Brands, no matter how big or small they may be, a common concern they all share is maximizing their campaign effectiveness. For the sake of illustration, imagine a Mercedes Benz Ad targeting a female aged 22-27, will it be effective in any sense? No Brainstorming please, No is the obvious answer. Not only is this targeting futile, it also invokes a negative perception in the targeted individual which can lead to brand dispersion among similar prospective targets in the future. Making sure this ineffectiveness Rests In Peace is a prime focus for Brands.
To maximize campaign effectiveness, better understanding of a person’s interest and the corresponding relevance needs to be taken care of.
Some Online Campaign Management Platforms have tie-ups with websites from diverse fields ranging from News (BBC), Sports (ESPN) to Cooking and even Social Networks. Whenever we login to a website, say Bestbuy.com, a Java Tag is attached to that login which yields a unique User Id. Based on the User Id, the browsing pattern of the users is tracked which gives the exact “likes” or interest domains of that particular individual. Now the same individual, after logging in from his/her Laptop or Desktop switches to some mobile device during the unavailability of the Laptop or maybe due to the increasing ease and effectiveness in using mobile devices and also while he/she is travelling. Once again, a User Id is generated corresponding to that mobile device keeping track of what is being browsed.
Identifying same users across different devices is a new buzz. Recently Kaggle , a leading platform for Data Science competitions, hosted ICDM 2015: Drawbridge Cross-Device Connections, which tasked the teams to identify the same users across different cellular and non-cellular devices leveraging big data consisting of the cookies info, country info and some other key information. Once same users across different devices are identified, we have a consistent or continuous insight about the searches being done. The insight generated acts as a tool for refining the future campaigns targeting a particular individual.
Some Data Management Platforms such as Lotame or BlueKai , conduct online surveys about the interests and the likeliness of a particular person going for a particular type of product or about collecting the general notion of the person towards a particular product or a company. The DMP data when merged with the data collected using the website tracking can give us a broader and a much powerful insight about what exactly a person wants to explore, try and longs for which eventually can provide a better platform for targeting him with the relevant ads.
Using the data obtained from the surveys or captured online about the different attributes of a particular individual like Gender, Age etc. platforms like ComScore can help in roughly estimating the probability of fraction of people falling under different attributes.
Suppose some click on Bestbuy.com is made, then merging the insights and the ComScore analysis can give us the idea whether that particular person is Male or Female, what age bucket is he/she likely to fall in, and other important information. This analysis will form the base for Marketing Personalization wherein we can know whether to target an individual with a particular Marketing campaign or not, whether it will be relevant for the individual or not and whether after being targeted with the campaign, he/she is likely to convert or not, which in turn will enable the brands to have an effective marketing campaign.