| When it comes to optimizing marketing performance it takes the right combination of capabilities to drive measurable improvement. First, it takes the most predictive customer intelligence that can be created to drive strategic and analytic processes. Predictive Intelligence (PI) is the art and science of integrating data, technology and predictive analytics to generate actionable marketing insights. A Predictive Intelligence engine is designed and maintained as a long-term asset that continually gets smarter and drives incremental performance improvement and value to the broader organization. Predictive Intelligence drives performance through smarter data, smarter analytics and smarter marketing.
What is Predictive Intelligence?
 There are many approaches to improving marketing performance from a strategic and analytic point of view and Predictive Intelligence is another approach for marketers to consider. PI integrates the marketing disciplines of data, predictive analytics and technology to create the most predictive custom attributes possible for a given business application. The blending of these marketing disciplines represents the science of creating PI. The art of creating PI comes from the ability to assimilate business challenges and objectives, marketing strategy, customer behaviors, competition and other influencing internal and external factors to establish the context for and the application of Predictive Intelligence.
The practical use of PI must be considered to fully utilize its value. Therefore, the skills required to create and implement PI go beyond modeling and analytics into the ability to deploy it effectively against clear business objectives. The successful PI engine requires commitment to innovation, application development, research and development and testing. This commitment coupled with the right approach, the right marketing environment and the right team creates an asset that is fully leveraged through the organization, yields a maximum return on investment and creates competitive advantage. The payback not only maximizes marketing performance, but also extends into customer service, billing and collections, risk management, enterprise growth strategy, research and development and many other industry specific functions.
Manufacturing Predictive Intelligence
There are three steps to manufacturing Predictive Intelligence.
Step 1 - Static & Compiled Data
The first step is to source and integrate multiple, often hard to find static and compiled data that proves to be valuable in terms of its predictive power. This data includes:
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Step 2 - Dynamic, Proprietary & Unique Information
The second step is to leverage static and compiled data to manufacture predictive information. We catalog derived data attributes into predictive information layers which include:
- Descriptive Consumer Indexes that support descriptive modeling processes
- Behavioral Propensities that support predictive modeling processes
- Consumer Behavior Deltas that provide trigger based capabilities
Step 3 - Optimized Highly Predictive Intelligence
The third step is to integrate your customer data with predictive information layers to create highly predictive custom attributes for optimizing performance. These attributes are then processed through dimensionalizing programs to determine their predictive value. These programs process different types of attributes including:
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Allant maintains a library of pre-configured data structures, processes and methodologies for rapidly deploying predictive intelligence for specific marketing challenges like acquisition, growth and retention. In addition, Predictive Intelligence continually re-adjusts to search for new patterns as new data is introduced. This self learning process enables the Predictive Intelligence models to become more robust - producing improved insights which lead to sustainable, competitive advantage. |
