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pharmaceutical industry

How is Big Data Analytics Contributing to the Changing Dynamics of the Pharmaceutical Industry?

The use of big data is no longer limited to transforming customer-facing functions such as sales and marketing alone. In the pharmaceutical industry, big data analytics is helping companies to deal with declining success rates and stagnant pipelines. Big data analytics is creating immense opportunities for companies in the pharmaceutical industry to deal with complex business environments amidst the explosion of data sets. The effective utilization of these datasets can help pharmaceutical companies in drug development. Also, big data analytics has enabled companies to improve clinical trials, manage risks efficiently, and improve patient safety.

Our analytics solutions help pharmaceutical companies in medical cost management and drug development. Request a FREE proposal now to gain better insights into our portfolio of analytics solutions.

How is big data analytics revolutionizing the pharmaceutical industry?

Improving sales and marketing

Until recently sales and marketing were grey areas in the pharmaceutical industry. But by leveraging big data analytics, pharmaceutical companies can easily focus on specific geographical areas to promote their medications. Consequently, pharmaceutical companies can create targeted marketing campaigns, thereby saving both on time and effort. Therefore, the role of big data analytics has become even more critical in devising marketing strategies and sales plans.

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Enhancing the efficiency of clinical trials

Clinical trials are an integral part of the pharma industry. The patients undergoing these trials must meet some prerequisites. Big data analytics solutions help companies merge the databases from multiple sources, to filter out patients who do not meet the basic requirements. Also, these solutions help researchers monitor the patients on a real-time basis and predict the side-effects of drugs.

Helping in early detection of diseases

Predictive analytics is helping companies in the pharmaceutical industry in the early detection of drug toxicity as well as improving the chances of patient survival. The algorithms used by predictive analytics helps in gaining detailed insights into patient data and deliver personalized care to the patient.

Our pharmaceutical industry experts help companies to manage their supply chains through specialized algorithms, tools and analytics models. Get in touch with them right away.

Providing real-time feedback

Today leveraging big data analytics solutions has become imperative for the pharmaceutical industry to reach out to their end-users in a better manner. Digital apps can help companies build relations with the target audience. The data collected on these apps are linked to various verticals of the pharmaceutical and healthcare industry which provides primary data on patient compliance and instant feedback on the health of patients.

Allowing doctor-pharma collaboration

One way in which big data analytics is making improvements in the pharmaceutical industry is by predicting the best treatments for individual patients. It can help in looking through data faster than humans and find the interventions likely to cause the most significant advantages for ill patients and their caregivers. With help from big data analytics, pharmaceutical companies can reach out to physicians treating patients that fit appropriate criteria and advise on how a certain medication could and should fit within a person’s treatment plan. Also, some physicians collect real-time data about whether treatments have intended effects, especially when their patients use Internet of Things (IoT) enabled wearables.

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Is Customer Analytics the New Kingpin for Banking Services Companies?

For modern banking services providers, understanding the customers is the foundation for a sustainable competitive advantage. The internal and external data sources available to banking services companies can be great sources for guiding product development, customer communication, innovation, and growth. This data can be further meticulously analyzed using advanced capabilities such as customer analytics through which banking services companies can get to know their customer at a more granular level. Furthermore, it can help in effective customer segmentation that reveals specific intelligence that could otherwise be obscured by the sheer volume of data. These insights aid banking services companies identify messaging strategies for marketing and customer service strategies and also gain a better understanding of the customer lifecycle and predict customer behavior.

Why is customer analytics important in banking services?

It is high time for banking services companies to up their game in customer analytics. Here’s why:

Analytics is the new normal

 As a result of low-interest rates, moderate fee revenue, onerous regulation, and a less than robust economy, the banking services providers are expected to remain revenue challenged for the foreseeable future. So, it will be more important than ever for banking services providers and credit unions to focus on all possible strategies that would help them reduce costs and increase revenues. Some of these strategies that can be achieved by customer analytics include:

  • Better management (and measurement) of sales leads across channels
  • Inclusion of custom customer incentives/rewards to influence behavior
  • Improved targeting of customer segments
  • Moving from a product focus to a customer focus 

