The following is a guest contributed post from Jill Draper, President of Marketsmith Inc.
These days, most enterprise marketers use a multichannel brand awareness and business development strategy, spreading the word about their company, products and services via a variety of platforms, including digital ads and social media marketing. But, television still gets the lion’s share of ad spend, and it’s time for enterprise brand marketers to demand that their TV brand awareness campaigns work harder and smarter.
According to a recent Nielsen report, Internet display ad spending grew 32% in 2013, which demonstrates the growing power of the digital medium. However, Internet display advertising still makes up only 4.5% of total spending, with TV accounting for nearly 58%. And marketers have good reason to put their faith in TV advertising: A Nielsen analyst noted that TV remains the most trusted source of paid media information.
But the question remains: How do enterprise brand marketers measure the effect of their direct response TV marketing and make campaigns more accountable? Predictive modeling platforms provide the answer by delivering data. The concept of “Big Data” has generated significant buzz in the business world for the past several years, and in this instance, the hype is justified: Big Data can provide unprecedented insights into how advertising drives consumer behavior.
In the past, marketers in sectors such as insurance and telecommunications put brand awareness campaigns on television with no accurate way to measure the return. But predictive modeling technology offers a more scientific and analytical approach, empowering enterprise brand marketers with accurate metrics to demonstrate exactly how campaigns are delivering responses via the web, telephone and retail locations.
With an intelligent marketing platform, enterprise brand marketers can bring all relevant media performance data together with information on fulfillment, cost center data and web analytics. This allows them to tie consumer actions back to the specific airing of direct response TV ads. By using an algorithm similar to that used by successful day traders, marketers armed with effective predictive modeling technology can then accurately project which specific ad slots will drive the desired consumer response.
The result can be rightly viewed as the Holy Grail of television advertising: A fully accountable media strategy that enables enterprise brand marketers to funnel ad spend where it drives the best response, and redirect dollars that are not generating sufficient ROI. None of this would have been possible just a few years ago, but with advanced predictive modeling technology, it’s not only feasible – it’s affordable. And given what’s at stake in terms of television ad spending, enterprise brand marketers can’t afford not to use predictive modeling.