Statistical modelling/algorithms

In this data-driven economy, organizations have enough data to work with, more ways to extract actionable intelligence from data. Growing data volumes with the promise of insights and the organizational imperative to keep robust analytical approach to find answers to business problems have made statistical modelling valuable and effective to transform data into insightful decisions.

Statistical modelling

Where organizations are driven to influence and establish successful future outcomes, predicting future actions across operations give them the lead to get future-ready and take competitive lead. From predicting wants and behaviors to customer churn, statistical modelling becomes a potent tool to build predictive engines across business operations.

Whether it is about rolling out personalized campaigns to increase customer loyalty or forecasting customer demand to ensure that right stocks are available at the right place at the right time, enterprises seek to make quick intelligent decisions to create successful outcomes. As organizations look to augment their decision engine, Saksoft augments enterprise decision making by leveraging mathematical models to help predict the impact of possible decisions.

Statistical thinking is at the core of our Data Science practice. Our team helps organizations get the most out of heterogeneous data sources, takes advantage of model-based predictions and promotes data-based strategic decisions. The team at Saksoft is well versed in using a range of frameworks for statistical modeling including:

  • Clustering

  • Predictive modelling

  • Scoring

  • Recommendation systems

  • Market segmentation

  • Time series

  • Attribution modeling

  • Supervised classification

At Saksoft, Data science and domain experts work closely with organizations to understand business problems, deploy statistical modelling techniques to create positive influences on future outcomes. We help organizations make the most of data, leverage statistical data modelling to make faster, smarter and insight-driven decisions across operations.

Our statistical modelling techniques encompass regression models, stochastic methods such as exponential smoothening, nonparametric models and Bayesian model. We leverage statistical modeling to strengthen areas including Capacity planning, Demand forecasting, Inventory management, Customer behavior analysis, Social media analytics, Consumer segmentation and Promotion spend optimization.

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