Measurement is a topic that has been top of mind for digital advertisers for what seems like ages, and as more advertising dollars shift online, it is only growing in importance. Advertisers have always trusted their guts when it comes to connecting with consumers. But, how do we really know that works? Enter data science. The numbers are out there to tell us if campaigns are truly effective, and it’s sparking a debate over the end of intuition. Has the time finally arrived for us to let computers tell us what people respond to and connect with most, or do we still need to trust our instincts?
Recently, I sat down with Paul Pellman, CEO of Adometry, and he shared some insights around this discussion.
What is your take on how the data science revolution in advertising changes the role of intuition?
To start, creatives don’t have any reason to worry about their jobs. Quite the opposite, to be honest. At the end of the day, getting the right message to the right audience at the right time is still a bit like riding a bicycle with your hands tied behind your back. It’s possible, but it takes a ton of practice and no matter how many times you’re successful the next time is still going to be an adventure.
Like many innovations, the foremost impact of data science in the advertising industry is one of efficiency and economies of scale. The number of marketing channels keeps increasing, placing a growing burden on advertisers to understand where they can get the biggest impact for their finite resources (budgets and talent). To an extent, data — and more importantly, the insight derived from that data — allows advertisers to quantify intuition, either confirming hunches so that companies can feel more confident “doubling down” on marketing strategies or highlighting new opportunities.
Keep in mind these nascent technologies are just now reaching the mainstream, so there surely will be growing pains as advertisers learn to harness analytics and data-driven optimization recommendations as part of ongoing planning.
What are the key considerations for advertisers as they consider how to integrate data science into their strategies and campaigns for reaching target audiences?
Advertisers shouldn’t be afraid of the data or what it says. In our business, this typically manifests itself in the form of analysis paralysis, which I define as ‘inactivity due to fear of work required.’ Our attribution platform uses a number of variables and data sources to provide marketers with insights and observations about which of their media is most effectively driving conversions. Talented marketers play a critical role ensuring campaigns are appropriately targeted, but without good measurement data they are tackling only one part of the equation.
My advice to any organization serious about understanding the impact of all marketing efforts is to first do an honest assessment of what they can measure. Identifying the holes, or where the data is lacking depth, typically will lead you to the areas where investing in data science will have the greatest impact.
What’s on your data science and advertising reading list?
- Nate Silver’s book, “The Signal and the Noise”
- Harvard Business Review, “Advertising Analytics 2.0”
- McKinsey, “Measuring Marketing’s Worth”
- “On Intelligence” by Jeff Hawkins
- “The Face of Big Data” by Rick Smolan
- Occam’s Razor column by Avinash Kaushik
- “Moneyball” by Michael Lewis
- “The New Rules of Marketing and PR” by David Meerman Scott
To learn more about how data science is changing the role of intuition, watch presentations from the recent Advertising + Data Science Congress (ADS-CON).
