Predictive Analytics – A Crystal Ball to Peer Into Future Market Wants
As most advertisers readily admit, the ability to peer into the future would make their jobs infinitely easier. Whether a crystal ball or fortune teller, any device to look down the road and gauge the interests, passions, and tastes of tomorrow’s consumer would afford advertisers a more straightforward today.
While soothsaying abilities of the supernatural ilk are still well out of reach, technology is making strides toward accomplishing similar goals.
With the advent of predictive analytics and machine learning, advertisers are just beginning to tap into the power of trend modeling based on past and present data to create sophisticated, reliable models of likely future consumer behavior.
Although not quite as straight-forward as a crystal ball, predictive analytics is still bound to redefine the manner data is integrated into strategy formulation. Once adopted, advertising efficiency and effectiveness will be forever changed for the better.
A Simpler Concept Than It Might Sound
Though it sounds like alien technology from a sci-fi thriller, predictive analytics is actually a simple concept at its roots. Predictive analytics mines relevant data from the past and present, filtering it through a set of algorithms to generate models of future trends.
Although it has applications across many different industries, it especially wields power for advertisers who are constantly in search of new, insightful ways to study the coming marketplace. While trend analytics has been used for decades to gather such insight, the complex algorithms now available provide exponentially more impactful results to an advertising team.
A Handful of Uses, A Treasure Trove of Results
Like most technologies new to an industry, the full impact and varied uses of predictive analytics in advertising are still work in progress. Judging from the applications already being put to use, however, it appears as if a handful of specific but related uses will best utilize predictive analytics in the near future.
Modeling Human Behavior
First and foremost, predictive analytics will help advertisers create behavior models to measure the impact of variables on the marketplace. While still in its infancy and currently relegated to just a few specific uses due to the complexity and scope of human behavior, it’s already capable of transforming data sets into usable, insightful models.
Current applications are being used to predict clustering patterns of customers relative to products and services, propensity models to gauge the likelihood of particular sets of behavior and lastly, recommendation modeling that forecasts product and service suggestions based on past consumer behavior.
Secondly, predictive analytics will significantly increase an advertiser’s ability to visually engage the audience through a refined data visualization process. With consumer behavior data being filtered through the appropriate algorithms, advertisers can develop creatives that are more likely to visually appeal to the target audience.
From design features to product appearance, data visualization will magnify and broaden the appeal of a campaign to an audience.
The most straight-forward and prevalent of the current applications is the specific form of customer segmentation that times product release and relevance with the most appropriate audience.
In doing so, predictive analytics again uses consumer behavior data to find the optimal combination of product offer, timing, and market segment. This prescient ability to align future campaign efforts with specific market traits provides a tremendous advantage in finding a connection with the audience that previously required significant amounts of effort, patience, and trial and error.
Predictive analytics takes the bulk of the guesswork out of the process and provides a level of precision never before enjoyed by an advertising team.
Predictive Analytics In Current Advertising
While advertisers are only beginning to embrace the power of predictive analytics, there have already been some notable examples of its usefulness.
The most obvious instance comes from Netflix, the market leader in subscription-based streaming media. By using predictive analytics modeling in its recommended viewing suggestions, Netflix employs a variety of metrics that include past shows watched, the amount of time spent watching a particular show as well as genre and actor preferences to formulate a suggestion list that will likely appeal to an individual viewer. The complex algorithms used in predictive analytics is what provides Netflix the ability to accurately predict each subscriber’s tastes.
In another example, Forbes uses predictive analytics to provide their advertising partners a more precise idea of where an individual reader might be in the buying cycle. In doing so, advertisers are able to hone their message appropriately, choosing the creatives and tone according to a specific stage in the buying process. Although Dell was the first partner to take advantage of Forbes’ new predictive analytics advertising, several other companies have since joined the fray.
Similarly, the New York Times has integrated predictive analytics into their communication with subscribers and social media feeds. At a time when print media, particularly newspapers, are struggling to find revenue, the New York Times looked to technology to provide them with a competitive advantage.
By using predictive analytics, they can identify and act upon trends within the news cycle, tailoring their message according to the predicted topics of interest. Therefore, the paper integrates that data into their social media feeds to distribute articles that will maximize interest and attention according to the trends.
ReFUEL4’s AI-guided creative management platform provides advertisers with the ability to make intelligent selections of ad creatives to use for your online campaigns using predictive analytics. We rank each of your ad designs with an AI score indicating likelihood to perform based on your campaign’s objective and targeting.
Sometimes technology makes incremental advances that might seem subtle at any given point in time. However, there are other moments when a single technology provides a significant step forward in innovation and impact.
Predictive analytics is a transformative advancement that gives advertisers tremendous insight into the murky, often confounding trends behind human behavior.
Although it’s only now receiving a broader embrace from advertisers, its power and insight will prove to significantly change advertising as it refines its ability to engage with a dynamic, data-driven marketplace.