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Social Network Data is the New Oil of Marketing


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Social networking has become a dominant factor in western communities in an incredibly short period of time.  For instance, Facebook became mainstream only within the last 5 years, but, for many people, it already represents a dominant form of social interaction.  

That the data generated by social networking represents unique market intelligence was recognized almost immediately, and attempts to mine Twitter, web and public Facebook data to determine consumer sentiment has been a hot topic for several years.

However, we are now seeing a seismic shift and increase in the significance of social network data for marketing and brand analysis.  The next wave of social network exploitation promises to allow companies to narrowly target consumers and leads to predict market trends, and to more actively influence consumer behavior.

Consider today’s telemarketing experience.  We are all frequently subjected to intrusive and frequently low value interactions with telemarketing individuals who often live in a different country and know little about us.  In the near future, it is likely that at least some telemarketing and inside sales will be targeted based on public social network data (Twitter, Facebook, LinkedIn, etc.).   Companies such as LeadSpace are using social data to generate leads and call lists, while companies such as Nimble provide detailed individual profiles based on social network data. The idea of telemarketers using social network data to target and engage with you might seem undesirable, but it may, at least, lead to more targeted programs and less “unwanted” engagements.

In his 2010 book, “Super Sad True Love Story,” Gary Shteyngart postulates a dystopian future in which social networking has permeated everyday life to the extent that individuals constantly rank strangers on various dimensions of desirability. In Shteyngart’s book, social networking site Global Teens constantly suggests to users that they use images rather than text: “less words = more fun!!!” and “typing makes wrists large and unattractive.” Shteyngart feared that social networking would reduce literacy, which may or may not be true, but it is unquestionable that social networks are becoming increasingly image heavy. Networks such as Instagram, Snapchat and Pinterest are oriented almost exclusively around images, while 75% of Facebook posts include images.

The prevalence of images creates challenges and opportunities for those attempting to mine the social data. Pinterest, where users “pin” images of items they aspire to purchase, provides a particularly rich form of intent data, since objects often are pinned prior to purchase. Furthermore, images on Pinterest often are taken from advertising materials, which allows them to easily be matched with inventory. The startup Curalate provides a platform for mining Pinterest and other image data to determine demand and campaign effectiveness.  As image recognition grows in accuracy, we can expect that more social image data will be mined for marketing purposes.  

 

Many people were disturbed to discover recently that Facebook had engaged in social science experiments in which the effect of manipulating uses newsfeeds was measured. Not surprisingly, it was found that Facebook feeds have a significant influence on our emotions and behavior. In some respects, the effect on our mood of social networks is not qualitatively different from the effect of advertising streams on television. What is very different, however, is that it is now possible to correlate, at individual and group levels, the relationship between social network campaigns and individual behavior. This feedback loop may allow for more effective – though possibly more intrusive – social network marketing campaigns.

 

Most of us still think of social networking activities as inherently personal. After all, we use social networking primarily to communicate with our friends and families, and rarely do we deliberately interact with product and service providers. It seems clear, however, that the exhaust generated from social networking is perhaps the most valuable source of information for market research, product campaigns and brand sentiment analysis. 


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