Google Analytics Alerts: the start of a complete view?

By: Alistair Croll - November 26th, 2009  Filed under: Social Media, Twitter, Web anaytics, What did they do 7 Comments

Google Analytics recently added a new feature, called Alerts. At first glance, it’s an elegant way to show someone when a KPI on their site has changed significantly from what’s expected. It’s baselining, applied to all KPIs — even the ones you’re not looking at.

Daily Alerts - Google Analytics

This is a great idea for folks who forget to check their analytics data, because now they can find out about significant events. It tricks you into being a better analyst. It encourages baselining, segmentation, and thinking about your business. But we think it’s the start of something bigger, once it incorporates the things Google and others know about your online presence.

Details, and some juicy UI mockup speculation, after the jump. [Read More]

How Twitter’s Retweet creates Pagerank for humans

By: Alistair Croll - November 20th, 2009  Filed under: Social Media, Twitter, What are they saying 9 Comments

We’re finishing a busy week in New York, with presentations at both Web2Expo and Interop New York. We had a great time running our first Communilytics Boot Camp, and O’Reilly’s bookstore sold out of our book.

The Communilytics stuff was really interesting; we proposed a new “long funnel” model that incorporates both community metrics (such as followers, amplification, and the like) and traditional analytics (conversion rate, checkout value, and so on.) It’s a holistic approach, and we’ll write it up here soon.

We also looked at message propagation in communities a bit. Here’s a clip from the session, which discusses how the combination of Twitter’s formalized Retweet and an understanding of relevance can create “pagerank for humans” in microblogging platforms that share Twitter’s asymmetric-follow pattern.

Completely independent of this, Alex Bowyer over on Bitcurrent wrote a thoughtful piece on how Twitter should have formalized Retweeting, and some of the issues with the current model.

Unfortunately, there’s some strangeness going on between Youtube and Keynote’s video export, so the last 30 seconds of this are clipped. Basically we make the point that this is how to monetize microblog analytics, either by selling sentiment propagation analysis, finding out who influential proponents and detractors are, or knowing where to display ads and to whom.

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International stores, video advertising, and the Windows 7 launch

By: Alistair Croll - November 10th, 2009  Filed under: How did they do it, Web anaytics, What did they do, WIA 5 Comments

We’re in Amsterdam this week, presenting at a Measureworks conference on web performance and optimization and attending a Tweetup.

Our host, Jeroen, told us yesterday that since the introduction of GPSes in Amsterdam, traffic accidents in the narrow-streeted city have risen significantly. Many people are focused on their instruments, rather than looking around them. This made me think of some issues I’d seen with web advertising recently that would have been hard to detect through instruments alone, and underscored some of the shortcomings of a purely instrument-driven analytics approach.

Microsoft Canada's website for the Windows 7 launchWith much fanfare, Microsoft launched Windows 7. By many accounts, it’s a good operating system, despite the widely derided launch parties they tried to encourage (which, to be fair, did get people talking about the launch.) The launch involved a massive online ad buy, as well as a new online store for the company. Two aspects of this launch caught my attention: The differences between regional stores, and the state of video advertising.

[Read More]

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Guest Post: How much is enough when it comes to Voice of Customer?

By: Jonathan Levitt - November 2nd, 2009  Filed under: Building a new site, startup, VOC, What are they saying, Who's talking?, Why did they do it 8 Comments

jl1Jonathan Levitt has spent the last 5 years as a pioneer in the voice of customer analytics space. Through his speaking, writing, and evangelism, he was instrumental in legitimizing voice of customer analytics at a time when traditional web analytics still dominated the online business intelligence conversation. Jonathan has worked with world leading brands like Bank of America, Verizon, Dell, Procter & Gamble, Ford, and Reebok and has been featured in several industry publications including 1to1 Magazine, ClickZ, DM News, and MediaPost.

One of the best sources of business intelligence for companies of any size is raw Voice of Customer data.

This is particularly true for start-ups, where early, frequent, and consistent interaction with customers is critical to getting off the ground. The more customer-centric your decision making processes are from day one, the more likely you will get to the next stage in the development and maturation of your business plan.

This explains the recent growth in the selection of free and low cost Voice of Customer collection tools. User Voice, Kampyle, Survey.io, 4Q Survey (disclaimer: I helped conceive and build 4Q) — all of these are examples of popular Voice of Customer collection tools that can provide site owners with a pipeline of cheap and actionable visitor-sourced insights.

Once you put on the VoC practitioner’s hat, however, questions about respondent count size inevitably come up. Simply put, you need a way of knowing how much data is enough.

At what point can you act on the findings coming through your shiny new tools, with full confidence that you have collected a representative sample of your audience? If you’ve been running a User Voice customer feedback tool for 3 weeks and you’ve only collected 20 respondents, is that enough to act on? These are certainly agonizing questions for a data-centric marketer.

Now’s the time to start glancing over enviously at the big sites, because they don’t have this problem. The laws of probability are such that feedback from 500 respondents is usually enough to deliver reliable data at even the strictest confidence intervals. A big site like Dell.com can pull in 500 respondents within a day or two; at that clip, statistical significance comes through in a heartbeat.

But since your traffic generation muscle isn’t likely to match Dell.com’s anytime soon, I’ll let you in on a little secret: for small, startup websites that want immediate answers to their questions, the size of your sample almost doesn’t matter.

Here’s why. [Read More]

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