The Big Data Conundrum

The increase and infusion of usage of big data is seen across all industries – healthcare, sports, logistics, finance and especially in the world of marketing. Digital marketing specifically has evolved to become so reliant on programmatic methods and platforms, and the availability of a robust volume of data has provided both an opportunity and a threat to marketers. On one hand, more data about the end consumer is never a bad thing. After all, the goal of a successful marketing plan is to reach users with pertinent messaging that create a sense of a connection to facilitate an end result. Having more data to help navigate those decisions is definitely a good thing and can help the marketer achieve greater personalization and efficiency with their media spend. The paradox in having such a massive amount of data to sift through is how to use consumer data but also channel data for campaign measurement. Companies have come and gone, claiming to have the ‘secret sauce’ when it comes to media mix modeling and campaign measurement and this has created a real tangible problem within the industry. Whether to credit a social ad, that was seen after a search ad and a product listing, or a display ad that ultimately drives the sale. Not to mention a TV ad or a podcast ad that are difficult to tie back to the same user in a reliable way. There isn’t a perfect answer to this challenge and it’s the marketers job to see both sides of the big data conundrum as both a blessing and a potential curse.