Ogilvy’s addition of Todd Cullen as Chief Data Officer to their C-suite this month is the latest indicator of the rising importance of data for agencies.
Cullen will guide the advising of clients on gathering cross-channel data, using 3rd and 1st party data, and creating advanced analytics and modeling.
The new CDO role reflects an increasing demand and need for personnel at agencies who talk tech and brand with equal ease. The agency culture at Ogilvy is no doubt very performance-oriented and that means being metrics and data-oriented as well.
The goal for agencies leveraging big data is to enable more effective campaigns that drive consumer engagement. When used properly, big data can reduce costs and amp up performance. And agencies have developed a strong preference for online 3rd party data according to research conducted by eXelate in April 2013.
“The overarching message was that data drives better results with more precision.”
The Endless Pressure to Increase Reach
Online, offline, CRM, social, POS, analytics, mobile devices, search — there is a massive amount of consumer data available.
The prevailing strategy is to leverage this 1st party data to retarget users. Advertisers then create look-alike models using 3rd party data to expand beyond the current customer base, and try to achieve comparable performance to 1st party data.
Many go one step further and overlay 3rd party data on top of 1st party data, painting a clearer picture of market segments and who should be targeted with what message.
So by mining 3rd party and 1st party data, and compiling that data into a central platform, agencies are increasing the efficiency of buys intended to reach new users.
But the challenge is that due to endless pressure to increase reach and simplify buying, 3rd party data has been heavily aggregated. In many cases the same or similar data is available from a lot of different sources in the data marketplace — unfortunately creating a lot of junk information.
Aggregation, which benefits data vendors, can be a major source of frustration for marketers on the buy side, because it can dilute the granularity and specificity needed to make smart buying decisions. This creates a quality versus quantity tradeoff that agencies are dealing with.
With hundreds of thousands of segments, it can be challenging to validate quality and find unique overlaps across multiple segments. Looking for consensus across multiple data providers is one method, where each data point shared between different sources gives the advertiser a sense of confidence in the data.
Hunting a Moving Target
Another challenge in leveraging data is exposing the fallacy that consumer preferences are static. The truth is that consumers are not the same today as they were yesterday. They won't be the same tomorrow.
Brand loyalty used to mean something greater, but online it’s extremely easy to change product preference and pick something else at a moments notice. This is only accelerating with the limitless access to information and trends online.
As a result, marketers need to be open and receptive to change. Always be agile. Market conditions change and so the data that worked last time may not work next time. Using analytics tools can help bubble up insights about what is working right now and enable advertisers to be adaptive.
Another strength of data is invalidating preconceived notions. Selection bias is real and happens more often than we’d like to think. But big data analytics can surface up new possibilities or market insights that wouldn’t be empirically apparent.
Remember the Funnel
The other thing to consider is that in pursuit of scale through targeting via 3rd party data, marketers must realize that identifying new segments may mean reaching out to net new customers who may not be familiar with the brand. You have to go through that processes of driving awareness and consideration. That means advertising to a new audience may not be able to drive a sale today. But what it does is bring new people into the funnel — planting the seeds for organic customer growth. That can be a hard pill to swallow if the expectation is that newly identified markets should immediately perform as well as existing ones.
Ultimately, end-to-end data analysis is needed to truly calculate ROI and see if folks are converting eventually. In some cases, the technology is there, but in so many others, we aren’t. The task is then how to connect the data points together and evaluate success.
That’s exactly why Ogilvy created a CDO position — to take the best practices across the organization and make them smart, standardized and repeatable.