Leveraging Sentiment Analysis to Enhance Business Performance
Business & Growth Strategy
Objective
Sentiment Analysis has become a cornerstone for businesses looking to gauge customer opinions. Traditional sentiment analysis focuses on overall polarity (positive, negative or neutral). Aspect-Based Sentiment Analysis (ABSA), however; provides a more granular understanding by identifying sentiments associated with specific aspects or attributes within text. This blog dives into ABSA techniques, challenges, tools and practical examples, giving you everything you need to leverage it effectively.
Market Attribution Modelling for an FMCG Client
Business & Growth Strategy, Data Science & Predictive Analytics
Objective
One of our biggest FMCG clients has hundreds of brands and each brand has thousands of products. They started their eCommerce business in the later half of the last decade and by 2020, they were spending c.$100M on digital marketing across various platforms like Amazon, Walmart, Kroger, etc. The business challenge was that while the brands and business verticals knew the Sales for each brand and product, they did not know how much of these sales were as a result of digital marketing on these platforms, i.e. they did not know the “market attributed sales” (in other words, sales due to digital marketing alone) and market attributed ROAS for the products and the brands.
The goal was to create a forecasting model to optimise ROAS so that marketing spend could be optimised at a product and brand level. The initial focus was to develop the models for Amazon and Kroger based on the marketing spend for them.
Reducing Telco Customer Churn: Insights, Predictions & Actionable Strategies
Business & Growth Strategy, Cloud Technologies, Data Science & Predictive Analytics
Introduction
In today’s competitive telecommunications industry, customer churn is a persistent challenge. With the rise of alternative service providers and increasingly savvy customers, businesses must prioritise retention to maintain growth. Predicting and reducing churn not only helps to safeguard revenue but also allows companies to improve customer experience by addressing the root causes of dissatisfaction.
In this case study, we explore how advanced machine learning techniques, particularly churn prediction models, can help telecommunications (Telco) companies reduce churn. We’ll walk through the data analysis, modelling and insights, demonstrating how these insights can lead to actionable strategies for improving customer retention.