Over the past two decades, marketers have driven toward one clear goal: Learnmore about your customers so you can present the right offer to the right person at the right time. To do so, 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. 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. Mobile devices literally add a new dimension (location) to customer interactions - if marketers can figure out how to take advantage.
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 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. 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 discover they urgently need. Three key areas will be involved in such capabilities: data, analytics and execution.
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 see 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 customer or prospect 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.
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. Preprocessing will also be essential for quick response.
The analytics 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.
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.
Humans will still design major new marketing programs, but they will need tools that make it easier 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 ROI 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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