Dynamic Attitude Analysis (DAA) is a marketing measurement practice in which a brand can use specialized tools to capture blog posts, Usenet articles, and other consumer-generated content. Part 1 of this series discussed a few (free!) tools marketers can use to set up living, persistent search queries. Thus, the brand manager for Scrappy Kat Kitty Treats can be notified whenever someone says something online about Scrappy Kat Kitty Treats.
This is enormously valuable, but a higher level also exists. It goes beyond capture and into analysis: knowing not only when, but the quality of the citation, too. That is, a system scans through these posts and make a determination as to whether the post is good or bad.
To which I say, “Whoa.”
Creating Structure in the Blogosphere
At first glance, the ability to automatically count how many people praise your brand and how many bash it is pretty impressive. Then, most everyone arrives at the same question: How on Earth do you find structure in the chaotic snarl of blogs and Usenet posts? With cross-links, TrackBacks, comments, and a pretty free-flowing writing style, any attempt to find the uniformity necessary for an automated system seems hopeless.
It’s not that bad, actually. Intelliseek, which has done a lot of work in this space, developed a text parser specifically tuned to pull out the stylistic and linguistic peculiarities of this content type. Consider Usenet posts: Every post has some common features, such as brackets, indents around quoted passages, and the phrase “[Gary Stein] said:.” By searching for these elements, the program breaks away this tough layer of text to find the content inside.
Same thing with blogs and, really, any other content. As long as a style sheet can be generated, programs can just pull the content that’s valuable to the marketer.
Type a query in a search engine box and you get a list of results, period. The challenge is to make that list as relevant to the query as possible, but that doesn’t provide any sense of the content’s nature. Type a political figure’s name into a search engines and you get a list of sites about that person. You don’t know, and can’t categorize, which sites are for the person and which are against.
DAA systems enable you do to know which sites are in favor of the politician. With formatting stripped away, the system looks for valuable words and phrases: “easy,” “problem with,” “questions about,” and so on. From here, the system not only categorizes but also takes account good versus bad; and happy versus sad.
With this accounting, the system can also track, providing a nearly automated brand tracking system. In fact, numbers from a DAA system may be more accurate than those from a brand tracking system. You get the consumer’s real voice from a DAA system, not a survey question response.
A number of companies are moving into this space. Current leaders include BuzzMetrics, FAST Marketrac, Cymfony, and Intelliseek.
DAA Use and Abuse
DAA is a powerful tool and technology, particular when sentiment is automatically determined. Brands must be careful of how they use it. If a brand finds champions, great. If it finds attackers, a new set of circumstances is created.
Imagine a blogger who actively attacks a particular brand online. Using a DAA system, the brand quickly finds that person. The brand could decide to approach the person to try to convince him of its value. It could ignore him. Or, it could take legal action.
That last option is attractive to many, but it must be resisted. DAA systems could easily be perceived by the blogging community as an intrusion into their world and their culture of free-flowing information. If DAA systems are viewed as anti-blog, it threatens not only the systems but also brands that use them. Imagine a standard being created that forces DAA crawlers to obey an exclusion file. A blogger could determine whether to allow her blog to be crawled.
Like anything else, the future of the system and its efficacy is in the hands of those who use it. Use it to get smarter, not to gain control over consumer communication.
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