• ...
  • ...

Open a Window to the Future

Use past data such as consumer purchase patterns, percentage changes or averages.
It could be applied to various departments such as production, inventory, finance, marketing and sales.
Tools Used – SPSS, SQL

Determine optimal actions that can trigger best outcomes Collect sales & marketing trends and data from CRM, ERP, HR and other systems to make predictions on consumer behaviour, supply chain, inventory and operations.

  • Root Cause Analysis - Why happened?

  • Identifying correlated data.

  • Pattern Identification – action to correct a process.

Predictive Analytics - What will happen next?

Predictive analytics is used to study what can happen in the future based on past trends & results, and helps predict the likelihood of a future outcome by using various statistical and machine learning algorithms.

Determine and deal future events in advance and seize future opportunities

Predictive analytics allows to forecast how behaviours will change and market shares will move under different packaging, messaging and pricing scenarios by linking the sales transactional information to attitudinal research findings to improve business performance.

  • Analytics and Predictive Modelling.

  • Derive trends from your data.

  • Learn customers' purchase propensity within the category and for your brand.

  • Learn customer's churn risk and how to mitigate that risk.

Respond to challenges and take advantage of future trends

  • Forecasting Future Trends

  • Monte-Carlo Simulation – What may happen?

  • Decision tree models

  • Regression

  • Clustering

  • Neural networks

  • Machine learning

  • Random forests and gradient-boosted random forests

  • Prescriptive analytics

  • Text analytics

  • Social media analytics

Prescriptive Analytics - Reduce ambiguity and gain better clarity

Prescriptive analytics uses simulation and optimization to suggest possible outcomes and result in actions to impact on the key business metrics.

Organizations use this field of analytics to get a list of probable outcomes to a new growth initiative by using historical data, big data and behavioural patterns.