Customer Loyalty and Churn Analysis
Turn your customers into growth drivers by increasing loyalty, retention, and brand advocacy with data.
Given the high customer acquisition costs across industries, retaining customers is often more cost-effective than acquiring and winning new customers. Hence, most forward-looking, agile businesses aim to convert first-time buyers into long-term profitable customers, making customer loyalty and churn analysis an indispensable part of every organization’s customer retention efforts.
Today improving customer loyalty and reducing churn through an intelligent segmentation of your customer base is essential to business viability. But to reap maximum benefits from a well-segmented and thoroughly analyzed customer database requires analytical thinking and a data-backed approach. Quantzig’s deep expertise in customer loyalty and churn analysis can help you drive your customer retention efforts by enhancing your ability to mine customer data and leverage insights.
Core Capabilities
Sentiment Analysis
Sentiment analysis helps businesses detect customer sentiment on social media, gauge brand reputation, understand the unique needs of customers. Analyzing sentiments also helps businesses drive customer loyalty and, in turn, reduce churn.
We offer advanced sentiment analysis solutions that leverage machine learning algorithms and natural language processing (NLP) to assign weighted sentiment scores to the entities and analyze datasets in real-time so that you can take appropriate actions and solve critical business issues in real-time.



Market Basket Analysis
An unpredictable economy and unrelenting marginal pressures require businesses to think more proactively and identify factors that drive consumer buying preferences and behaviors.
Our unique approach to customer loyalty and churn analysis combines in-depth domain expertise, predictive analytics, and data mining to help clients gain actionable insights and make smarter decisions that future-proof their businesses.
Churn Modeling
Measuring and analyzing the underlying reasons for churn is of utmost importance for businesses so that they can devise ways to reduce it.
To address this requirement, we’ve developed robust customer loyalty and churn analysis solutions that can help effectively manage risks associated with churn while improving business value.



Customer Retention Strategy
In the current business scenario, it’s worth going the extra mile to retain profitable customers by improving service efficiencies and customer satisfaction rates.
We’ve curated a portfolio of advanced customer loyalty and churn analysis solutions that focus on increasing wallet share by identifying and retaining profitable customer groups.
Agile, forward-looking businesses leverage data-driven insights to attract and retain customers. With Quantzig’s unique data-backed approach to customer loyalty and churn analysis, businesses can now measure customer churn indicators and prevent at-risk customers from churning before it’s too late.
Drive your customer retention efforts by enhancing your ability to mine customer data and leverage insights.
Request a free proposal to understand the drivers of customer success and improve loyalty by delivering the outcomes your customers desire.
Our Latest Articles
Supply Chain Analytics and its Importance for Businesses
Supply chains generate massive amounts of structured and unstructured data, which, when used efficiently, can enable organizations to gain intelligent, actionable insights. Traditional supply chains, that do not make use of data analytics are siloed and slow-moving,...
What are the Undeniable Pricing Analytics Benefits for Business?
Benefits of Pricing Analytics S NoPricing Analytics Benefits1.Identifying Pricing Opportunities2.Planning Pricing Strategies and Promotions3.Improves Operational Efficiency4.Getting Stakeholders to Buy into the Pricing Strategies5.Optimize Pricing The Need for Pricing...
Four Metrics in the Telecom Industry to Make Smart Decisions
What you can expect from the Telecom Analytics Metrics Article IntroductionTelecom Analytics Metrics Highlights of the Telecom Analytics Metrics Article S NoTelecom Analytics Metrics1.Average Revenue Per User (ARPU)2.Minutes of Usage (MOU)3.Churn Rate4.Subscriber...