
Strategy Formulation for businesses: looking beyond variable importance
For businesses, while it is important to have an accurate model, an interpretable model is equally important. Apart from wanting to know what our model’s prediction is, we also wonder why it is it high/low and which features are most important in determining the forecast. (Most machine learning algorithms produce variable importance as a part […]

Assessing market demand using Neural Networks
Objective The objective was to assess and forecast demand for a retail outlet, using Neural Networks. Approach In order to conduct the analytics, we applied the concept of Multi-Layer Perceptron (MLP) in Neural Networks which can classify and predict the patterns accurately. The inherently non-linear structure of neural networks is particularly useful for capturing the […]

Understanding the factors that make a brand a ‘favourite brand’
Client: A global fast food restaurant chain Objective The client intended to find the performance attributes driving the “Favourite brand” of the category where the population is more heterogeneous. Approach Since the population was heterogeneous in nature, merely aggregating the data and deriving the set of drivers (factors driving the brand’s success) would not have […]

Tapping the pulse of ‘Digital India’: understanding challenges and solutions
OBJECTIVE ‘Digital India’ has emerged among the most discussed phrases in the country. It certainly piqued our interest too. In order to understand the challenges and solutions related to achieving a truly ‘Digital India’, we executed an online study (named India Online Study) in association with India Open Data Association (IODA) and IIM Lucknow. The […]

Helping a healthcare brand assess the market using Latent Class Segmentation
BUSINESS CHALLENGE Scientists around the world have made advances targeted towards improving the body’s immune system for the treatment of various types of cancer. These advancements have led to new therapies. This survey we executed focused on the treatment of cancers, across different tumour types. The purpose of this research was to understand how the […]

Determining the right price of a product using Price Sensitivity Measurement (PSM) Analysis
OBJECTIVE Getting the price of a product right is one of the most challenging issues faced by a B2B marketer. Price Sensitivity Measurement (PSM) Analysis is one of the marketing techniques for determining consumer price preferences by assessing different price-levels to provide recommendation on the most optimal price of a product. The aim of the research […]

Gauging what works best for a brand using correspondence analysis and hierarchical clustering
OBJECTIVE Marketers have always had to manage goals such as making their brands distinctive, making them central in their category, and understand competitors. The objective of the study was to understand how brands and a list of attributes/features are perceived by consumers. While understanding why a customer chooses a particular brand repeatedly over time, the […]

Developing a Recommendation Engine using Hybrid Approach
Client: A cloud-based interactive smart video platform that delivers personalized interactive videos on-demand to consumers. Objective Business: Increase time spent on site, number of videos watched, and repeat visits. The Engine: Devise an engine that offers relevant recommendation dynamically and in real-time. The Need Real-time recommendations need to be self-learning and based on massive amounts […]

MaxDiff modelling for product feature optimization
Objective To understand which product features or applications are most important to a particular market. Approach An online quantitative survey was conducted that included a MaxDiff exercise in which 40 different product features were evaluated on what is best and worst among 15 sets with 4 features in each set. MaxDiff modelling was used over […]