Our content-disrupted world has made techniques like personalization and contextualization necessary at the forefront of the marketing industry. Customers often favor a personalized approach that recognizes their individuality—but those techniques can become intrusive and counterproductive when they appear in the wrong place, at the wrong time.

Recently, rumors said that Facebook was tapping into people's conversations then showing them laser-targeted ads about what they had discussed—a dream vacation in Greece, new 3-D TV, or new spicy pasta recipe.

Fortunately, those rumors were unsubstantiated, and Facebook offered an official statement denying those claims and putting the rumors to rest. However, it's still hard for consumers to not be creeped out at times by marketing campaigns that are so precise.

How Big Data Made It Simple

The rise of Big Data has resulted in marketers gaining access to specific behavioral and purchasing patterns popular among specific targeted segments. Marketers now have plenty of information to analyze and deliver the perfect message to each individual customer.

In having a user-oriented outlook, brands are creating better relationships with their target audiences, which eventually lead to an increased return on sales and better overall reputations. Brands that use targeted tactics report a 20% increase in sales, according to a DemandGen study.

Many high-powered companies have paved the way with this technology, and others have carved out a market for themselves by offering niche services geared toward specific platforms.

As more data starts to roll in and pile up, the industry faces storage challenges while it maintains efficient and quick methods of analysis. Ultimately, however, this technology can't just be about numbers… It's about building relationships and bringing forth services that have people in mind.

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ABOUT THE AUTHOR
image of Evelyn Kotler

Evelyn Kotler is director of Marketing at SQream Technologies, a Big Data Analytics software vendor delivering a high-performing, next-generation GPU database that quickly relieves complex Big Data and analytics pains.

LinkedIn: Evelyn Kotler