C5i > 实例探究 > Advanced recursive chain forecasting model evaluates sales impact and helps form new strategy and future roadmap

Advanced recursive chain forecasting model evaluates sales impact and helps form new strategy and future roadmap

公司规模

1,000+

地区

America

国家

United States

产品

Transformed product

技术栈

Data Integration
Data Analytics
Recursive Chain Forecasting Model
Bayesian network model

实施规模

Enterprise-wide Deployment

影响指标

Productivity Improvements
Revenue Growth

技术

分析与建模 - 预测分析
分析与建模 - 实时分析

适用功能

商业运营
销售与市场营销

用例

需求计划与预测
补货预测

服务

数据科学服务

关于客户

The customer in this case study is a major technology company operating in the Information Technology industry. The company was facing challenges due to increasing instances of malicious downloads and difficulty in storage and use of their products. In response to these challenges, the company implemented changes around their different sales outlets to overcome competition and adapt to the changing landscape. They replaced a few pre-existing brands with a single, easy-to-carry, less space-occupying product across major U.S. electronic/technology retailers for all states. The company sought to conduct a deep dive study to understand the effect on sales due to these changes and to develop a deep level understanding of various factors influencing their sales.

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挑战

The client, a major technology company, was implementing changes around the different sales outlets to overcome competition and embrace the changing landscape. They replaced a few pre-existing brands with a single easy-to-carry, less space-occupying product across the major U.S. electronic/technology retailers for all the states. This step was taken as the company was facing issues like increasing instances of malicious downloads and difficulty in storage and use. The client wanted to conduct a deep dive study to understand the effect on sales due to these changes. They also wanted to breakdown the effect by different regions and products to develop a deep level understanding of various factors. This analysis will help the company evaluate the new strategy and hence formulate the future roadmap.

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解决方案

Blueocean Market Intelligence built a customized solution to achieve the client's goals. The solution involved sales trend analysis of the product over a period of time, data harmonization for reducing seasonal impact and carrying out an unbiased analysis over a period of time, and a time series model to establish the unit sales volume for the products. The Recursive Chain Forecasting Model and Bayesian network model were used to determine the impact on sales due to the introduction of the transformed product. Techniques such as Granger Causality and Cross Price Elasticity were used for suggesting prescriptive measures for enhancing sales. The solution also involved data integration and cleansing for analysis development across all the states, integration of different sales data, and integration of other data sources like labor data at a zip code and month level.

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运营影响

The analysis helped the client understand the seasonality of the products.
Blueocean Market Intelligence formulated bundling strategies by identifying products whose sales were impacted the most by introducing the new product.
The analysis identified segments that responded well to the introduction of the new product and suggested measures for improving sales.
Recursive chain forecasting and residual analysis determined the new product sales were driven by the old product.

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