Achieve customer centricity

Customer delivery and communication channels are expanding. This means that more customers interacting with their financial providers and banking services companies are using online and mobile channels, making it easier to gain insights into real-time sales and services. Analytics can respond to this rapid migration to digital channels by:

  • Integrating sales and service tools within a new digital environment
  • Improving branch efficiency and effectiveness
  • Helping to drive high value, high touch traffic back to branches

Technological changes

Customer analytics is no longer a domain that can be used and accessed solely by highly skilled specialists. Today, these solutions can be easily accessed and used by marketers and other business users to answer complex inquiries. Improvements include:

  • Increased number of specialized vendor solutions and expanded talent
  • Collapsing of product silos and ability to process increased data sources
  • Cloud-based solutions

Establishing analytics as a true business discipline can help banking services prContact USoviders to grasp the enormous potential. Get in touch with us to know how we can help banking sector clients in establishing a customer analytics program to suit their organizational requirements.

How can customer analytics help banking services?

We at Quantzig have identified six levers that make customer analytics a core component for banking services companies to consider:

Customer Insights

Most financial marketers are highly interested in the ability to gain a better insight on current customers. Demographics and current product ownership form the foundation of customer insight. However, behavioral and attitudinal insights are gaining in importance as channel selection and product use have become more differentiated. Take the instance of sentiment analysis and social media analysis that are helping companies analyze in-depth about their customer emotions on social platforms. Furthermore, scoring models such as FICO is especially useful for banking services companies to analyze consumers’ credit history, loan or credit applications, and other data to assess whether the consumer are likely to meet their payment obligations on time in the future.

Business strategy

Customer analytics proves to be highly useful in banking services companies for product and channel development as well as economic forecasting, business improvements, risk analysis, and financial modeling.

Managing customer experience

Using customer analytics for customer experience management (CEM) helps banking services providers in delivering personalized, contextual interactions that will assist customers with their daily financial needs. Moreover, if done correctly, customer analytics enables the real-time delivery of product or service offerings at the right time, thereby ensuring a better customer experience.

Risk management

One of the more common uses of ‘big data’ today especially for banking services companies is in the area of risk and fraud management. The applications of data mining have expanded well beyond providing internal purchase and balanced insights. It now even includes transaction patterns and social media interactions that can provide a leading indicator of potential losses or fraud. The integration of structured and unstructured data in banking services can also be leveraged for traditional risk management including pricing decisions.


Another traditional use of customer analytics in financial services is the ability to increase the effectiveness and efficiency of sales and marketing. The ability to derive insights on the likelihood of purchase based on the available information on individual customers has ushered in a seismic shift in marketing from product centricity to customer centricity. Banking services companies and credit unions are now able to make unique, timely, and relevant offers based on available customer insight rather than offering products and services based on what the financial institution would like to sell. This allows banking services providers and financial marketers to significantly improve the efficiency of marketing spending and the close rate of sales leads.

To learn more about how Data analytics solutions work in banking sector companies, request a proposal.

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Implementing customer analytics for banking services

The future is already here. The only drawback is that it is not evenly distributed. Banks services and companies in every other industry are already deploying advanced analytics to move their businesses forward. Quantzig has identified that almost every top bank lists advanced analytics among its top five priorities. Most plan to invest further in these techniques. A few banking services companies are already seeing the rewards. By establishing data lakes and centers of excellence and using machine-learning techniques these leaders have already built substantial foundations for their business.

 How do you know what analytics capabilities to invest in for your business? All you need is an analytics expert that can guide you on leveraging the available data by avoiding pitfalls in banking services and accessing the broad set of opportunities. At Quantzig, we understand these needs of our clients and are committed to helping them bolster their analytics capabilities. Request a demo to know more about our analytics solutions.



Role of Advanced Analytics in Reducing Health Care Costs

There are several questions asked by healthcare professionals like – Are there enough measures available that must be taken in case of flu? Or are the patients operated yesterday likely to catch an infection? How can recruiting staffs and providing facilities be done in a cost-effectiveContact US manner? These questions can be answered accurately using advanced analytics, which, in turn, can help in reducing health care costs. As the number of patients keeps increasing along with the associated costs, there is a dire need for adopting advanced analytics in healthcare. Advanced analytics has become a tool in reducing health care costs for many healthcare organizations. It can help in reducing health care costs through various segments, ranging from stock management to patient care to staff deployment. But before delving into the correlation between advanced analytics and health care, let’s first understand what is advanced analytics.

