The Shape of Web Analytics to Come

What will the future of Web analytics look like?

Last week, we posted about a new Twitter Web Analytics tool, which represents a logical next step for the micro blogging platform. But to those awaiting a more complete Web analytics tool measuring data from search engines and social media, the Twitter rollout represents just more of the same -- a partial view instead of a complete picture of your data online.

Joe Stanganelli, an blogger and online marketing consultant, commented on our boards: "There is far, far more to social analytics than we presently understand. The upcoming API sounds like more of the same-old-same-old. Something new, truly innovative, and truly revolutionary would definitely go a long way in the analytics arena."

So what would a more comprehensive tool do? I asked Stanganelli to help me create a profile based on our combined wish lists.

Mainly, Stanganelli says he'd like to see a tool that realizes the promise not only of measuring the number of brand and keyword mentions across the Web, including on social media platforms, but also tells us how visitors feel about those brands and keywords. He imagines a plugin that could work with a company's existing analytics software and mine data from the Web over months to uncover hidden trends and correlations.

I'll add a couple of less ambitious thoughts:

  • Integration. A comprehensive Web analytics tool should be able to integrate mentions of a keyword or brand name from across the Web, including on blogs and Websites, in chat rooms, in social media (Facebook, Twitter, LinkedIn, etc.), on social bookmarking sites (Digg, StumbleUpon), and on other sites (YouTube, PR sites, you name it). It should be able to display them on a single dashboard giving a full picture of mentions across the Web.

  • Isolation. The tool should be able to isolate given mentions based on various parameters or selected factors. For example, the tool should eliminate mentions of your brand by your marketing team or by those working with you, only displaying organic mentions.

  • Connection. The tool should display the connection or relationship between mentions -- say, the relationship between a blog post, the Facebook link where it was later shared, and then the Twitter posts where it was later tweeted and then re-tweeted.

  • Comparison. The tool should be able to combine these mentions into a graph showing the day-to-day, week-to-week, month-to-month, and even year-to-year occurrence of selected keywords, brand names, or other terms or information across the Web and to compare them in a variety of ways to identify any meaningful trends.

We've probably only scratched the surface here, and I'm sure there is much more that a truly comprehensive Web analytics platform could do. For example, could it measure Likes, votes, or any other positive (or negative) sentiments or comments associated with your content? How about tracking secondary keywords that might reveal sentiment and other more in-depth insight about the mentions being made?

What would your ultimate Web analytics tool look like? Share your thoughts on the boards below.

Shawn Hessinger, Community Editor

Shawn Hessinger is a community manager, blogger, social media and tech enthusiast, journalist, and entrepreneur based in Northeastern Pennsylvania. He serves as community manager and blogger for, a business news and information Website, and contributes regularly to the online business news source, Small Business Trends. He is the founder of, an online content and media community, and has provided blogging and social media services and consulting for companies all over the world. He researches and writes on a variety of business, Internet-related, and other tech topics including business intelligence and analytics. He is also keenly interested in computer-aided data management as it relates to his various online ventures. A newspaper journalist with more than 11 years experience as a reporter and then managing editor, Shawn began blogging in 2006 and now provides a variety of consulting and outsourcing services in Search Engine Optimization, Web development, and online marketing to companies large and small. He is a strong advocate for the use of BI and related computer data management in business decision making, whether using software as a service (SaaS), cloud, or other applications, and in the opportunity these technologies provide to transform small startups and larger established businesses alike.

BCBSNC, SAS Team on Advanced Analytics

The key to improving heathcare outcomes is to look at individual needs, the companies say.

Spoofing, Privacy Greatest Barriers for Biometrics

In Wednesday's e-chat, we discussed the analytics of identification and whether the technology might find a bigger role one day in marketing intelligence.

Re: Like
  • 9/21/2011 9:19:08 AM

Sounds like we're all in agreement, then. 


Re: Like
  • 9/20/2011 11:47:41 PM

Hi Joe and Beth,

What I'm suggesting is really just a starting point, a simple way to begin gathering social media and other Web analytics in one place. I put limited weight on Facebook "likes" myself or on other similar feedback, but it would be a launching point and a simple tool which is more than we have today...and perhaps a starting point for others who may push the envelope further.

Re: Like
  • 9/20/2011 10:09:18 PM

Joe -- being able to put a precise dollar figure on the value of having certain data and the associated correlations of that data, as you say, is indeed the ultimate goal -- and a monumental one at that. I tend to the a bit of a cynic when it comes to finding value in measuring likes, sentiments, and what-not in the social sphere today, but have no doubt that our methodologies and techniques will evolve, grow in sophistication, and get us closer to that ideal over time. 

Re: Like
  • 9/20/2011 2:12:16 PM

Hi, Shawn.

"...I feel like just tracking and graphing the important data across multiple platforms would be enough to start with."

That's just it.  Without context or an understanding of the meaning of these actions, one can't really be sure which data are important -- or why they are important.

The ultimate goal should be to be able to put a precise dollar figure on the value of having certain data and the associated correlations of that data.  Unlike other areas of analytics, we're not there yet with Web/Social analytics, but it can happen.

Re: Like
  • 9/20/2011 2:07:28 PM

Hi Joe,

One of the interesting things about this kind of exercise is that it is an important first step in thinking through some of the issues connected to how such a system might work. As for the "likes," well, you have to start somewhere. I'm really more worried about adequately tracking these mentions in the beginning than about trying to delve into the meaning of some of these actions. Maybe I am not being ambitious enough, but I feel like just tracking and graphing the important data across multiple platforms would be enough to start with.

  • 9/20/2011 12:07:46 PM

One of the problems with measuring "Likes" and their ilk is that you don't know why the particular item is being liked.

Likes (and the like) are often used as a way of bookmarking or keeping track of content (a great example is Netflix; after recent customer controversies, customers flocked to Netflix's Facebook page and Liked it, not because they actually liked Netflix, but because they wanted to voice their concerns and keep track of company messages).  Indeed, this is how I often use such tools myself.

Plus, for people who truly "like" something, you don't know what they like about it.  It is a context-less click of a button.

Currently, there is too much emphasis on Likes, Follows, +1s, and so on in social media analytics, and not enough focus on the stuff that really matters.

Thanks for this piece, Shawn.  It was interesting thinking about and discussing this with you.