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Are Your Twitter Analytics Tools Just ‘Data Puking’?

If there’s one thing Twitter lends itself to (OK, two things, if you count brevity) it’s metrics. Twitter data can be sliced, diced, charted, graphed and turned inside out. But according to Google Analytics evangelist Avinash Kaushik, most of this data is useless for determining the value of your Twitter efforts.

In a very long but fascinating post on his Occam’s Razor blog, Kaushik quickly defines the problem:

Analysis of new social media channels has been hobbled by old world thinking, when it comes to marketing, from the world of Television and Magazines or, when it comes to measurement, from the world of traditional web analytics.

These new channels, twitter and facebook and youtube and tumblr and, yes, even blogs, are very distinct customer/participant experiences. Stale marketing or measurement thinking applied to them results in terribly sub optimal results for all involved.

graphedge_legitimate_followers2.png

Absolutely true. The problem with being able to grab and bang out Twitter data is that most of it merely measures activity, not effectiveness. Or as Kaushik writes:

Most twitter analytics tools just do data puking. They find numbers that can be computed and then proceed to puke at you as many as they can find, with wonton disregard of value being provided or outcomes being measured.

Hailing a “massive proliferation of new thinking,” Kaushik goes on to discuss four Twitter analytics tools that he believes “look promising.”

The four are:

Klout — attempts to measure reach, demand, engagement and velocity

GraphEdge — measures legitimate followers (see graphic), churn rate

(Note: The next one wins today’s “It’s a Little Freaky” award.)

TweetPsych — Kaushik: “uses the Linguistic Inquiry and Word Count (LIWC) method and the Regressive Imagery Dictionary (RID) method to build a psychological profile of a person based on the content of their last 1,000 tweets”

Twitter StreamGraphs — visualizes word associations

As I said, Kaushik’s blog post is long, but he really drills down. If you’re into analytics, it’s a must-read.

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