2010 Jul 01

Autonomous Marketing Messages
David M. Raab
Information Management
July / August 2010

Here’s a metaphysical puzzle: can you send a marketing message before it’s created?  The answer used to be no: messages remained unchanged after they were sent, salve either because they were broadcast and vanished immediately or because they were physically persistent but inert, like a printed catalog or recorded TV ad.  Even messages that were dynamically tailored to a specific individual and situation were rendered and then frozen before they were sent.  A Web site might adjust its offers over time, but each offer was itself fixed.

Because marketers knew the contents of each message when they sent it, the only subsequent information they needed was who received it and how they reacted.  Indeed, most marketing measurement boils down to answering those two exceedingly difficult questions.

But marketers today face an added challenge: capturing the message itself.  Paradox notwithstanding, an increasing number of messages can now change after they’re created.  Consider:

– Adobe’s latest design software, CS5, can create ads that send different messages to different individuals and record the results.  Specifically, Web designers can embed the testing, segmentation and automated optimization of Adobe’s recently-acquired Omniture Web analytics system.  The solution relies on the Omniture server to execute tests and store results.  But the next logical step is to embed test logic, tracking and automated self-optimization within ad itself so it can function when a server connection is unavailable.  This would result in a truly autonomous marketing message.

– Vendors including smartFocus, Genius.com and Genoo have extended social media sharing to tag each item with the ID of the individual who shared it, so they can be credited as the source of later visits by recipients.  In other words, if Jane posts a link to this article on Twitter, marketers will later know not just which visitors came from Twitter, but also which came from Jane’s Twitter post.  This lets them measure how much traffic Jane generates and identify the members of Jane’s social network.  In effect, the original message is being modified by adding the identity of each sharer, which must then be captured with responses.

– Barcodes on products and advertisements are being linked via mobile phone applications to Web sites that vary their content based on location.  Here, the original message is being enhanced with the viewer’s location and, perhaps, actual identity.  One obvious use is to deliver different offers based on local weather and competitive promotions.  Vendor StickyBits make a buzzword triple play by adding social media to mobile and geo-targeting, with separate social media sites for different locations of the same UPC code.  Since the social site also evolves, marketers can only know the message received by each consumer if they capture a snapshot of the site as it appeared to each visitor.  They must also capture whatever contextual variables (time of day, weather, competition, current promotions, etc.) play into offers and results.

These examples point to the emergence of autonomous marketing messages: communications that are launched into the world to operate more or less independently, occasionally phoning home like a dutiful college student to report results and perhaps get some advice.

The concept poses challenges for everyone involved.  For marketers already struggling with the transition from one-way broadcasts to peer-based communities, it’s a further loss of control.  For technologists serving those marketers, it’s another set of delivery systems and reporting systems to manage.  For marketing analysts, it’s a new type of data to incorporate.

But the concept also creates new opportunities for success.  Messages that can track their own movement from consumer to consumer can provide important insights into the always-mysterious connection between messages sent and resulting customer behavior.  Autonomous viewer logs, testing and optimization can enhance media where continuous real-time connections to central servers are unavailable.  Periodic contacts with central servers let the applications download their information and update their libraries of offers, models and business rules.  Combining mobile, location and social media provides rich information about consumer behavior, along with direct opportunities to deliver highly targeted messages.

Autonomous messages add to the flood of data already generated by digital marketing.  This increases the need for ways to load, store, access and analyze tremendous volumes at reasonable cost and speed.  Similarly, the complex and variable structure of the new data reinforces the existing demand for technologies that can easily incorporate new data types and models.  Autonomous messages also require improvements in techniques to automatically uncover significant patterns within the data and infer appropriate marketing treatments.

The major new challenge posed by autonomous messaging is portability.  Autonomous systems must somehow incorporate decision rules, self-adjusting analytics, alternative treatments and data capture mechanisms while making minimal demands on host resources.  This is a particular issue in mobile environments, where bandwidth, storage and processing power are scarce.   The messages must also find efficient ways to exchange data with central servers.

Customer identification is another issue.  Autonomous messaging could ease some privacy concerns by tracking and responding to behaviors without sharing them externally.  But it also extends to platforms where customer identification is more difficult than usual, making it still harder to gain the most value from data that marketers have permission to use.

Progress will be incremental.  The immediate future will see hybrids that combine different aspects of autonomy with centralized techniques.  Marketers and technologists will need to assess the strengths and weaknesses of each approach and look for opportunities to combine them to deliver solutions more powerful than any one method provides by itself.

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David M. Raab is a Principal at Raab Associates Inc., a consultancy specializing in marketing technology and analytics.  He can be reached at draab@raabassociates.com.


2010 Mar 01

Marketing Systems for OnLine Media
David M. Raab
Information Management
March / April 2010

Online media account for about one-third of consumers’ time (1) but receive less than one-sixth of all advertising expenditures (2).  So it’s a safe bet that marketing systems will increasingly need to support online advertising.

This is a challenge for current products, find which were developed for outbound campaigns via mail, story email and telephone.  Even real-time interactions have been 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, and 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 anywhere near as 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 are inherently imprecise measures of marketing impact.

