Customer Analytics

Real-time customer intelligence and advanced analytics that drive greater engagement and growth.

Replace Guesswork with Data-driven Insights for Smarter, Faster Decision Making

Actionable algorithms enable intelligent audience activation and personalized engagement.

Micro-segmentation using RFME models

Dynamically identify and micro-segment customers using a wide range of personal characteristics, including demographics, purchase and browsing behavior, real-time cross-channel interactions, and explicit and implicit preferences. Monitor and model migration enabling marketing to drive relevant, timely campaigns and customer engagement.

Segment analysis and underserved audience identification

Gain a complete view of each segment, and its composition, including ARPU, brand affinity, RFME and more, for more strategic marketing, campaign planning and orchestration, using segmentation modeling and KPI modules.

Segment migration analysis and prediction

Track, analyze, and understand migration patterns; create and optimize predictive models that anticipate movement, to engage customers with the right messages at each point of the customer journey, using segment behavior analysis.

Algorithms that Predict Churn, Profitability and Lifetime Value for Customers

Churn prediction algorithm
Model your customer base to proactively identify likely to churn candidates, using churn modeling. Use the insights to create effective customer retention strategies that increase engagement, customer satisfaction, loyalty, and lifetime value.
Propensity models

Drive increased share of wallet by introducing new categories to existing customers with affinities for them. Improve response rates by matching promotions and marketing events with the customer segments most likely to respond to them.

Customer lifetime value (CLTV) algorithm
Know the future value of every new customer and opportunity before you acquire them and adjust your marketing strategies and tactics accordingly. Identify your most valuable customers and prioritize investments to satisfy and retain them.

Drive intelligence-based customer engagement with prescriptive analytics models

Market basket analysis models
Understand basket composition of customer by segment, identify preferred and hidden affinities between products and brands, and develop relevant cross-sell promotional strategies to increase basket size and average spend.
Integrated next best action and real-time experiences activation

Recommend best offers, products, and combos (complete the look) based on real-time customer behavior, personas, lookalikes, browsing history and past purchases to improve average spend and customer loyalty.

Out-of-the-box Customer Metrics for Real-time Insights

Custom Build Data Science Models with Ease

Advanced platform for data preparation

Source of clean, connected, aggregated customer data and a platform for data exploration, hypothesis testing and data preparation.

Easy-to-use model building workflow

Wizard for quick algorithm development. Built-in model accuracy improvement techniques, such as outlier treatment, missing value treatment, variable significance testing, and train and test approach.

Custom model import and management capabilities

Ability to import and run PMML models for custom analysis and execute algorithms via API.

Model publishing

Automated customer scoring schedule management and marketing execution through advanced list management.

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Resources

Guides

Dynamic Content Personalization: How Active Content Brings Dynamism into Your Campaigns

Let’s face it—customers nowadays expect deeper and relevant communication, not cookie-cutter-styled messaging across every channel.

Case Study

Personalizing Beauty at Scale: How Matas Grew Attributable Sales by 36% with Personalized Recommendations

Deliver a best-in-class customer experience, increase online sales, and drive operational efficiency at scale