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Data is giving time a run for its money because of its ability to deliver more revenue-building value thanks to the injection of science into the equation. Now, data science is essentially helping brands and publishers generate more revenue than ever before with insights that deliver the specific strategy for what will maximize the return.
Essentially the guessing game and the shotgun can be tossed out in lieu of the ability to hit the bull’s-eye in terms of which brands to go after and what message to deliver.
Easier, But Not Easy
With such an easier approach to making money, it might be hard to imagine that publishers still face challenges. However, issues still exist when it comes to publishers trying to sell ads. They know that brands are not interested in spending their marketing budgets on a single-spot TV ad or full-page print magazine ad. Instead, ad sales teams must figure out a way to sell complex packages that satisfy the needs of advertisers and deliver a strong ROI.
However, in order to know what to pitch, there needs to be transparency. Sellers don’t get much time with buyers so ad sellers must do their homework before they pitch if they want to stand a chance in closing the deal. Having an easier way to gather those key insights would then help that sales team work smarter and maximize that return.
The Human In The Data Science Machine
Enter data science that is fueled by the use of artificial intelligence and machine learning. Companies like MediaRadar, which works with more than 1,400 publishers, realize that this combination of technologies can help track and evaluate ads in such a way that their clients can access the necessary insights and target their pitches for better results.
According to Todd Krizelman, CEO and cofounder of MediaRadar, “Many of our applications are trained to improve over time as they encounter more data. We use classical algorithms and machine learning, which improve based on historical data. Both classifications systems evolve with the introduction of analytical techniques.”
Data science clearly delivers favorable results for brands and publishers. However, sales will always require some human element to create balance. It’s the art part that integrates with the science quotient. Remember that it was only a few years ago when programmatic emerged and some believed it would displace human selling. In reality, this didn’t happen and isn’t likely anytime soon. In the end, programmatic companies also employ sellers because they realized humans have the art of selling down. Machines can do the rest.
The result of this combination is that publishers can use the insights to measurably increase and expedite their sales process. Publishers can identify new prospects that would value their audience, tell them when and who they need to pitch, and provide all the information they need to deliver a compelling pitch. This data science formula also works for brands and agencies. They benefit from an improved package and more targeted pitch from their media partners.
The machine learning aspect to these data platforms also serves as a matchmaker to further enhance the results. For example, based on demographics, past successes, timing, and the audience, the platform can pair media properties and brands in almost an eHarmony kind of way.
Making Happy Media And Brand Relationships That Last
MediaRadar has created long-lasting relationships with publishers like Bloomberg Media and Giant Media thanks to their data science platform’s capabilities. According to Keith Grossman, CRO for Bloomberg Media, “As the media landscape continues to evolve, the way in which advertising will effectively engage consumers will shift as well. Regardless of the trend of the moment, the goal of any engagement should be to inform, not deceive, the consumer. MediaRadar provides a format that is easy to search, shape and digest to ensure that we can do the right thing for our readers.”
Giant Media, a premium video distributor who made a name for itself by putting out the first Dollar Shave Club video that quickly went viral, uses this data science provider on a strategic and tactical level. John Cobb, CEO of Giant Media, explains, “Strategically, we know what brands and agencies are working together and what type of media they are putting money behind. Tactically, our team can conduct prospect research on a brand or agency that we may be talking to or trying to get a meeting with. Overall, we have a better understanding of our market and can more easily personalize our sales approach.”
The media company has derived some giant results from applying data science to their process. Giant Media have contacted more than 10,000 people at brands and agencies across the country based on the insights they have received from the data science platform. In New York, they identified more than 500 brands to target, with 118 fitting their profile that they would not have been able to compile – or even find – so quickly.
The results are similar in other cities that Giant Media is working in. For example, in Chicago, they are targeting 215 brands with 36 running video and native advertising as well as 192 brands in Los Angeles with 26 running video and native advertising.
An Evolutionary Process
What companies like MediaRadar are doing is creating an evolutionary process that has applied the rules of data science to what had once been just the art of sales. Now, it’s become a hybrid animal that is gaining a life of its own and delivering better results for brands and publishers alike, making for some very happily-ever-after stories.
This article originally appeared on Forbes.