What is advanced analytics?

There is a simple difference between analytics and advanced analytics. Traditional analytics is used to get insights on the current happenings; whereas, advanced analytics helps understand the future to forecast upcoming behaviors and trends. This tool can be categorized into data mining and big data. Advanced analytics uses various mathematical techniques and statistical modeling techniques to analyze current and past data and predict future scenarios.

How can advanced analytics reduce healthRequest Proposal care costs?

There are several ways in which advanced analytics can aid in reducing health care costs. Predicting demands of operating rooms, reducing the rate of readmissions, adding intelligence to pharmaceuticals, and optimizing staffs are some ways in which advanced analytics can help reduce costs.

#1 Predicting demands of operating rooms

Operating rooms are quite expensive to maintain. So, every hospital tries to optimize the operating room without compromising on patients’ health. This goal can be accomplished by recognizing the role of advanced analytics in better understanding the relationship between the operating rooms that can lead to mismanagement of effective scheduling. Thus, advanced analytics can help in streamlining the operating room schedule and reduce health care costs. 

#2 Reducing rate of readmissions

Unnecessary readmissions are very frequent in the U.S and it leads to confusion of discharged patients who fail to understand how to take care of their health or take precautions after they get back to their home. Due to this, an unnecessary burden of cost is also created. This is where advanced analytics comes into the picture.

Advanced analytics helps in reducing health care costs effectively. New advanced analytics algorithms take into account various clinical factors, which helps identify patients who need to spend less than two nights in the hospital. This tool also helps doctors to know when a patient requires observation and, thus, helps in reducing health care costs to a large extent. 

CTA QZ#3 Adding intelligence to pharmaceuticals

This is one of the most powerful features of advanced analytics since it can helps investigate every corner in detail and unveils available opportunities and forthcoming challenges. The historical data available in the clinics and hospitals can help in creating predictive models that can subsequently help the pharma companies to respond to the expected and unexpected changes. Advanced analytics can also be used to uncover the opportunities for internal savings caused by inventory standardization and, thus, help in reducing health care costs.

#4 Optimizing staffs

Advanced analytics can help in trimming costs of labor and predict demand in advance to match resources and staff; thereby, minimizing the last-minute unnecessary expenses. Optimizing the staff skill using advanced analytics can be of great help, especially in reducing health care costs.

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Advanced Analytics – A Wind of Change in the Banking Sector

Data is the fuel that propels the analytics solutions to generate relevant insights and predict future behavior. In that case, the banking industry is not deprived of data, with ATM machines, credit card processing, online transactions, and personal data churning out millions of data points every second. All such data were previously discarded or deemed unuseful. However, with the advancement in analytics capabilities, banks are using such information to uncover deeper insights. With increasing competition, new technologies such as blockchain, and looming economic instability, banks are under pressure to remain competitive and profitable without sacrificing on customer satisfaction. Although effective mining of insights has remained mostly vague in the banking industry, developments in advanced analytics and machine learning will undoubtedly re-shape the banking world. Apart from predictingFree demo customer behavior and improving risk assessment, advanced analytics can be widely used to assist decision maker to grow profits in the banking sector.

Putting a stop to anti-money laundering activities

Governments all across the world are being aggressive in their attempts to crack down on anti-money laundering (AML) activities. They have put forward AML compliance guidelines which should be followed by global and regional banks. Despite huge technology and process investments to achieve such compliance goals, the banking world is still falling short to meet these requirements resulting in million dollar fines. Today, banks all around the globe are using advanced analytics to stop the flow of such illicit funds. To ensure AML compliance, banks are using tools such as Customer Due Dilligence (CDD), Know Your Customer (KYC), social graph analysis, Transaction Monitoring Systems, behavioral modeling, and customer segmentation.

