKinsey Global Institute, May 2011)

Wishful thinking

I wish 2012 will be the year where web analysts break out of the marketing, web-centric mold and mature to become business analysts of a new generation. Based on the vivid discussions around a simple topic such as a definition of web analytics and the skills involved, I think we have plenty of opportunities to learn, share and collaborate. The frenzy around Big Data will impact us. Analytics will remain a sought for job, let's make 2012 a year of progress and keep having fun doing it!

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Chris G | March 2012

wow, Stephane, this is even above your usual level of telling it like it is. I will be showing this to other people - couldn't agree more on several of your points. Thanks.

Shalin Shah | April 2012

As companies gather greater volumes of disparate kinds of data (i.e., Both structured and unstructured), they are also looking for solutions that can scale. This kind of data includes data generated by social media activity streams, existing ERP systems and network data. Real-time analysis of large amounts of data is becoming more prevalent. For example, communications service providers need real-time visibility into activation system service orders, showing activation times and lists of potential exceptions. Or, Internet service providers need real-time visibility across field work operations to improve the management and prioritization of work orders, installer schedules and maintenance requests. The recent buzz around “Big Data” solutions is growing louder, but only Operational Intelligence solutions are purposely built for analyzing Big Data.

Geo George | May 2012

Big data is relative - 10 years back - my first job handling a 100 thousand unique users and their 5 visits per month was great big data for the channel i was responsible . when it grown to half a million in 6 months it was really Big to . hande

later i handled portal products that handled over 30 million UUs a day and over a billion transactions every week. Worked on Projects where the lading bank and a multi-partner loyalty program put together was woth a min 100 billion transactions a month - thats a crazy BIG data .. but the beauty is in segmenting and taming the monster - simplify clusters create performing samples and build value props - there we are in track

S.Hamel | May 2012

Totally agree George - imagine: over 20 years ago I was DBA, sysadm and advanced developer in a research team working on mapping observations from hundreds of instruments installed in dams (temperature, pressure, inclination, humidity, visual observations, etc.) - each with hundred of thousands of data points - over a period of 40 years... We were using Oracle and 2D dams blueprint in ArcInfo GIS to map the observations in 3D! We never called it Big Data but it was a very complex scenario!

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