ANALYTICS

INSIGHTS AND ANSWERS LURKING BEHIND THE DATA

METHODOLOGIES

ARIMA MODELS

ARIMA MODELS

Prediction based on moving average of observed variable and the prediction error

FOURIER SERIES

FOURIER SERIES

Prediction based on tracing the rhythm of the underlying influences

EXPONENTIAL SMOOTHING

EXPONENTIAL SMOOTHING

Prediction based on moving average of observed variable with emphasis on more recent observations

DECOMPOSITION MODELS

DECOMPOSITION MODELS

Forecasting by adding or multiplying trend, cyclical & seasonal components

MULTIPLE REGRESSION

MULTIPLE REGRESSION

Understanding the relationship between an observed variable & various predictor variables

LOGISTIC REGRESSION

LOGISTIC REGRESSION

Understanding influencing factors behind the choice of a particular decision route

DECISION TREE

DECISION TREE

Develop a classification model based on probability of each likely outcome

NEURAL NETWORK

NEURAL NETWORK

Building of a relationship model among unstructured data using artificial intelligence

ASSOCIATION ANALYSIS

ASSOCIATION ANALYSIS

Spotting cross-selling opportunities based on past purchase history

CLUSTER ANALYSIS

CLUSTER ANALYSIS

Segmenting a population based on maximum similarity within segments & maximum difference between segments

CONJOINT ANALYSIS

CONJOINT ANALYSIS

Finding a bundle of product features with maximum utility value

RFM MODELS

RFM MODELS

Finding most valuable customers based on recency, frequency & monetary considerations.

ANALYTICS IN ACTION|PREDICTIVE CAUSAL MODEL

Find out what factors influence your sales and predict future sales

Regression model is useful in finding potential factors that influence the historical sales performance, but it has limitations in predicting future sales.

Time-series model has done good jobs in predicting future sales, but it doesn’t provide any explanations.
Our expertise in developing predictive causal relationship models helped predict new period performance by observing the changes of significant influencing factors.
image 3 case study

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