Increase Customer Acquisition and Retention with Customer Analytics Solutions
Our tailor-made customer analytics solutions enable you to efficiently comprehend customer behavior, drive loyalty and increase revenue.
Do you want to increase customer acquisition rates for your organization?
Building a loyal customer base is the ultimate goal of every business. But the evolving technological innovations and the rapid paradigm shift have disrupted the global business landscape leading to dynamic shifts in customer behavior. Customer analytics has, therefore, become an integral part of every business agenda. Customer data holds immense value, and a detailed analysis of these data sets using advanced analytics methodologies can reveal incisive insights that can help you build a customer-centric organization.
How Does Quantzig Work?
We’ve helped some of the world’s leading companies gain unparalleled access to smarter insights and analytically use customer data to drive positive business outcomes.
Our Customer Analytics Capabilities
Customer Lifetime Value
Quantzig’s customer journey analytics solutions combine the application of dynamic micro-segmentation and predictive modeling techniques to accurately forecast customers’ lifetime value based on their purchase history, demographics, and other behavioral traits.
Customer Segmentation
Quantzig’s customer analytics solutions enable you to segment customer base into granular, homogeneous groups, analyze patterns, and identify the factors that impact their purchase decisions, thus empowering businesses to make the right decisions to increase MROI and customer satisfaction.
Next-Best Action Analytics
Driven by machine learning and AI-based models, our next best action analytics solutions help track and analyze purchase behavior, social media interactions, and other aspects of the customer journey, enabling the delivery of superior experiences across all customer touchpoints.
Customer Satisfaction
Quantzig’s robust customer behavior analytics solutions ensure you gain in-depth insights into your customers’ sentiments and optimize the drivers that create a seamless customer experience and enhance customer satisfaction.
Net Promotion Index
Our customer analytics solutions enable you to calculate the net promotion index to gain insights into customer experience and gauge marketing effectiveness. net promotion index analysis also enables you to strengthen customer relationships, provide tangible value propositions throughout the customer journey, and deliver an experience that resonates with their customers’ needs and preferences.
Customer Loyalty and churn analysis
Quantzig customer data analytics solutions help you formulate strategies to retain loyal customers and reduce churn. Our solutions also enable you to customize your offerings as per different segments, improve customer relationships, and increase customer loyalty.
FAQs – Customer Analytics
What exactly is customer analytics?
Customer Analytics is a set of processes and technologies that provide organizations with customer insights necessary to contact the right customers, at the right time, with the right messaging. Customer analytics enables organizations to analyze customer data such as customer sentiments, history/identity, web presence, buying patterns, online and offline touchpoints, to understand customers.
Which industries can benefit from customer analytics?
All industries, both B2B and B2C, can make efficient use of customer analytics to understand their customers better and increase loyalty and acquisition. The principal industries making use of customer analytics today are retail and CPG, food and beverage, BFSI, communication and media, automotive, transportation and logistics, healthcare and pharmaceutical, manufacturing.
How can customer analytics benefit a business?
Building a loyal customer base is the ultimate goal of every business. But the evolving technological innovations and the rapid paradigm shift have disrupted the global business landscape leading to dynamic shifts in customer behavior. While these disruptions have severely impacted business growth, forward-looking, agile businesses are capitalizing on these opportunities to drive customer loyalty.
Customer analytics has, therefore, become an integral part of every business agenda. Customer data holds immense value, and a detailed analysis of these data sets using advanced analytics methodologies can reveal incisive insights that can help you build a customer-centric organization.
What is the future of customer analytics?
The future of customer analytics lies in real-time data collection of customer needs and expectations, which will provide insight into customer behaviour, identify previously unimagined market opportunities and answer questions businesses have never dared ask before. Driven by artificial intelligence, machine learning, and cognitive analytics, this new method will enable organizations to adapt to their customers’ actions and sentiments and create manufacturing, marketing, and sales strategies that are holistic, predictive, precise, and clearly tied to business outcomes.
What are some of the common customer analytics features?
Some common key features of customer analytics are:
- Funnel analysis – Creation of key user funnels to preimpt and eliminate bottlenecks and customer experience issues
- Market segmentation – Building of user segments based on common customer characteristics
- Retention analysis – Discovering highly correlated events and creating cohorts to conduct analysis on.
- Collaboration and sharing – Streamline collaboration and sharing between decision-makers with public dashboards, scheduled reports, and more
- KPI tracking – Creating dashboards and visualizing results to enable easy tracking of KPIs and performance
- AB testing – Testing marketing and product changes in real time with the help of simulation
- Data governance – Creating organizational policies for secure and easy access to all data for analysis
- Revenue analysis – Identifying customer actions tied to higher revenues and mapping the impact of these actions
What is the source of customer data and how are these collected and analyzed?
Some common sources of customer data are:
- Website data
- Personal and social media data
- Mobile app data
- Customer service data
- Survey data
- In-store and online sales data
- Marketing automation and web platforms
These datasets can be further divided into – personal, engagement, behavioral, and attitudinal datasets. They are collected with the help of the following tools/mediums – website analytics, social media analytics, contact information storing, tracking pixels, customer service software, customer feedback and surveys, transactional information.
The analysis of this data happens in two phases – quantitative data analysis and qualitative data analysis – with the help of tools and technologies like data mining, clustering regression analysis, prediction analysis, content analysis, and narrative analysis.
What should I do If I need to test if customer analytics solutions work for my organization?
Test out Quantzig’s advanced customer analytics solutions to solve your complex business challenges at no cost with our 4-week complimentary pilot. This offer bears no hidden clauses and serves as a perfect opportunity to explore our value proposition and gauge organizational synergies.
During the 4-week pilot, you will be working with our advanced analytics experts who leverage the latest advanced analytics and visualization tools and techniques, statistical approaches, and platforms—designed and custom-built to suit your needs to deliver solutions with the power to transform your business.
Being one of the world’s fastest-growing analytics solutions provider, we are committed to delivering cutting-edge customer analytics solutions to help clients institutionalize data-driven decision making and tackle complex customer experience management challenges.
Request a free proposal to leverage statistical approaches and robust customer analytics solutions to accelerate your journey from data to decisions.
Our Latest Articles
Use Cases or Big Data Analytics in the Media & Entertainment Industry
What You'll Find in this Case Study: Industry Overview We’ve highlighted these big data use cases in this article: Highlights of the Write-Up– Big Data Challenges in the M&E Industry The Complex Media and Entertainment Industry – Overview Factors that influence...
Use Cases of Big Data Analytics in the Healthcare Industry
Healthcare Industry Overview The healthcare industry has seen a complete overhaul in the recent years due to big data analytics. Given the ubiquity of healthcare data generated by business processes within the healthcare sector, healthcare data analytics and big...
Major Use Cases of Big Data Analytics in Food Industry
Irrespective of the location across the globe, you’ve been a part of the food and beverage industry, often as a consumer. As we’re all aware, the food and beverage industry is divided into multiple sub-sections, ranging from—fine dining to fast food. First, let’s talk...