Tag: benefits of big data

data and analytics

Weekly Round-up: A Storyboard on the Importance of Data and Analytics for Businesses

LONDON: Quantzig, a leading analytics services provider, has announced the release of their new storyboard on the importance of data and analytics for businesses. Each of these downloadable articles explains how data and analytics solutions can help companies to make smart decisions, improve customer satisfaction, decrease e operational expenditure, reduce risks, and enhance fraud management.

Business leaders across industries are increasingly adopting big data analytics and data visualization techniques to improve their business operations. However, many organizations still seem to think of analytics as a quick fix for their business needs and investing in data and analytics is just the beginning of their journey. But to achieve business goals, it is high time for businesses to leverage data and analytics solutions that can help them boost transparency and enhance their approach towards data-driven decision making.

Quantzig’s data and analytics solutions have helped companies with the right data visualization techniques, capabilities, and frameworks to handle the volume, variety, and velocity of data to make informed business decisions while ensuring information privacy and security. Below, we have summarized some of Quantzig’s free resources and have also highlighted ways in which data and analytics solutions have helped businesses to gain a leading edge in today’s competitive business scenario.

Our data and analytics solutions help companies to make proactive business decisions and pre-emptive planning. Request a free proposal to gain better insights.

#1: How can analytics solutions transform business models? A successful business model is not just about completing a business plan or determining which product or service to pursue. It is about mapping out the strategy to create ongoing value for customers. But you must be wondering where to start. This free resource by Quantzig can be your key to success. It gives a detailed overview of how companies can reshape their business models by leveraging data and analytics solutions. Also, it unveils five secrets that can help companies identify and capitalize on new business opportunities.










Gain a holistic view of your datasets with our customized data and analytics solutions. Request a FREE demo now!

#2: What are the top AI and analytics trends in 2019? Analyzing and optimizing the customer experience is the bedrock of successful digital transformation in 2019. Data and analytics capabilities with minimal manual efforts have become the hallmark of all business intelligence solutions. Artificial intelligence (AI) and machine learning technologies are transforming businesses and organizations have become highly dependent on automated data-analysis capabilities. This free resource by Quantzig uncovers some of the top AI and analytics trends that took off within corporate boardrooms but will continue to proliferate across different layers of business operations in 2019 and beyond.






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#3: What are the key steps to build an analytics-driven organization? Companies across industries agree that the capacity for data and analytics is becoming very crucial to their basic viability. Therefore, they need to be prepared for the future when data and analytics are going to be both important and integrated at all levels of organizational decision-making. It has become imperative for businesses to exploit available data in order to maximize profits. However, when it comes to extracting business value from data, most of the companies fail miserably. Quantzig’s free resource uncovers a few important steps that can help organizations to improve transparency, enhance business efficiency, and boost overall business performance. Download the free resource now to know more.







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Big Data in Banking: Transforming business operations significantly

Companies in the banking sector are working hard today to adopt a data-driven approach to enhance their customer service and expand business operations. But the main challenge lies in the fact that banking companies are disrupted by the immense volume of data assets and the increase in the volume of customers. This is affecting the levels of services offered by banking companies dramatically. This is where big data in banking can play a crucial role in game changer for banking companies.

As the importance of big data in banking continues to grow, companies in the banking and financial services sector have realized that they can use data to track the behavior of customers in real-time. This real-time analysis can enhance the overall profitability and performance of the companies. Consequently, this can boost the growth of companies in the forthcoming cycle.

We, at Quantzig, understand the significant opportunities that companies can unveil by understanding the role of big data in banking. And to help companies excel in the competitive landscape, our team of experts have explained in detail about how big data in banking can act as a catalyst in the process of churning growth. Also, they have highlighted the ways in which big data in banking can guide in simplifying the process of monitoring, improving customer service, and optimizing business operations.

Are you looking for ways to uncover opportunities for cost structure and working capital improvement? Get in touch with our experts now.

Benefits of Big Data in Banking

Benefit #1: Improves customer experience

Customers today have high expectations while they interact with their banks and credit companies. This makes it essential to focus on the needs of the customers and understand their complex buying journey. Big data in banking can help banking companies to gain a 360-degree view of customer journeys. It provides a central data hub combining customer’s interaction with the company, transaction history, his personal data, preferred service etc. These insights provided by big data analytics can help in customer segmentation and thus, serving customers better and building a customer-centric culture in the organization to enhance customer service significantly.

