Why Big Data Analytics is a Necessity in Digital Advertising
In the age of digital, the traditional way of advertising is slowly fading away — this means fewer brochures and more Facebook videos, fewer mailers and more personalized e-mails. An article on The Balance lists some of the cons of previous traditional advertising methods, which include hard to quantify results, expensive legwork, and unappealing hard-sell methods. This is because it was difficult to track just how useful those traditional ads were, how many people they reached, and how much new business was acquired because of them.
The era of digital advertising does away with these problems by focusing on data-driven strategies that are more effective and advantageous. Big data analytics, in particular, is continually reshaping the advertising industry. Research from IBM shows that 2.5 quintillion bytes of data are created every single day, which is why analytics has become necessary to filter and make sense of the massive volume of data points generated. Read on to find out why big data has become such a big deal in digital advertising, and why no advertising agency can survive without it today:
Targeted Ads
Scrolling through one’s social media feed these days and seeing recommendations that feel like they’re meant for you has become the norm. This is thanks to big data analytics, as it allows advertisers to create less intrusive and more targeted ads. Emerging technology allows for more specific data gathering and, in turn, more targeted marketing strategies — taking away most of the guesswork that used to be involved in traditional advertising. Global digital marketing agency Ayima state that this unique data can improve a brand by providing insights on customers’ specific needs at precise times. This allows for a precise data-driven approach to advertising. For instance, if someone recently searched for health insurance on Google, there’s a high chance that an ad about it will show up on Facebook or Instagram ads that same day.
Semantic Search
Semantic search is a more sophisticated way of understanding what people type in search engines through analyzing natural language. This is in contrast to simple keyword searches that are not as accurate. For example, if someone were to type “What is the best hobby to promote mindfulness?,” semantic search understands that whole sentence and can produce realistic answers — whether it’s cross-stitching, running, or indoor gardening. Big data analytics, paired with machine learning techniques, can make this precision in text analysis possible. In turn, users can get the right “hits” when searching for a certain product or service. Advertising agencies can then glean information from analytics to tailor their content to these searches through Search Engine Optimization.
Personalized Content
The glory days of spam mail and random ads are finally coming to a long-overdue end. Personalized content is all the rage in the advertising industry these days, as it gets users to engage more with brands. An Adtech expert tells The Huffington Post that this personalization is giving consumers more power, as agencies scramble to provide relevance and entertainment in exchange for viewers’ attention. Today, a good marketing strategy may be to send an e-mail with the potential client’s name, on a holiday that matters to that particular demographic. This level of personalization requires data analytics that can quickly sort through known information to provide actionable insights. Coupled with artificial intelligence, it gives users the feeling that brands care about them and their interests.
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