Twitter, The Analytics Provider And Data Mine

I will admit that I do not agree with Michael Arrington very often. He tends to be a bit of a sensationalist, but I guess that goes with the news territory. However, he wrote something this morning that I completely agree with, and I do not think he went far enough. Twitter as a search engine is a good start when thinking about the type of revenue that Twitter could generate. Arrington also gives us a money quote:

More and more people are starting to use Twitter to talk about brands in real time as they interact with them. And those brands want to know all about it, whether to respond individually … or simply gather the information to see what they’re doing right and what they’re doing wrong.

Disappointingly, he mostly stops with the amount of ad revenue that search can generate:

All they have to do is keep growing the base and gather more and more of those emotional grunts. In aggregate it’s extremely valuable. And as Google has shown, search is vastly monetizable – somewhere around 40% of all online advertising revenue goes to ads on search listings today.

He does mention that brands may want this information and Twitter can “tax the utility they are bringing to brands”. However, this is the area that could generate more revenue long term. Significant ad revenue requires a large amount of traffic. Analytics and data mining are things that can be brought to the enterprise or large brands. This may not be really sexy or exciting, but I said yesterday that boring is profitable. Granted, I am a little biased on this topic. I have always been involved with data. I used to do a lot of data warehousing. I have done enough academic research in data mining to know that there is money to be found there if done right.

The key in the Twitter data is that it is fairly simple. Each tweet is a maximum of 140 characters. There may be millions of tweets, but the number of variables you are dealing with is minimal. There are times of day measures, like the most active time of the day or even the most active day of the week. People are coming up with retweetability measures, mostly from the ego perspective, but people will eventually look at the data being retweeted. What constitutes retweetable content?

In addition to the basic mining and analytics, there are more interesting and complicated measures to be found. If a brand sees that they are being mentioned often, that is only part of the puzzle. When are they being mentioned? Is it related to some advertising campaign? Are they saying good things about the brand? What is the “state of the tweetverse”? Technorati and others publish annual whitepapers regarding the state of the blogosphere, why can’t Twitter do the same? They could also have a premium subscription for access to the daily trends of tweets and searches.

As you can see, there is money to be found in the data. The big question is whether Twitter can capitalize on this opportunity.

Disclosure: I am the author of YackTrack, a conversation tracker that searches various services, including Twitter, for mentions of keywords or links to blog posts. Obviously, I am very interested in this topic.

10 thoughts on “Twitter, The Analytics Provider And Data Mine

  1. hammer_shi,

    Yes, you may republish this post (especially if it is translated to chinese). I would just prefer that you refer to this blog as the source.


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