5 Things to Know About IBM Predictive Customer Intelligence
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This blog was written by Vivian Braun, IBM Worldwide Solutions Marketing Executive for Customer Service and Marketing
We are in the age of the empowered customer that has many organizations scrambling to relate to each individual customer on their terms with customized offers that fit their needs and desires. The paper Winning over the empowered consumer by the IBM Institute for Business Value states “Trust is widely recognized as the foundation of interpersonal, cons
1. What is IBM Predictive Intelligence?
IBM Predictive Customer Intelligence helps translate all the data and information you have about your customers (within and external to the organization) into insights and recommendations that help the organization understand and effectively interact with each customer. These insights and the ability to take action on those insights can drive long-term customer loyalty and value.
2. What makes up IBM Predictive Customer Intelligence?
IBM Predictive Customer Intelligence contains predictive analytics and decision management capabilities. Pre-configured industry specific models can be scored in real-time and recommended next best actions deployed directly at the point of interaction. Connectors are provided to IBM Big Data and marketing systems for deployment across all channels, and the solution also interacts with third party outbound and inbound marketing and customer services systems. The models can be tailored and extended to fit the organization's evolving and unique requirements in order to help recommend a personalized, relevant and timely offer/solution to each customer situation.
3. Where does the data come from that feeds IBM Predictive Intelligence?
All customer touch points can provide inputs for understanding who the customer is, how they interact with the business, what business they have done to date, and why they purchase goods or services. The data can be interaction, attitudinal, descriptive, and behavioral in nature. The sources of this data can be internal and external to the company and the data can be structured and unstructured. The data includes historical data, as well as, the here and now data (the context of the current interaction). Being self learning, the solution also consume feedback logs for continuous refinement of the models.
4. How does IBM Predictive Customer Intelligence fit into a business?
Think of the overall business (IT) environment in three layers. The bottom layer is a big data platform that manages a wide variety of data and information related to each customer. The middle layer is IBM Predictive Customer Intelligence that has an extensive set of predictive modeling and analytic capabilities that provide insights and recommendations to the customer facing business units within an organization. The top layer is Operations, or Systems of Engagement, that encompasses all the customer facing teams and systems that support and engage with the customer. Predictive Customer Intelligence integrates with these systems providing key information in real-time that the teams and systems use in their customer facing processes to improve marketing, sales, and customer service outcomes.
5. What are some of the industries that can take advantage of IBM Predictive Customer Intelligence?
Basically, any industry or sector that has customers they want nurture, keep and grow is a candidate for using Predictive Customer Intelligence. Currently, it is used heavily in following industries: telecommunications, energy and utilities, retail, banking, insurance and other service providers.
To learn more about IBM Predictive Customer Intelligence, see the IBM Redguide “Retain and Delight Your Customers by Applying IBM Predictive Customer Intelligence”, REDP-5163 at: http
Vivian Braun is the IBM Worldwide Solutions Marketing Executive for Customer Service and Marketing based in the UK. She has written widely on analytics use within industry.