Commentary

How To Turn Data Into Knowledge And Action

Every day, millions of consumers travel across online channels, leaving a huge trail of data in their wake. Online marketers understand that this data contains critical insight into their best customers and prospects, such as who they are, what they value, which products they prefer, to which brands they’re loyal, as well as what they intend to purchase.

What marketers need is a way to capture, analyze and apply all of that data to drive smarter advertising decisions. Considering the sheer volume of the data pool (sometimes referred to as ‘Big Data’), this is no small task. At eXelate, data is our passion, and we recognize the urgency marketers feel to turn data into knowledge and action. We therefore devised the Audience Discovery Value Chain, as a comprehensive analytical framework to guide digital marketers through the process of understanding and leveraging consumer behavior.

The Audience Discovery Value Chain provides a proven framework for digital marketers to achieve their goals by making strategic use of Big Data, therein helping them to maximize the effectiveness of digital media dollars. The Audience Discovery Value Chain includes: 

  • Standardized Campaign Response Reports (‘What’)
  • Ad-Hoc Campaign Performance Slicing & Dicing (‘Which’)
  • Audience Clustering & Profiling (‘Whom’)
  • Optimization of a Single Digital Media Campaign (‘What Will’)
  • Optimization Across Multiple Digital Media Campaigns (‘What Will Work Best’)
  • Multichannel Marketing Optimization (‘What Will Work Best at Scale’)
  • Attitudinal Research (‘Why’)

Audience Clustering & Profiling (‘Whom’)

Akin to market segmentation, audience clustering is the process of categorizing individuals into distinct, mutually exclusive groups, based on similarities in product preference, geo- demographics, or psychographic attributes (values, interests, lifestyles). 

Advantages: Personas are useful tools for brands seeking to connect with prospects on an emotional level as they provide insight into consumer’s wants, needs and aspirations. It can be especially powerful when combined with brand awareness and favorability tracking studies.

Data: For years, offline marketers have used consumer information housed in marketing databases to identify and describe various consumer personas. This functionality is now available to online marketers, thanks to the emergence of data management platforms (DMPs).

DMPs store multivariate digital versions of interest, intent, and demographic data that online marketers can tap into for audience clustering. When combined with offline data, marketers can create the most complete picture of consumers to date.

Limitations: Audience clustering is not, in and of itself, necessarily a tool for predictive response modeling. It does not directly predict how an individual will respond to specific marketing stimuli. Rather, its value lies in its ability to describe and profile various classes of individuals.

Multichannel Optimization (‘What Will Work Best At Scale’)

Multichannel optimization employs predictive modeling and marketing execution technologies to optimize marketing spend across multiple channels, both on and off-line.

Multichannel Optimization -- the holy grail of marketing –- uses predictive modeling and intelligent marketing-execution technology to optimize marketing spend across all channels.

Use: Multichannel optimization helps the marketer maximize reach, revenue and profit by ensuring that consumer preferences are captured and that prospects are engaged in the way that will most likely have the greatest impact. Multichannel optimization is used for integrated campaigns (e.g. a campaign encompassing direct mail, TV ads and various digital media channels targeted at, for instance, a Nielsen PRIZM segment). Multichannel optimization is useful for gleaning actionable insight into each audience and for gathering cross-channel metrics.

Advantages: Multichannel optimization ensures that every consumer is engaged in the most efficient and effective way. More importantly, it ensures that channels are used in the best possible combination to achieve a fully integrated marketing campaign across all touch points.

Data: Integrating online and offline marketing must begin with integrating the various data contained in each so that marketers get a complete picture of their customers (a daunting task, but one that is becoming easier with the ever-growing means to tackle ‘Big Data’). For multichannel optimization to succeed, all players in the digital media ecosystem will need to speak a common language based on universal multivariate data pools with consistent and transportable audience definitions.

That means offline data, such as Nielsen PRIZM segments, TargusInfo, Acxiom, Experian and Epsilon must be brought online, and online behavioral data must be brought offline. Once that happens, true multi-channel optimization at scale will become a reality.

Limitations: At the moment, few marketers are audacious enough to attempt multichannel optimization at scale. It is, after all, an intimidating task, and marketers must take into account privacy considerations before proceeding. But those that do will develop a strong competitive advantage over those who fail to recognize the power of this approach.

Turning Knowledge into Action

The purpose of analytics is to serve the business of marketing and its goals of gaining market-share, growing top line sales and building the brand. Moreover, while some might claim that marketing analytics is an objective discipline, in truth, it is as much of an art as it is a science.

The numbers, when looked at objectively, may not lie, but knowing what to do with them is often a subjective exercise requiring a close partnership between marketing and analytics resources, combined with deep domain knowledge. Therefore, to truly take advantage of Big Data, the marketing organization needs to be intimately involved in the development of an ‘analytics road map’ that outlines marketing goals and objectives, and, at least at a high level, the intended approach.

The Audience Discovery Value Chain will sharpen an organization’s competitive edge -- as long as it translates the insights it receives from the data into direct action.  To accomplish that translation, the organization needs a sophisticated mix of people, technology and data.

 

 

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