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Thriving in the Future

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Forecasting & Optimization

Strengthen decision-making to achieve key performance goals

By leveraging a range of forecasting and optimization techniques, we help you to forecast demand in every business area that is critical to your business expansion - from macroeconomic and demographic models with behavioural equations and time series techniques.

  • Linear regression

  • ARIMA

  • Logistic regression

  • Multiple regression

  • Exponential smoothing

  • Time-series

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Multidimensional Analysis Framework

Using analytic techniques such as multivariate analysis and data modelling reveal optimization opportunities.

Implement segmentation solutions using data reduction techniques, such as factor and cluster analysis, to identify the most lucrative segments of your audience.

Partial Least Squares Path Modeling (PLS-PM) to identify drivers of brand attraction or choice

A statistical approach for modelling multivariable relationships (structural equation models) among different sets of variables, uncovering which (independent) variables have a predictive impact on the outcome of other (dependent) variables. It also provides statistical testing of these relationships - factor loadings that indicate the strength of the impact between the two types of variables.

We use a number of methods to determine how consumers react to price adjustments.

MaxDiff Scaling provides insight into the differentiation between consumers’ options.
Latent class segmentation analysis into how different groups of consumers base their purchase decisions on the different product/service attributes.

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Optimization of product configuration alternatives

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Product Pricing and Marketing response analysis

Van Westendorp Price Elasticity Modelling, stress-tests the range of prices consumers expect to pay for product/service, while conjoint analysis measures price tolerance given various alternative options.

Experimental design-based methods can reinforce findings of how many consumers will buy product/service under various price options.

With Choice-Based Conjoint (CBC), we help determine best fit product/service options in terms of sales, revenue, and profitability.

A combination of CBC modelling and consumer segmentation helps determine how your target audience will react to specific product/service attributes.

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Discrete-choice modelling

What should we do better?

Smarter decisions in the data-driven economy
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Artificial Intelligence & Machine learning

Machine learning is an artificial intelligence (AI) technology which allows machines to learn by using algorithms to predict outcomes and learn from successes and failures.

“What should we do better?”

  • Highlight the root causes and understand why problems occurred.

  • Optimize outcomes that help achieve best business objectives.

  • Identify data uncertainties to make better decisions.

Speed up intelligence delivery with machine learning algorithms and models

  • Decision Trees and Random Forest

  • Regression models

  • Clustering

  • Support Vector Machines

  • Reinforcement Learning algorithms

  • Dimensionality Reduction algorithms

  • Deep learning

  • Hidden Markov models

  • Artificial Neural Networks

Our research analysts make the most of open source machine learning frameworks including TensorFlow, Spark ML, Scikit-learn and Apache Spark MLlib to augment Sales forecasting, Customer data interpretation and churn detection, Sentiment analysis and Behaviour tacking, Personalized customer recommendations and Fraud detection.

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The Cognitive Advantage

Cognitive analytics empower organizations to go from big data to smarter decisions that transform business value.

We help apply cognitive analytics in the areas of customer service, production and supply chain, and risk assessment.

  • Build intelligent chatbots leveraging cognitive analytics

  • Embed cognitive analytics in recommendations, trends, products and pricing to promote personalized customer experience

  • Use NLP for identifying patterns and performing sentiment analysis