Benefit #2: Optimizes business operations

Big data analytics has the potential to enhance the forecasting power of risk models. This can effectively improve the response time and effectiveness of the system. Also, it provides extensive coverage of the risk and automates the process to increase cost savings. Furthermore, this helps in optimizing business operations effectively.

Benefit #3: Enhances employee engagement

Employee engagement is one of the important aspects of any business operation. Application of big data in banking also helps to analyze, enhance, track and share performance metrics of the bank employees. Furthermore, big data in banking helps in identifying and acknowledging the employees who are performing as well as the employees who are struggling and unhappy.

Our portfolio of solutions has helped clients in risk assessment and understanding financial trends across key growth segments while offering a real-time view of the organization’s performance and factors that drive their revenue. Request a free proposal now to know more about our services.

Benefit #4: Helps in identifying transaction channels

Big data in banking helps banks to understand their customers and their behaviors if they withdraw all the sum available in cash or by debit or credit card. This way the customers who use debit or credit card can be approached with lucrative offers of investments.

Benefit #5: Facilitates cross-selling of products

It is always better to offer a better return on interest to customers to encourage them to spend actively. Big data in banking helps in precise analysis of the financial backgrounds of the customers. This ensures the cross-selling of auxiliary products and engages the customers with more personalized offers.

Benefit #6: Manages and prevents fraud

Leveraging advanced analytics and big data in banking can help banks to understand an individual’s spending pattern which further helps in risk assessment if something suspicious happens. If a customer withdraws all his money from his account via a debit card, this might raise an alarm. Big data in banking can help significantly in assessing risk and preventing fraudulent activities.

Benefit #7: Aids in understanding customer spending patterns

Banking and financial services companies have easy access to the historical data of their customers and their spending patterns. Leveraging big data in banking can help bank employees to apply a variety of filters like macroeconomic conditions to understand the patterns of growth in the salary of the customers. This can be considered as one of the crucial factors for evaluation of mortgage, loan screening, cross-selling of products, and risk assessment.

Want to gain more insights into how our analytics solutions can help your banking business? Request a free demo today!

How Can Big Data in Banking Help Improve ROI?

#1: By embedding big data analytics into decision making

Senior managers at bank acknowledge the power of big data in banking but they often do not know how to leverage it for better decision making. Though such an approach fails to support data-driven decision making this is where leveraging big data analytics can help.

#2: By aligning analytics priorities to strategic activities

Majority of the banks struggle to connect analytics with their business strategy and this is a big drawback. But using big data in banking can help in risk mitigation, innovation of new and better services and serve the customers in a much better way. Furthermore, this can help in improving annual revenues.

#3: By investing in important analytics roles

Today banks also need to expand their analytical vision and banks can do this by expanding their analytics team. Investing in data scientists and machine-learning engineers can make the task much easy. Furthermore, this can also help in solving business problems easily.

Quantzig’s Advantage

Banking and financial services companies globally have been the first ones to adopt new technologies for enhancing their security and operations. We offer big data analytics services to banking companies to channelize their huge volumes of data and generate real-time visibility. Also, we have helped companies to make data-driven decisions faster and smarter through our customized analytics solutions. Our analytics solutions have helped leading banking and financial services companies in ensuring complete safety across all transactions and have reduced their exposure to risks significantly.

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Weekly Round-Up: A Storyboard on the Benefits of Big Data Visualization

LONDON: Quantzig, a leading analytics services provider, has announced the release of their latest storyboard on the benefits of big data visualization and how it can help businesses churn the large chunks of big data and harness the information lying beneath it. 

By utilizing big data visualization tools, companies can anticipate the available data to trace outliers, trends, patterns and interact with it to make informed decisions. The need for big data visualization tools can be inferred from the fact that the global business Intelligence and analytics software market is expected to grow significantly by 2019.

Quantzig’s analytics solutions have helped more than 55 Fortune 500 companies to make data-driven decisions and boost their revenue. Below, we have rounded up some of Quantzig’s recent success stories for this week and have also highlighted ways in which big data visualization have helped companies to speed up the process of comprehending large and complex data.

