Summize helps marketers peer into the attitudes of a million+ Twitter fans

July 9, 2008 –

How is this for stating the obvious? Data mining is helping marketers better understand and cater to consumer behavior. Examples abound — even here, in Digital Solid. But this fact is worth repeating considering this latest example.

As reported and discussed in this GigaOm post, Twitter is likely to purchase Summize, which is a popular third-party application that searches and reports on keywords embedded in these 140-character packets of text. Om Malik of GigaOm conjectures that the reason for the purchase is less about search, which can be interesting, but about understanding consumer behavior, which can be useful to marketers.

This is an understatement.

The biggest question surrounding Twitter has been, How can this seeming toy ever break through and become a profitable business? This week’s news suggests a research product that, in its beta phase, is already quite good. Go to its Sentiment Analyzer and type in a phrase. Malik typed in keywords related to the acquisition of Summize by Twitter. Here was his result:

Analyzing what Twitter fans think of the Summize purchase

Sentiment is “Bad.” Obviously the majority of people Tweeting about the buy-out aren’t Summize’s soon-to-be-wealthier founders! If you want to see really bad, however, type in “Gas Prices,” as I did here:

Twitter Sentiment surrounding \'gas prices\'

It’s a fun toy. But the real time market research implications are huge.

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Posted in Database Marketing, Visualization, Web Marketing |

2 Comments to “Summize helps marketers peer into the attitudes of a million+ Twitter fans”

  1. Matt Says:

    I don’t understand how it determines that the prevailing attitude of twitter buying summize is bad? I count seven ‘wretched’ boxes to 18 ‘great’ and six ‘bad’ to 11 ’swell’ boxes. I assume ’so-so’ is neutral?

    It sure seems like the good tweets are outweighing the bad according to the weird box chart yet it says the prevailing attitude is bad?

  2. Jeff Larche Says:

    Matt, I’ll bet they set up a scoring system that places greater weight to a negative comment than one that is positive or neutral. Similar to the Net Promoter Score.

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