Advanced analytics

There has been an unprecedented growth in volume, variety, and velocity of the data being generated today. Though this comes with challenges with respect to storing and processing at this pace, it also presents opportunities to mine and extracts value out of the same. We provide distinctive strategies and solutions to discover valuable acumen from data and convert those into business benefits. We deep dive into your data and turn it into a competitive advantage. We help you effectively utilize pertinent customer information and win customer adoption. Our analytics knowledge combined with deep domain knowledge supported by embedded AI/ ML models intelligently builds data strategies and transforms you into an analytics-driven organization. Our deep understanding of the broad spectrum of analytics-based assets and market-tested approaches deliver valuable insights that help in better decision making and improve your customer satisfaction.


We offer the following advanced analytics-based and machine learning-powered solutions

  • Customer churn analysis

    Businesses can analyze when the customer is likely to churn and based on that, retention and marketing policies can be decided. We use classification, association and survival data science models to predict the churn propensity of a customer.

  • Customer retention

    Through customer’s brand association and feedbacks to surveys/social media on brand loyalty and brand satisfaction, businesses can categorize/segment customers and target with appropriate and specific campaigns for the respective segment. For example: Focusing on improving the customer experience for loyal but dissatisfied customers, whereas providing loyalty benefits offers for satisfied but not-so-loyal customers.

  • Sentiment analysis

    With the advancements in deep machine learning, multi-channel data mining techniques, and natural language processing algorithms, sentiment analysis solutions can provide a competitive advantage to the business with a large web and mobile presence. Business can monitor the conversation and engage with their promoters/influencers and detractors across multiple channels and design loyalty offers and other customer engagement strategies.

  • Security and regulation

    This is becoming an evidently increasing concern in the telecom industry and the use of social networks helps in identifying and reducing/preventing security threats. Based on social data mining, deep learning, and natural language processing techniques, this can provide CSPs to support law enforcement in identifying and preventing potential criminal and terrorist activities.

  • Segmentation and targeted offerings

    Segmentation and targeted offerings model is a customer-driven and not a product-driven methodology of marketing that helps businesses deliver appropriate and personalized messages to engage with respective customers and to identify the segments and groups across their large clientele. Designed based on clustering and response propensity modeling, it enables the business to look at a combination of optimization models to get maximum revenue and profit used for each of these segments.

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