Last Updated on April 8, 2016
Data obtained from social networking sites can be used in order to make sites more relevant to readers as well as more profitable for advertisers. At the present time, digital advertising is still in its infancy. But in coming years, digital publishing could make significant amount of money for advertisers. Along with this potential for increased sales also comes a risk of privacy invasion.
Today, many digital publications are unable to make a large profit. Readers come and go very quickly. Even when the cash does flow to such publications, it is usually not enough to make the venture very profitable. The reality is that if publishers are not able to make a good profit by publishing online, they risk losing their business. However, it can be tough to be noticed amongst all the other websites on the internet.
The solution is to tailor ads to the interests of consumers. Consumers are happy because the ads are relevant to their lifestyles and advertisers have a greater potential of making a profit. Extracting information to be used for such purposes is often referred to as “obtaining Big Data” or just “Big Data”. Big data is often too large to be analyzed by conventional tools. However, analysts agree that Big Data information can be very helpful.
Using semantics, patterns in speech can be analyzed. Using such information, people with access to the right analyzing tools can predict a number of things. For example, they can determine who is depressed, who is happy, and who perhaps just got divorced. Semantics can predict these patterns even if such events are not overtly expressed.
The truth is that such analyzing techniques have been used for quite a while by phone companies as well as by some retailers. For example, an article in the New York Times described how Target used a model to determine which customers had reached the second trimester of their pregnancy. The retailer chose customers at this point in their pregnancy because it is at this point that many people begin to purchase items for their anticipated new arrival.
Big Data has other uses too.
For example, Google Flu Trends tracks flu outbreaks in areas better than government agencies. Retailers could conceivably use this information to market flu remedies as well as items designed to help manage flu symptoms.
Today, the internet already provides massive amount of information on people. For example, Facebook already analyzes content in order to show ads that are relevant to the interests of consumers. The social media site also is able to detect changes in someone’s relationship status in order to provide further relevant ads. Facebook can also predict the chances that two people who exchange messages online will eventually become a couple.
The information obtained on the statuses that are posted can also be used to ascertain information about a person’s financial status, their political beliefs, religious beliefs, or even their overall health. This information is gathered by analyzing the semantics of posts. The irony is that most Facebook users probably don’t have a clue that their online behavior makes their lives very transparent.
This same technique could be used by news content outlets in order to maximize profits while providing relevant content to readers. This could in turn increase readership which would make their online venture very profitable.
How might this work?
Consider the online habits of a fictional character we’ll call Mrs. Smith. Online analysis shows that Mrs. Smith has been frequenting websites lately which have job listings. One could conclude that Mrs. Smith is looking for a job. From her other web searches, it is apparent that Mrs. Smith likes to go camping. She also appears to live somewhere in Texas as she checks websites related to activities in Texas very often.
Over time, the content which Mrs. Smith sees will be tailored to her interests and needs. This means that she may also begin to spend more time online and perhaps spend her money shopping online due to the number of ads she has seen.
Will consumers be willing to exchange their privacy for convenience? Only time will tell. Right now, Big Data is still not being utilized extensively. However, this will surely change as time goes on. While consumers will have more options, they will also need to be vigilant to guard their private data.
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