Leverage Quantzig’s optimized data analytics solutions that are designed to address your analytics requirements, reduce costs, and deliver outstanding performance. Get in touch with us today!

#1: Big data visualization facilitated robust risk management strategies: Making informed decisions, improving competitive position in the market are challenging tasks for businesses. Are you finding it difficult too? Not anymore. Big data visualization holds the solution to this. By utilizing big data visualization tools companies can manage storage and integration of big data. Furthermore, this can offer actionable insights into competitors’ strategy and help in devising robust risk management strategies.

Quantzig’s Big Data Analytics Helps A Pharmaceutical Industry Client Devise Robust Risk Management Strategies

#2: How will virtual reality transform big data visualization?  Although there are layers of technological capabilities that companies have been using to seek meaningful outcomes from the available data, the use of virtual reality in transforming big data visualization is a relatively new concept. The large amounts of data generated by organizations can be understood only through a series of data analytics steps, and effective data visualization plays a vital role in enhancing this strategy.

How Will Virtual Reality Transform Big Data Visualization?

#3: Big data visualization improved customer engagements significantly: Are you wondering how to address customer challenges and demands? Data visualization of heterogeneous data can help as it helped one of Quantzig’s clients who was facing the same issue. The client approached Quantzig to leverage its expertise in providing big data visualization solution. Quantzig’s visual analytics solution offered unparalleled visibility into heterogeneous data and enhanced customer engagement by innovating their products and analyzing their journey.

Big Data Analytics Helps a Leading Gaming Industry Client to Improve Customer Engagements

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#4: Big data visualization boosted operational efficiency and on-time delivery: Analyzing real-time information in every step of the production process is not an easy task for businesses. Don’t you agree? This is where big data visualization comes to the rescue. By using big data visualization tools companies can gather actionable insights from various sources, which include social media, business transactions, and information from machine-to-machine or sensor data. Additionally, it can help in aligning business strategies and objectives and identifying industry trends and consumer buying patterns.

#5: Big data visualization enhanced product launch planning and decision making: Creating real-time data repository and reporting system is an essential component for any business for data-driven decision making. This is where big data visualization comes into the picture. It has the potential to assist in analyzing various data sources and setting up data mapping and normalization methodologies which results in better decision making and effective business planning.

Global pharma company improves product launch planning through real-time big data analytics reporting

#6: Big data visualization and master data management reduced the cost of ownership and skyrocketed profit margins: This is one of the most significant success stories of Quantzig, where the client managed to gain strategic insights into the entire manufacturing operations through real-time cost analysis dashboard. This helped them in reducing the cost of ownership and improving profit margins by 10%. Moreover, visual analytics also helped the company to seek instant feedback and pro-actively solve problems before they arise.

Global pharma company improves product launch planning through real-time big data analytics reporting

With the help of Quantzig’s predictive analytics solutions, a lot of businesses are taking improved decisions for better and profitable orders. Are you interested in our data analytics solutions? Request a FREE proposal now!

#7: Realizing savings of $12 million in 12 months with big data visualization: Do you really think consolidating large volume of data and obtaining real-time insights is a humongous task? If yes, then you must go through our latest success story where Quantzig’s big data visualization tools and predictive analytics solution helped the client to save $12 million in 12 months. With big data visualization tools, it becomes easy to gain meaningful insights for process automation and optimization. Furthermore, this helps in enhancing process coordination, determining operation requirements, planning procurement, production operations, and labor utilization which results in significant savings.

Big data analytics saves USD 12 million for industrial equipment manufacturer

#8: Big data visualization revamped decision making by predicting future network scenarios: Are your data analytics models hindering informed decision making? If yes, then you must be going wrong somewhere in assessing a plethora of data. This is clearly evident in Quantzig’s latest success story where the client was dealing with the same issue. But by utilizing big data visualization tools and predictive analytics solutions, the client was able to realize a great improvement in its decision-making process. Furthermore, these solutions paved the way for quick verification of the results of the analysis with different input parameters and make accurate predictions.

Big Data Analytics Reduces Transport Network Congestion

#9: How to create a synergy between big data visualization and human intuition? The rise in machine learning and computational power has driven the growth of big data visualization. As a result, the trend of adopting big data visualization among organizations for decision making is on the rise. However, still, many companies rely on human intuition and experience for better and effective decision making. But businesses need to realize that combining the power of big data with human intuition can unlock immense possibilities.

