Defining the Signal from the Noise

April 1, 2014

By Rob Jayson

The world is awash in data. Every time a consumer uses a website or a social media platform, a detailed data set is recorded. Every mouse click leaves a trail to follow.

Data has always been a centerpiece of research. From decades-old techniques such as consumer research surveys, product purchaser panels, and customer relationship marketing to newer, financial market approaches like time-series modeling, chief marketing officers have always looked to data and analytics to drive their decision making.

In the modern age, however, two critical changes are transforming the research landscape in ways we couldn't have imagined. First, there has been a huge increase in the availability of data to track consumer attitudes and behaviors in real-time. Second, we, as marketers, have increased our ability to blend and filter that mass of data into actionable insights that shape marketing campaigns at the strategic and the tactical level.

This real-time data explosion is revolutionizing the way we develop insights about how consumers interact with brands, what prompts them to action, and what communications prompt them to recall and consider brands.

Where in previous years the core of consumer trend analysis might have been a rolling two-year average drawn from a large diary- and paper-based survey system, today we are mining real-time consumer trends from a multitude of online and offline sources.

Rather than just relying on diaries, we can mine Google's database of consumer actions to locate peaks and troughs of interest in brands and categories and investigate what drove them.

Social data — tracking consumers' interactions with brands and content across multiple platforms such as Facebook, Twitter, and YouTube — give a real-time view of how brands are engaging with their potential consumers. Insight platforms such as ZenithOptimedia's Social Tools can tell us immediately if brand content is engaging consumers and to what extent, and benchmark those results against their close competitive set.

Developing real-time research data insights requires several new skill sets to add to the existing toolset that media researchers use:

  • Analytics. The ability to isolate the signal from the noise as quickly and accurately as possible but without sending brands down a potential rabbit hole based on outlying data points.
  • Digital know-how. A lot of today's real-time data is delivered to serve the trading market place and is not packaged up as neatly as syndicated research in crosstab formats. Today's media researcher needs to know how to manipulate digital response data almost as well as the marketplace buyers.
  • Data versatility. Insights come from multiple sources and points in time — from historical trending of category data through customer segmentation behaviors to real-time social media insights. Today's researcher needs to be able to blend these sources into a cohesive insight-driven consumer story.

Tracking fans' interaction with content, following the engagement score of brands in a category, and then evaluating the social keywords used by brand engagers are all new tools we can use to develop real-time insights. Real-time social data allows us to understand how consumers are interacting with the content that brands are delivering to them and how we can optimize our messages to those responses.

Rob Jayson is chief data officer for ZenithOptimedia Worldwide, a leading global media services network in the Publicis Groupe.


"Defining the Signal from the Noise." Rob Jayson, Chief Data Officer, ZenithOptimedia Worldwide. ANA Magazine Spotlight. April 2014.

You must be logged in to submit a comment.