Realizing cross-selling and up-selling opportunities

Advanced analytics can be used to create a detailed profile of the customers and when coupled with transactional and trading analytics, acquisition and retention rates of the clients can be improved along with cross-selling and up-selling opportunities. With the help of predictive analytics, banks can seek out profitable customers, understand their needs, and estimate the results. Prediction models are built taking into consideration decision tree, time series, neural networks, and linear regression. Consequently, the correct product for cross-selling promotion is identified along with its optimal price point.

Digital banking and advanced analytics

Consumer expectations are growing at a rapid pace as they look for a seamless, high-quality experience across all digital channels. Financial institutions are delivering services through all possible digital mediums embedded with exciting features. It’s a win-win situation for both parties as banks can provide a much better customer experience at a fraction of the current cost. However, complications arise in the digital medium when customers start out in one channel, perform subsequent steps in other channel, and end up completing the transaction in a completely different one. As a result, banks and financial institutions are using advanced analytics to understand the customer and build a proper and consistent journey view to create a seamless multichannel experience.

Exploring growth and profit opportunities

The banking industry is continuously looking out for new growth and investment opportunities. Advanced analytics can help banks identify such opportunities and even recommend new business models. In the future, banks may partner with other industries to reap income from their data repositories. For instance, banks may be able to share customer-analytics capabilities with players in the telecom or retail industry to boost their operational efficiency. In May 2017, BBVA, a Spanish bank, officially announced its intention to launch open banking. The platform allows third parties such as retailers to use customer data to offer tailored products and services. For instance, a retailer could notify a customer when they can obtain a preapproved loan from BBVA which is accessible at the point of sale.

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Beverage Industry Company Devises Pricing Analytics to Compare their Pricing Trends

pricing analytics

LONDON: Quantzig, a global analytics services provider, has recently completed their latest pricing analytics for a renowned beverage industry client. The beverage industry comprises of alcoholic and non-alcoholic segments with a significant share of growth contributed by the APAC region. The customer segments, rising population base of the young generation, and increasing per capita incomes further contributes to the growth of the beverage industry.

“The growing urbanization and the rising disposable income are the major factors that are expected to fuel the growth of the beverage industry. With the help of pricing analytics companies can gain a clear understanding of the internal and external factors affecting the profitability at a macro level.” says an industry expert from Quantzig.

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The pricing analytics solution helped the client to implement profit optimization tools to optimize pricing and promotion strategies. The beverage industry client was also able to gain a customizable pricing solution to achieve better returns on their marketing investments.

Additional Benefits of Pricing Analytics

  • Build robust pricing capabilities to achieve a positive impact on the bottom line
  • Position products properly against the competition and analyze the profitability across niche target segments.
  • To know more, request a free proposal

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A Consultant’s Guide to Sell Analytics to Skeptics

Analytical data greatly affects the business decisions made by companies. Therefore, there are high chances of decision-makers at the top-level hierarchy of a company to be skeptical and cautious while choosing the consultant to assist them in providing analytical services and arrive at a mutual plan of action. So how do you get corporates to turn to you for assistance in decision making? Here are some tips and tricks to sell analytical services to clients:

Mining Gold from DataFree demo

Analyzing a client’s historical transaction data will provide a quantitative estimate of the potential benefits that a client could gain by undertaking a certain activity. The best way to gain the trust of a skeptic is to provide them with information that they were not previously aware of.  The analytical services provided to the client should help them discover unexplored facts about the business and should also add substance to their suspicion regarding improving business processes.

Partnering with Companies

Once a client gains confidence in the analytical services provided to them by a consultant, the chances of them offering more projects are higher. In such cases, the analytical services provider can partner with these companies by providing services at a lower price instead of a benefit-sharing agreement. This helps to create a long-lasting relationship with the clients.

Provide Testimonials

Testimonial stands as an unbiased recommendation of the analytical services provided by a consultant. Providing testimonials and instances of business success of past clients gives potential clients the confidence to entrust their faith in the analytical data that is provided to them.

Clear Cut Why and How to Substantiate Data

Top level managers employ analytical services to assist them in key decision-making processes. Therefore, it is essential to clearly state how and why a particular decision will impact or prove beneficial for the business. Making blank business predictions out of thin air is a big “no” for consulting companies providing analytical services.

Grabbing the attention of potential clients?

As in every industry, there is heavy competition among analytical services providers. So how do you differentiate yourself and effectively grab eyeballs of potential clients?