Creating a Synergy Between Big Data Analytics and Human Intuition

#10: Big data visualization transformed the business ecosystem: Business forecast might sound complex, but you need not worry if you have proper big data visualization tools in place. A leading financial services firm was dealing with similar predicament but experienced a significant change in their business outcome by leveraging Quantzig’s data visualization solutions. These solutions helped them to discern patterns in the extracted datasets. This enhanced transparency of the risk management process. Additionally, it helped in analyzing assets and a better understanding of idiosyncratic risk factors.

Data Visualization Best Practices | A Success Story on How it Turned Out to be a Wise Investment for a Financial Services Firm


How Advanced Analytics is Changing the Business Landscape in 2019?

What is Advanced Analytics?

Advanced analytics describes data analysis that goes steps ahead than simple mathematical calculations such as sums and averages or sorting and filtering. Advanced analytics leverages statistical and mathematical formulas and algorithms to recognize patterns, generate new information, and to forecast outcomes and their respective probabilities. It can be applied to several cases, ranging from the prevention of contract termination, classic customer value and success forecasts, or sales, price, and demand forecasts to new tasks such as the machine failure prediction, monitoring of social media and evaluation, and predictive policing. Advanced analytics enables both innovation and optimization. It has the potential to improve existing processes.

Are you finding it difficult to make informed business decisions, while ensuring information privacy and security? Get in touch with our analysts who can complement you with a shared need to discover and build those capabilities and drive continuous market excellence.


What are the Different Advanced Analytics Techniques?

In advanced analytics, “advanced” refers to quantitative methods such as algorithms, statistics, and stochastic processes. All the advanced analytics techniques are not predictive, but they are future-oriented as the core idea of the techniques is to support data-driven decisions in the future. Furthermore, the advanced analytics techniques can be categorized into three functions:

Descriptive analysis

The descriptive analysis focuses on understanding an underlying process or phenomenon. The descriptive analysis has the potential to answer questions such as, “Which products do consumers usually purchase together?” or “What are the typical characteristics of customers who tend to churn?”

Predictive analysis

The predictive analysis aims at studying hidden relationships between factors and outcomes. The data derived is then used to forecast or estimate an unknown value. For example, a predictive model will allow us to estimate how much revenue will be lost if temperatures drop 10 degrees or forecast which customers are going to churn.

Simulation and optimization

Simulation copies the operation and characteristics of a process and condenses the outcome whereas, optimization prioritizes the options of decision-based on a key performance index.

Are you struggling to manage the high volumes of data generated by high-tech sensors? Leveraging advanced analytics solutions may help. It has the potential to generate predictive insights that facilitate proactive business decisions and pre-emptive planning. Request a free proposal here to check out our portfolio of advanced analytics solutions.


Why Advanced Analytics Is Becoming So Important for Businesses? 

In this era of digitalization  new technologies and analytic methods are improving business operations and are helping businesses to maintain a competitive advantage in the following ways:

  • New big data technologies enable processing and analysis of large amounts of data and cost-effective storage
  • Modern and intuitive user interfaces allow user groups to derive informed insights and make better decisions
  • Advanced analytics software facilitates better analysis of collected data, relationships, and future events.

Today, modern technologies like predictive analytics accelerate and improve decisions and processes along the value chain. Therefore, you should carefully evaluate how advanced analytics can be used within your company in order to excel in the competitive landscape.

Key Benefits of Advanced Analytics

Detailed analysis helps in personalized marketing

Advanced analytics helps identify patterns from less aggregated datasets, such as at the store level or at an individual customer level. For example, advanced analytics can help businesses to capture the characteristics of every individual customer and offer him or her customized products by analyzing the pool of data. This eliminates the method of simply concluding the overall market demand of a customer segment and then offering the full audience’s favorite product. By leveraging big data analytics solutions businesses can significantly improve marketing effectiveness as well as customer satisfaction.