The flood of data provided by online advertising seems to offer an escape from the uncertainly 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 contains and how the customer 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 as “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 is not always known in advance.  Thus, systems must analyze it in many different ways before they can identify features that are 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 non-textual 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 relations 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 with varying degrees of anonymity, all 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.

(1) Forrester Research, “Consumer Behavior Online: A 2009 Deep Dive”, July 27, 2009
(2) PricewaterhouseCoopers and Wilkofsky Gruen Associates, “Global Entertainment and Media Outlook: 2009-2013”, June 16, 2009

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David M. Raab is a Principal at Raab Associates Inc., a consultancy specializing in marketing technology and analytics.  He can be reached at draab@raabassociates.com.

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2010 Jan 01

Marketing Infrastructure for a Customer-Driven World
David M. Raab
Information Management
January / February 2010

Over the past two decades, ask marketers have driven towards one clear goal: learn more about your customers so you can present the right offer to the right person at the right time.  Companies have gathered data from more sources, analyzed it in more detail, and built more elaborate campaigns tailored to more precisely defined segments.  But the fundamental premise has remained the same: marketers initiate the campaigns and hope that customers react.

That model no longer applies.

Today, customers are taking control of the relationship.  They block inbound marketing messages and instead reach out for information when they want it.  And when they do seek information, they’re more likely to trust external sources, including social media such as Facebook, YouTube, Twitter and blogs, than the company itself.

As if that weren’t challenge enough, marketers must also adjust to changes in the communication channels.  Mobile devices literally add a new dimension (location) to customer interactions – if marketers can figure out how to take advantage.  Online channels offer a tantalizing glimpse of endlessly detailed consumer data – if marketers can penetrate technical and legal barriers to identifying who is doing what.

No one is more aware of these changes than the marketing automation vendors.  But companies like Unica, SAS , Teradata, Aprimo and Oracle/Siebel originally engineered their systems for traditional outbound marketing.  All have added some support for real time interaction management, but their recent enhancements have largely been aimed at improving the efficiency of outbound campaigns.  Common improvements have focused on campaign optimization, marketing resource management, performance measurement, improved interfaces, and closer integration among separately-developed components.

Smaller and newer vendors, particularly those serving online and business-to-business marketers, have been somewhat more nimble.  Yet no vendor can move too far until marketers know which features they need.  The best practices in this new marketing world have not yet emerged.

But even though the application details are still vague, we can already outline the foundations needed to support them.  From an IT perspective, this is enough to begin work on the capabilities that marketing will tell you tomorrow they needed yesterday.

– data.  Marketers will want much more information.  Traditional marketing databases hold basic profile information (address, demographics, etc.), transaction history (purchases and possibly other interactions such as payments and service requests), and promotions sent.  These might be supplemented with derived information such as model scores and segment codes.  Future marketers will want to a consolidated timeline of every Web page view, every social media comment, and every location the customer has visited.  They’ll also import more external data, such as competitive advertising that customers were exposed to, relationships within social networks, and behaviors of similar individuals who are tracked in research panels.  This implies storing huge volumes of data – the Web details alone could be an order of magnitude larger than today’s typical marketing systems.  The systems will also need to recognize the same person across different channels and to update and access information during real time interactions.  Real-time and near-real-time updates alone require fundamental changes in how marketing databases are designed and managed.

– analytics.  Much data is more useful when it’s been summarized and classified.  For example, the business rules that will help to drive many interactions require records to be clustered into manageable numbers of categories: otherwise, the rules themselves get too complex to manage.  Pre-processing will also be essential for quick response.  The analytics themselves must execute more efficiently, so that scores and segment codes can be updated as soon as new data becomes available, models are revised as behaviors shift and the environment changes, and optimal allocations are recalculated in response to new conditions.  Greater use of analytics also means that analytical processing must become more automated, with human experts shifting from hands-on model building to deeper innovation and monitoring the quality of the automated systems’ output.

– execution.  Speed will dominate the requirements for marketing execution.  Insights from analytical systems must be immediately translated into marketing decisions and then transmitted to operational systems that are managing the actual interactions.  Even outbound campaigns will be triggered by customer activities rather than marketer-determined schedules.  The systems will also need continuous automated processes to test alternative treatments, deploy the winners and monitor the long-term results.  Major new marketing programs will still be designed by humans, but they will need tools that make it vastly easier than today to build, deploy and measure complex treatment strategies.  Ultimately, marketers will manage a self-optimizing environment that looks beyond individual interactions to allocate corporate resources across all customer-facing investments.  For example, the system might decide each morning whether it should schedule more customer service agents for the afternoon shift or invest the money in another round of keyword advertisements – taking into account both long-term return on investment and real-world constraints such as cash flow, profits and quarterly revenue targets.

Such intense dependence on technology poses many dangers and requires substantial organizational change.  But companies that overcome these barriers will flourish in the new marketing environment – and gain a substantial edge over companies that do not.

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David M. Raab is a Principal at Raab Associates Inc., a consultancy specializing in marketing technology and analytics.  He can be reached at draab@raabassociates.com.