  • ReferencesA good reference can work wonders especially for a small analytical services provider. From clients who have used our services to industrial experts who are familiar with our work, all of them can help open doors for new assignments
  • ConferencesBeing an active participant at either attending or giving speeches at notable conferences can prove beneficial for a consultant. Networking with many top-level managers at these conferences can generate business for an analytical services provider
  • Websites, publications, and interviewsLeads can be generated with the help of content and other data that are published on the consultant’s website or any popular business publications. Client interviews about their success stories can also generate leads from businesses facing similar issues.


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Top Trends Gaining Prominence in HR Analytics

For ages, HR has always been about people management. The modern HR management era has seen a shift towards the use of data and machines to efficiently manage the workforce. A significant amount of data is available to the managers, which can assist them in identifying, recruiting, and rewarding the best personnel. The managers will no longer have to rely on intuition and rule of thumb to make HR decisions as the metrics can give them a complete overview and guide them to the correct decision. Organizations are always screening the developments in the HR analytics market to keep up with the latest innovations and best practices. Here are the top trends in HR analytics:Free demo

Embracing New Data Sources
Companies are realizing the power of analytics and are looking at new data sources in addition to incorporating all existing data sources to make an accurate analysis of their workforce. For instance, companies are encouraging their employees to engage in wellness programs such as bring your own wellness (BYOW). The BYOW concept relies on employees carrying their own fitness measuring devices to workplace allowing companies to collect data to organize fitness challenges or events such as exercising, yoga, or walking.

Capability Gap in People Analytics
Although a majority of the organizations realize the value of HR analytics, only a handful of them have the expertise to extract value out of the data to improve the HR processes. There have been numerous reports suggesting that only about 10-20% of the organization who strongly feel the importance of HR analytics is actually strong in this area.

Emergence of Dedicated Analytics Positions
Organizations are looking to narrow the existing capability cap in people analytics by hiring dedicated professionals to manage their HR analytics. This trend can be substantiated by a report from Deloitte that states that job postings for the HR analytics role have more than doubled from 2010 to 2015. Another report from BurtchWorks states that the entry-level data science role rose 14% last year with a median base salary of $91,000.

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Everything You Need to Know About Advanced Analytics

Advanced analytics tools are focused on predicting future events and market trends that allow companies to forecast the possible outcomes of their business strategies. The modern data analytics tools have a completely contrasting focus as compared to the traditional analytical tools, which revolve around past Free demodata. Advanced analytics helps organizations improve its business practices and operations with a future-oriented perspective. Every industry, be it manufacturing, healthcare or retail, has placed its bets on the evolution of advanced analytics and its widespread benefits. But what exactly is advanced analytics and how can it be applied in various industries, you ask? We all have a vague idea about predictive analytics, customer analytics, and other related data analytics but fail to understand the multifold advantages it offers to organizations. Read on to know more.

Advanced Analytics in A Nutshell

With big data gaining momentum across industries, organizations are seeking to build their advanced analytics capabilities. Analytics, as defined by Oxford dictionary, is “a systematic computation and analysis of data or statistics,” which the organizations can make use of to improve business decisions. The global market for data analytics services is characterized by the presence of many big players such as Google and IBM as well as several small players who are increasingly investing in capability building and improving the advanced analytics landscape. Several industries such as manufacturing, telecommunications, oil and mining, and telecommunication among others leverage predictive analytics, data mining, market analytics, customer analytics, and big data analytics to drive profitability.

Advanced Analytics – Which Industries Does It Benefit?

Data analytics is set to transform how organizations interact with their audience and improve customer experience. This is a result of evolving market dynamics and the gradual shift from traditional strategies and tactics to an analytics-driven landscape. Wondering how can advanced analytics benefit different organizations? Here’s how.

  • In the manufacturing industry, advanced analytics and market analytics helps organizations to monitor the processes proactively and gain insights to minimize downtime, boost productivity, and schedule regular maintenance activities
  • In the financial services industry, companies can improve customer satisfaction and ensure data security with big data analytics and customer analytics
  • With the help of predictive analytics and big data analytics, the retail industry can devise attractive marketing outreach activities, develop customer retention strategies, and personalize their product offerings


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