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, either because they were broadcast and vanished immediately or because they were physically persistent but inert, like a printed catalog or recorded TV/radio ad. Even messages that were dynamically tailored to a specific individual and situation were rendered and then frozen before they were sent. A website 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 an 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 tweet. 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 websites 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 makes 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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