Look-a-like models have long been the marketer's friend when designing direct mail and print campaigns. These models are portraits of existing customers that can be used to statistically identify and predict who is more likely to share an interest in a product or service. This idea is an old stand-by for direct mail or catalogue advertisers, and now, as the digital age continues to evolve, online marketers are gaining access to the same advantages as marketers in these traditional channels.
Digital look-a-like models are the way of the future. They provide a new way for online advertisers to evaluate the people who are actually viewing a web site and clicking on advertisements. For years, online marketing and advertising campaigns have had to rely on the placement of a cookie or tracking pixels to give them feedback on consumer habits. From the information collected by these trackers, marketers have had to make inferences about who their consumers are by evaluating limited and incomplete data. In addition, renewed attention is being paid to internet privacy concerns, and companies that depend on tracking consumer habits can be seen as intrusive and perhaps even unethical.
Behavioral targeting, or targeting consumers through the placement of cookies, is ineffective for a variety of reasons. In many cases, online users remove these trackers before any useful information can be gleaned from them, or the cookies simply expire between 30 to 60 days after being placed. There are even some computer programs designed to protect users from cookies being placed in the first place. Even when they do function as they're intended, they aren't always effective. The data collected by trackers can lead to misguided or wrong assumptions about online users, rendering the advertising ineffective and the investment wasted. For example, a teenage boy may love looking at websites devoted to luxury sports cars because he has an interest in cars and would like to own one someday, not because he's ready or able to buy one now. In most cases, a teenager cannot afford such an investment, but a cookie would have marked him as a viable target and exposed him to lots of advertisements for expensive cars that he has no means or inclination to purchase. This is a waste of valuable ad inventory and a wasted investment. However, had marketers relied on digital look-a-likes instead of behavioral trackers, the boy would not have been targeted and those advertising dollars would not have been wasted.
Semcasting is a leader in predictive modeling. Using its IP Audience Zone Targeting service, Semcasting is able to create reliable digital look-a-like models that can help businesses make the most of their ad spend by targeting those buyers who are not only interested in purchasing a company's services and products, but who also have the means to currently do so.
Digital look-a-like models are created by modeling the advertiser's IP addresses - those who look at the advertiser's website or who click on advertisements for the advertiser's product.The models are then matched to geo-location zones that are categorized by demographic and psychographic attributes to create a portrait of the category of visitor who is viewing the site or clicking on the advertising. IP Zones provides over 750 data points regarding consumers who visit a site, including key attributes like affluence, affiliation, life stage, personal interests and more. The digital look-a-like models are constructed from these hundreds of data points using Semcasting's patented predictive modeling, creating a statistically accurate picture of who site visitors are while also predicting where to locate the best possible online prospects who look just like them. This leads to a greater rate of attribution and the best return on an advertising investment.