Performance Analytics

The solution provides insights on various KPI's related to the performance of the marketing and service divisions of a major white goods manufacturer. The solution aims to empower the business and operational users in taking effective data driven decisions to improve business and overall process efficiency. The reporting is available at various cuts, and provides the users the flexibility of drilling down to any level of granularity based on their business need.


Sales Force Productivity

The solution provides insights to the sales managers on the performance of the individual sales representatives working under them, and identifies scope for performance improvement. Some of the identified key metrics of performance management are dealer penetration ratio, opportunity to win ratio, rate of follow up contact, revenue generation and cross sales generated.


Export Pattern Analytics

The solution highlights the trend in export pattern of sea food from India for a particular client and its identified competitors in sea food export. The analysis of export trends has been done at the following levels:

  1. Product Level - Highlights the species/grades of the sea food that are exported from India at the highest average price. Compares the market share of the company in the total export of the most expensive grades across geographies
  2. Country Level - Highlights the top countries that import sea food from India, and the market share of the client within all its operating countries. The solution also focusses on the variations of average selling price of sea food between the client and its competitors and whether the variations have any impact on the market share of the client in these countries
  3. Importer Level - Highlights the top importers of the client, and its corresponding market share among them. Reports the importers whose purchase from the client has significantly dropped over a period of time
  4. Competitor Level - Focuses on the top competitors of the client, along with the variations in their selling price.

Financing Scheme Analytics

The goal was to track the effectiveness of financing schemes offered by the client to its various dealers across the country. The solution involved computing KPIs like Amount Financed, Financed Volume & Cost per Unit across locations, counters, scheme types, product groups & models.


Trade Scheme Analysis

The primary objective was to track the various branch schemes offered by the client to its dealers across the country. The analysis analysed the effect of increase in trade schemes in quantity sold, material cost per unit, gross margin and sales mix of different models across location, dealer categories and counters. It also analysed the effect of branch schemes during festive & non-festive period.


Analytics for Optimal Spares Stocking

The objective was to increase customer satisfaction through reduction in call closure delay. One key parameter driving the call closure time is the availability of spares with the service franchisees. The soluion uses various forecasting algorithm to forecast consumption of different spares at the franchisee level and then uses franchisee level capital constraints and lead time for delivery of spares in an optimization model to recommend the monthly spares stocking at the franchisee level.


Campaign Analysis

The solution recommends dynamic allocation of funds for advertising through different Channels, aiming to achieve optimum Return on Investment. It uses marketing mix modelling to understand how advertising activities interact to drive purchases. This is done using multivariate regression models that looks comprehensively at all drivers to evaluate the contribution of each channel in terms of its sales impact and ROI. The solution then optimizes the marketing mix based on business goals e.g. ROI on ad-spend maximization

Predictive Modelling and Simulation techniques are used to run thousands of scenarios for business planning, accounting for elasticity of business drivers. The solution then dynamically allocates funds for advertising through different channels, utilizing the results of attribution and optimization analysis, measuring outcomes, and validating the models. The business can then make course corrections as needed.


Price Elasticity Analysis

The solution derives a demand price relationship based on historical data, taking into account factors such as location and seasonality. It provides the users the capability to perform scenario analysis on various price points in order to identify the "right" price points.


Sales Forecasting

The solution forecasts the weekly sales of various products, taking into account factors such as seasonal fluctuations, festive period effect, effect of trade schemes and promotions,etc. An ensemble modelling approach is used that leverages a library of predictive modeling algorithms and chooses the best fit model for a product in a geography, based on the observed accuracy on the training and testing data set. The forecasts are provided with an upper and lower confidence band to take into account "best-case" and "worst-case" scenarios.