Customer Data Analytics

Create deep and meaningful customer interactions across marketing channels

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Empowering marketers with predictive analytics to create relevant experiences for the engaged customer

Understanding the customer is at the heart of every business. Analyzing the massive data that is created during customer interaction with brands across various stages of the purchase funnel is a crucial step to offer customer-centric products and services. Sigmoid’s customer data analytics solutions provide detailed insights to carry deep data-driven segmentation and improve customer engagement. With predictive and prescriptive analytics, marketers can formulate targeted customer engagement strategies, plan marketing spends and deliver quality insights on consumer behavior to product development teams.

Unlock consumer insights with data and AI

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  • Voice of the customer
  • Personalization
  • Customer experience
  • Customer retention
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Marketing Analytics

Strengthen your business with marketing analytics

Looking to enhance delivery of tailored messaging to the right customer at the right time? Leverage data and predictive analytics for faster insights and higher ROMI by providing a multi-channel view of the customer to your marketing team.

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Customer success stories

Insights and perspectives

Podcast MTA with Reckitt, Sigmoid

Multi-touch attribution with Reckitt, Sigmoid

Infographic challenges in marketing optimization

Marketing optimization in the new normal

Whitepaper internal data monetization

A guide to effective marketing analytics

Customer testimonial


Customer analytics enables organizations to identify reasons behind customers churning by identifying patterns and predicting consumer behavior, and also recommend possible solutions to reduce churn. By analyzing customer data such as purchase history, interactions, and feedback, businesses can identify early warning indicators of customer dissatisfaction and disengagement. This enables them to take proactive measures, such as personalized offers, targeted communication, and enhanced service, to retain at-risk consumers and improve overall customer satisfaction, loyalty, and retention.

Analytics can be used to monitor customer journeys by implementing data collection tools, defining key stages, establishing KPIs, integrating data sources, analyzing customer behavior, and applying predictive analytics to comprehend and anticipate customer actions and behaviors at each touchpoint.

Companies can use customer analytics to enhance user experience by identifying pain points, personalizing experiences, gaining real-time insights for prompt interventions, conducting A/B testing to optimize UX, optimizing customer journeys, and analyzing customer feedback to address concerns and make targeted improvements. These data-driven strategies enable businesses to increase user satisfaction, boost engagement, and ultimately provide a superior user experience.

Customer analytics involves collecting, analyzing, and interpreting customer data to gain insights into behavior, preferences, and patterns. It encompasses techniques like data collection, segmentation, predictive modeling, and data mining to understand and predict actions, identify trends, and make data-driven decisions. By leveraging customer analytics, businesses can improve marketing strategies, enhance customer experiences, and drive overall performance by using actionable insights derived from the data.

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Leverage data and AI-powered consumer insights to better anticipate customer needs and offer personalized experiences.

Want to know how AI powered customer analytics solutions can improve your CX?