Energy and utilities companies can benefit from deploying contact center analytics by identifying changing customer preferences by analyzing large sets of customer data which include customer queries, interactions on social channels, web chats, emails, and online customer activities. This data can provide companies crucial insights into customer preferences say, for example, which customers are likely to adopt solar, join micro grids, demand pay-as-you-go plans, or expect their utility to provide in-home energy management. By capturing inbound customer communications and transactions, companies can have a 360° view understanding of their customers. Using contact center analytics, energy and utilities companies can have extensive insights into their customers, enabling them to improve customer service, better plan for future customer needs and streamline operations. For instance, Natural Language Processing (NLP) and machine learning incorporated into a contact centers analytics infrastructure can help to analyze call center conversations and interpret notes and comments, while big data systems can provide ability to combine customer transactions from multiple channels. Advanced customer analytics can generate insights into unique customer segments, and their differentiated behaviors and predictive analytics can provide companies the ability to predict changing customer behavior.