Recent reads – using data

The Birth (And Death) of Market Research: Why Design Research Will Prevail (Sam Ladner)

This article suggests that summary statistics relied on by market research companies are no longer relevant and qualitative research of the long tail is where the money’s at:

  • “Design research uncovers how long-tail niches develop and what differentiates them.”
  • “…design research is about knowing what to build as well as evaluating the prototype.”

When Data Gets Up Close and Personal (Stephen Anderson)

A good contemplative piece about tracking performance and creating feedback cycles. As an example, Stephen has considered how you could make a “game” out of email by considering motivating factors and presentation of progress.

  • “What we’re really talking about is setting up systems whereby individuals can (1) see in a tangible way (2) reflect on, and (3) learn from their past behaviors.”
  • “Get creative with how you represent the data– our brains will thank you for that with extra attention.”

The 4 Big Myths of Profile Pictures (OkTrends – Christian)

Well… the post is about dating site profile pictures, but I think that it’s a good showcase for data analysis. They’ve done extensive research and they’re using it to give advice to their users = users get more successful results from the site = spreading the word to friends = more money for the business.

The 2 in 100 who might matter most – your core web audience (Seb Chan)

Seb Chan from Sydney’s Powerhouse Museum provides an example of how he looks deeper in to the museum’s site traffic data to realise that 2% of people are visiting the site 10 or more times in a quarter.

  • “Whilst we all like the big figures of casual visitors we get to our websites many institutions, having flirted with social media, we are beginning to realise that casual visitors, much like casual visitors through the door of a museum, aren’t so useful for building sustained co-creative relationships with.”
  • “This 2.10% is one that needs a lot more analysis as does the ‘5 or more’ category. How do they arrive at our site? What are they looking for? What do they spend most time looking at?”

Analysis Ninjas: Move Beyond The Top Ten. Find Love (/Insights) (Avinash Kaushik)

  • “You know what is the one thing stopping you from finding truly actionable insights from your web data? Web analytics gems lie deep in the data and we spend our lives looking at the top ten rows of data.”

This article encourages investigation of the long tails in site traffic data to pin-point opportunities and shows how to make sense of what at first might seem like data overload. Avinash provides examples of how to apply advanced table filtering in Google Analytics, generate tag clouds (I’ve given this a try with a client’s search keyword data and it sprouted some very useful visuals), and how to set up keyword trees with Juice Analytics.

Back to Basics: Tip for exporting rows (Google Analytics blog)

This is a brief tutorial to show that while Google Analytics allows you to export up to 500 rows of data normally,   to export more (eg. all your search keyword terms) you can add &limit=xxxx (where xxxx is a number more than the total number of results) to the URL and then download the CSV to retrieve all the data.

Charting the Beatles (Michael Deal)

Beautiful infographics [swoon] !

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