Predictive Analytics

Help businesses in their race for a bigger customer base

Predictive analytics is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future.

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Why is Predictive Analytics important?

Optimizing marketing campaigns

Improving operations

Sales Forecasting

Predictive analytics are used to determine customer responses or purchases, as well as promote cross-sell opportunities. Predictive models help businesses attract, retain and grow their most profitable customers

Many companies use predictive models to forecast inventory and manage resources. Airlines use predictive analytics to set ticket prices. Hotels try to predict the number of guests for any given night to maximize occupancy and increase revenue. Predictive analytics enables organizations to function more efficiently.

Sales forecasting is the process of estimating future revenue by predicting the amount of product or services a sales unit (which can be an individual salesperson, a sales team, or a company) will sell in the next week, month, quarter, or year

Use Cases

Merchendise Planning & Price Optimization

Get the Right merchendise to the right store

Customer Inisght

Understand exactly what your customer want

Supply & Demand Planning

Accurately plan for customer demand