Online media accounts for about one-third of consumers' time, according to Forrester Research, but receives less than one-sixth of all advertising expenditures, according to PricewaterhouseCoopers and Wilkofsky Gruen Associates. So, it's a safe bet that marketing systems will increasingly need to support online advertising.
This is a challenge for current products developed for outbound campaigns via mail, email and telephone. In active campaign systems, even real-time interactions are treated as extensions of traditional campaign flows rather than versions of online advertising.
The distinction is significant. Outbound marketing assumes that marketers know who will receive their messages, can control the delivery of those messages and can directly capture responses. It further assumes that the promotions are the primary influence on consumer behavior. This lets marketers execute carefully structured champion/challenger tests to measure the impact of alternative customer treatments.
Advertising results have never been anything truly measurable. Advertisers in traditional mass media had only the vaguest notions of who was seeing their messages. Most measurements relied on consumer samples such as panels or surveys or on statistical correlations captured in marketing mix models. Despite formidably complex statistical techniques, these methods are inherently imprecise measures of marketing impact.
The flood of data provided by online advertising seems to offer an escape from the uncertainty of traditional media measurements. Unfortunately, it won't work. The key assumptions of outbound campaigns - that marketers control who receives their messages, what those messages contain and how customers can reply - are not true in the online advertising world. In online advertising, consumers decide where to direct their attention. Marketers can access an audience with presumed interests and attributes but cannot target specific individuals in advance.
Online advertisements are delivered in the context of some other consumer activity, such as visiting a Web site or conducting a social interaction. This greatly reduces the amount and type of content that can be delivered. More important, the online environment contains information from competitors, neutral experts and other consumers. Even if the consumer is lured to the marketer's own Web site, she can exit at any time.
Although many interactions are captured, few are directly linked to an actual purchase. This invalidates the central simplifying assumption that a single promotion can be credited for causing a specific purchase. With this cornerstone removed, champion/challenger testing requires elaborate analytical scaffolding for support. The challenge is magnified because interactions may be recorded but not linked to the same identity, making it difficult to understand the full set of contacts that influenced each consumer.
If a common problem threatens the outbound campaign systems, it's the need to handle unstructured data. Online advertising can capture huge amounts of detailed information about each consumer and each interaction, including Web pages the consumer has visited, competitive ads the consumer has seen, comments she has posted, profiles gathered by third parties, geographic location and even the interaction device (computer, smartphone, kiosk, etc.). But the structure of this data and the significance of individual attributes are not always known in advance. Thus, systems must analyze data in many different ways before they can identify features relevant for marketing. From a technology perspective, this implies specific capabilities, including storage and easy access to unstructured data, text and semantic analysis to extract and classify contents, audio and video analysis to deal with nontextual content, time-series and pattern analysis to identify significant behavior patterns and network analysis to understand social media influences. None of these are handled easily by traditional outbound campaign systems, which assume a highly structured environment.
The second new core requirement is better prediction of correlation between content and subsequent behavior. Traditional champion/challenger tests can't isolate the impact of the large number of contextual variables that apply in online marketing interactions. Even if they could, consumer behavior is too volatile to assume relationships remain valid weeks or months after they are collected. Rather, marketers must deploy self-adjusting models that can observe consumer behavior and predict which content (both tested and untested) is likely to be effective under different circumstances. Beyond predicting immediate response, marketers need new ways to track long-term results. This requires linking fractured consumer identities from first and third-party cookies, member profiles, social media personas, email addresses, IP addresses, location, customer accounts and other sources, each with varying degrees of anonymity, while respecting legal and ethical privacy constraints. As with traditional advertising, marketers will often find themselves relying on consumer panels and surveys to gather data that cannot be assembled without individual cooperation.
A third key requirement is data gathering, analysis and execution across complex networks in real time and near real time. These capabilities will evolve over time: It will be easier to execute dynamic models on your company's own Web site than through a third-party ad network. But as the advantages of superior content selection become apparent, marketers will increasingly press for the ability to deploy them more broadly.
All of these capabilities - unstructured data management, self-adjusting analytics and real-time execution - are outside the scope of traditional outbound marketing systems. Whether existing vendors can adapt to support them or whether new systems emerge will determine who dominates the growing market for online marketing execution.
David M. Raab is a principal at Raab Associates Inc., a consultancy specializing in marketing technology and analytics. He can be reached at email@example.com.
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