Attracting customers is easier once the marketing teams know the target audience. But, discovering the target audience is a difficult task in itself, which is why Big Data became so important for advertisers, explains Daniel Yomtobian.
“Using their huge troves of information, brands can send the right message to the right audience, thus ensuring the success of their ad campaigns and achieving the desired returns on investment. The caveat is that Big Data on its own is more of a hindrance than an aid: the raw, unstructured sets of information require proper analyses to deliver actionable insights. In the fiercely competitive advertising industry, the utilization of data analytics tools has become absolutely crucial, especially as consumer behaviors and preferences keep changing and raise the bar for end-user experiences,” Daniel Yomtobian adds.
Given the staggering amount of data generated worldwide on a daily basis, advertisers need to go a step further and not simply analyze the information but employ predictive models to gain real benefits. In doing so, they will be able to identify details that truly matter, including shopping patterns and trends, interests, user habits and behaviors, and the likelihood of conversion or defection. With the insights gleaned from predictive analytics, brands can fine-tune and personalize their messages, which vastly increases their chances of resonating with the intended audience and executing a successful campaign, Daniel Yomtobian notes. In addition to improved targeting, customer acquisition, and retention, analytics tools also provide marketers with insights that can reveal new product opportunities and facilitate content monetization.
It can be argued that brands clinging to the old ways of analyzing their ad campaigns put themselves in jeopardy in a world where “consumers are exposed to an expanding, fragmented array of marketing touch points across media and sales channels,” as stated in a Harvard Business Review article. Nowadays, the deluge of data requires what the author refers to as “Advertising Analytics 2.0.” He goes on to say, “Enabled by recent exponential leaps in computing power, cloud-based analytics, and cheap data storage, […] predictive tools measure the interaction of advertising across media and sales channels, and they identify precisely how exogenous variables (including the broader economy, competitive offerings, and even the weather) affect ad performance. The resulting analyses, put simply, reveal what really works. With these data-driven insights, companies can often maintain their existing budgets yet achieve improvements of 10% to 30% (sometimes more) in marketing performance.”
Daniel Yomtobian has come to be regarded as a pioneer and innovator in the online media space, receiving a number of awards for his contribution to the digital advertising ecosystem. Relentlessly committed to helping advertisers and publishers maximize their ROI and monetize their solutions, he has been the driving force behind several business ventures, including PPC network Advertise.com. Daniel Yomtobian attended California State University-Northridge.
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