Data Prediction/Regression/Classification

 Supply chain planning.  Learning seasonal variations is simple, we go a few steps further and can learn from POS transactions, sentiment and even traffic data.  Knowing what to order and how much reduces wastage, reduces costs in many areas and keeps the customer happy (reducing out-of stocks).

Supply chain planning.  Learning seasonal variations is simple, we go a few steps further and can learn from POS transactions, sentiment and even traffic data.  Knowing what to order and how much reduces wastage, reduces costs in many areas and keeps the customer happy (reducing out-of stocks).

 
 

know what to do next

Spectral Intelligence algorithms for prediction and regression are incredibly powerful tools for business and have been applied in the following instances:

  • Prediction of seasonal product by product stock on hand variations, in the interests of maintaining lowest possible inventory for just in time (JIT) fulfilment

  • Analysis of keyword and sentiment, in association with reward based feedback for customer query routing and solving

  • Multivariate regression for determining pricing to maximise revenue amongst competitor products in similar market
  • Customer retention algorithms – predicting when customers become ‘high risk’ of leaving

Don't do retrospective analysis.  Don't realise why your customers left, after they've gone.  Don't lose money holding stock that doesn't sell.  In your data, tucked away in correlations and cointegrations are all the clues.