IBM Accelerator Catalog
IBM Accelerator Catalog

Utilities Customer Micro-Segmentation

Customer micro-segmentation is a program used by utility companies to divide a company's customers into small groups based on their lifestyle and engagement behaviors.

Slide Two

Key Challenges

What is an accelerator?
Industry Accelerators are a packaged set of technical assets used to help you tackle your next data science project by addressing your most pressing business challenges. With sample data, notebooks, scripts, a sample application and more, you can kickstart your own implementation and leverage the power of Cloud Pak for Data.

  • Not all customers are the same, yet, without understanding and segmenting the customer base they can often all be treated in the same way
  • Energy and Utilities customers have different needs and interests. It is necessary to identify the customers with similar lifestyle and engagement.

Expected Business Outcome


Analyse lifestyle and engagement of the customers

Identify customer segments

Reach the right customers

Predict customer's Lifestyle and Engagement segments based on their demographic details, survey based questionnaire features relating to lifestyle, sustainability, historical energy usage and Cost-to-Serve

Identify group of customers with similar lifestyles and engagement

Reach the right customers with the right offers

Watch these illustrations of energy and utilities accelerator use cases for a better understanding of customers.

Watch the demo


Key Features

Information architecture

End-to-end AI Ladder application

Modular framework


An architecture enabling you to extract meaning from your data

From cataloging data through a glossary of terms to model development and deployment, simplify the lifecycle of your AI project

Composable and extensible pattern that can be applied to new data and industries

Get Started

Start experimenting today. Download and use this accelerator in your Cloud Pak for Data instance.

Get Accelerator Now

Highlighted Products for this Accelerator

IBM Cloud Pak for Data

Built on Red Hat OpenShift Container Platform, IBM Cloud Pak for Data accelerates your journey to AI to transform how your business operates with an open, extensible data and AI platform that runs on any cloud.

ViewLearn More

Watson Knowledge Catalog

Help your data users quickly find, curate, categorize and share data, analytical models and their relationships with other members of your organization.

ViewLearn More

Watson Studio

Empower your data science and AI teams to refine data and visually build and deploy models, using data on the desktop for anytime, anywhere access.

ViewLearn More

Watson Machine Learning

Deploy, monitor, and optimize models quickly, easily, and at scale.

ViewLearn More

IBM Knowledge Accelerators

IBM Knowledge Accelerators offer pre-created, extensive, curated glossaries to improve data classification, regulatory compliance, self-service analytics and other governance operations.

ViewLearn More

Related Accelerators

Utilities Demand Response Program Propensity

Which customers should be offered the opportunity to enroll in the Demand Response Program? Use the Utilities Demand Response Program Propensity accelerator to jump-start your analysis.

ViewLearn More

Utilities Payment Risk Prediction

Utilities Payment Risk Prediction is a program used by utility companies to identify customers who pose a risk and take preventive steps to remediate future revenue collections issues.

ViewLearn More

Utilities Customer Attrition Prediction

Use the Utilities Customer Attrition Prediction accelerator to jump-start your analysis and understand why your customers are leaving. Optionally, use Watson OpenScale to monitor and ensure that your models are free from bias.

ViewLearn More

Connect With Us

Additional details

  • Accelerator typeCloud Pak for Data industry
  • IndustryEnergy and Utilities
  • Business functionAny
  • Product and version Cloud Pak for Data,Watson Knowledge Catalog,Watson Studio,Watson Machine Learning - Current
  • Author typeIBM
  • Company nameIBM
  • Author name IBM
  • Last modifiedSeptember 28th, 2020
  • Language English