Better performing advanced analytics techniques improve accuracy

Most of the advanced data analytics techniques used today are more robust, faster, and accurate. For example, artificial neural networks greatly enhanced pattern recognition performance by generating a collection of functions that transform the input variables to approximate the required outcome. Predictive analytics and deep learning algorithms are applied to create more powerful hierarchies. Additionally, big data solutions allow machines to learn the complex business world in a much more flexible way. As a result, the prediction from analytical models is becoming more accurate and reliable.

Identify the level of risk in the implementation of the decision

By leveraging predictive analytics solutions, businesses can gain a confidence level for their prediction and select models based on performance measures. Furthermore, it helps companies by conveying the level of risk involved in the recommended action. Additionally, advanced analytics benefits businesses by conveying the risk level of implementing the recommended action. There are circumstances when there is a high cost for acting on false-positive or false-negative predictions. In such cases, companies can adjust the parameters of the predictive analytics model to choose not to act on low confidence predictions or avoid high-cost false prediction.

One of our recent case studies highlighted how advanced analytics helped a consumer products manufacturer to develop an aggressive growth-centric data strategy. Read the full story here.

Final Thoughts

Advanced analytics can help organizations to deal with confusions and challenges by delivering future-oriented and fact-based insights. Furthermore, it strategically extends traditional analytics solutions from being descriptive to predictive, and ideally prescriptive.

We understand the challenges companies face in managing large volumes of data and set up analytical frameworks to derive real-time insights that facilitate more informed decisions. Our advanced analytics solutions provide best-in-class frameworks for multi-dimensional data aggregation and use visualization-based data discovery tools for insight generation. Request a free demo below for more insights.




4 Huge Big Data Use Cases for Modern Businesses to Zoom Ahead

Organizations now have access to more data than ever before, but unless companies decipher how to bring this data to work it proves to be absolutely useless. Understanding the benefits of big data is not as simple as putting all the data in one place. Their real value can be harnessed only through specific big data use cases and applications. Those applications tend to vary widely across departments and industries. While there are several technical challenges associated with integrating and managing all of this data, organizations should first take the time to identify and crystallize the right benefits of big data for their business. Let’s delve into some of the key big data use cases for modern businesses that we have identified with several successful customer deployments:

Top big data use cases for business

E-commerce personalization

With hundreds and thousands of search queries and customer databases, it often becomes difficult for e commerce companies to optimize their customer’s shopping experience. This daunting tasks of collecting, processing, and analyzing shoppers’ behavior and their transaction data open up a plethora of opportunities for big data in e-commerce. Using a powerful search and analytics platform e-commerce companies can clean and enrich product data for a better search experience on both desktops and mobile devices. They can also use predictive analytics and machine learning to predict user preferences through log data, and then personalize products in a most-likely-to-buy order. This would ensure maximum conversion. Quantzig’ s customer analytics solutions provide customer insights to drive sales and improve revenues through acquisition, growth, and retention.  

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3 Ways Advanced Data Analytics Can Drive the Next Wave of Growth for Transportation and Logistics Companies

Today, transportation and logistics (T&L) companies have embraced advanced data analytics in their operations since it allows them to run sophisticated networks globally. But unfortunately, the investments made in advanced data analytics is not satisfactory. Now, it is time for that to change if the companies in the T&L sector really want their sales performance to grow. The commercial analytics capabilities of this sector lag average performance, which is primarily because of the reason that sales forces in this sector rely heavily on outdated processes and lack proper insights into preferences of their customers and growth opportunities. Here rises the need for big data analytics for T&L companies. They already have enough data and can utilize big data analytics extensively to earn desired outcomes. With years of experience in offering data analytics solutions to businesses, we have noted that companies in this sector who embrace advanced data analytics can generate an additional 2-5% percent return on their investment. In this article, we have summed up three things that T&L companies need to do to realize the true potential of advanced data analytics:


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Analyzing Benefits of Big Data: The Real Application of Big Data in Transportation

Today, the term ‘big data’ is being used to convey a variety of concepts like next-generation data management capabilities, huge quantities of data, real-time data insights, social media analytics, and lot more. Whatever be the industry, organizations have started to analyze and explore how to examine a vast array of information in innovative and new ways to derive the best possible business outcomes. Organizations across various transportation and travel segments like airports, airlines, freight logistics, railways, hospitality, and others are enjoying the benefits of big data in managing a large amount of data that they handle. In today’s interconnected and instrumentGet More Infoed world, every industry including the transportation segment captures an unprecedented amount of data. So, the benefits of big data and analytics help the transportation companies to accurately optimize and model capacity, demand, pricing, revenue, customer sentiments, cost and lot more. With the help of the analytics experts at Quantzig, we have listed few of the benefits of big data in transportation:

Benefits of Big Data in Transportation


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Top 4 Advantages of Big Data in The Banking Industry

The banking industry has witnessed the evolution of operations and delivery of services over the last few years. But it is a surprising fact that most banks have not been ablGet More Infoe to utilize the information in their own databases properly. This is gradually changing as the banking industry gears up to process the huge volume of data that is collected and created. The banking industry experts, in fact, say that there will be an immense increase in the volume of data before 2020. Therefore, big data in banking is a huge step towards the growth of the banking industry and will contribute immensely in its prosperity. Let’s take a look at the advantages of big data in the banking industry.

Big Data in Banking

#1. Prevention and Detection of Fraud

Big data in banking can help deal with one of the biggest challenges faced by banks today – frauds. Banks and financial organizations use analytics to find the difference between fraudulent interactions and legitimate business transactions. With the help of analytics and machine learning, banks can easily define normal activity on the basis of customer history and differentiate it from unusual behavior, indicating fraud. The use of big data in banking systems will help suggest immediate actions like blocking any irregular transactions. This stops fraud before it occurs and enhances profitability.

Continue reading to know more about the benefits of big data in banking or request free proposal

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Pharmaceutical Sector market analysis – How big data analytics solutions helped a pharmaceutical firm to evaluate effectiveness of new drugs

QZ PR templateLONDON: Quantzig, a global analytics services provider, has recently completed their latest big data analytics solution for a pharmaceutical firm. The global pharmaceutical industry incorporates businesses involved in the research, development, manufacturing, distribution, and marketing of medicines. The medicines manufactured by these pharmaceutical industries are essential for the smooth functioning of the medical sector. the drugs include OTC, prescription-based, and biologically-derived drugs. Additionally, the industry is witnessing a high demand for innovation for new drugs.

“The big data analytics solution offered by Quantzig assisted the pharmaceutical client to improve their ability to measure and monitor whether medications are being used as prescribed or not.” says an industry expert from Quantzig.

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The big data analytics solution focused on analyzing the number of drugs manufactured against supply data and market demand data, and the effect of drug counterfeiting on their overall business. Additionally, the solution also helped the client to understand the effectiveness of drugs by measuring social media sentiment.

Additional Benefits of the Marketing Mix Optimization Solution

  • Evaluate the efficacy and effectiveness of new drugs
  • Devise robust risk management strategies to help make informed business decisions
  • Decrease inventory write-downs and improve margins as volume increases.
  • To know more, request a free proposal


To know more about how our big data analytics solution helped the pharmaceutical client

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Telecom Company market analysis – How customer lifetime value study helped a telecom company to increase retention levels

QZ PR templateLONDON: Quantzig, a global analytics services provider, has recently completed their latest customer lifetime value prediction for a telecom industry client. The global telecom industry consists of giant players that make communication possible on a global scale, through either the phone or the Internet. Internet service providers, cable companies, wireless operators, and satellite companies are some of the most significant companies in this sector. The telecom industry is mainly driven by technological innovations and developments, which help to offer a wide range of communication services at low-cost margins.

“The customer lifetime value calculation offered by Quantzig assisted the telecom company to identify the necessary marketing efforts to reduce churn rates and ensure the right amount of marketing investments toward profitable customers. They were also able to profile the potential customers and develop a marketing strategy that maximized retention, net profit, and minimized acquisition and re-marketing costs.” says an industry expert from Quantzig.

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The customer lifetime value prediction study helped the client optimize interactions and conversations to drive customer referrals, repeat purchases, and reduce support costs. These solutions also offered real-time and actionable insights into customers based on future cash flows, which helped the client proficiently differentiate customers in terms of the profitability.

Additional Benefits of the Customer Lifetime Value Study

  • Achieve a higher retention rate and build long-term relationships with the customers
  • Drive repeat purchases, customer referrals, and reduce support costs
  • Develop a marketing strategy to maximize retention and net profit
  • To know more, request a free proposal


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