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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.

Quantzig offers analytics solutions specific to the pharmaceutical industry that provide evidence-based insights to help drive better decisions and results in all commercial operations. Request a FREE demo below to know more.

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.

Wonder how big data analytics solutions can help you improve ROI significantly? Request for more information below.

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Role of Web Scraping and Analytics in Transforming the Ecommerce Sector | Quantzig

Data plays a crucial role in driving business outcomes, and nowhere is this truer than in the e-commerce sector. With the ongoing fluctuation in market dynamics, diversifying customer base, ever-evolving business models, and the growing complexities of business functions, your ‘web data’ is the key to understanding the perceptions and demands of end-users while ensuring your business remains profitable in this fast-changing landscape. In this guide, our advanced analytics experts explain the importance of web scraping and analytics from four perspectives namely- customer preferences, content consumption patterns, data monetization approaches, and customer retention.

How Analytics and Web Scraping Can Help Etailers

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How Can Analytics Solutions Empower Businesses in 2019?

With the changing business environment, data analytics solutions have become the key to outshine all competition. Leveraging analytics solutions effectively is the major difference between companies that fail and succeed in the competitive business landscape of today. Companies that are highly successful in the B2B marketplace are using analytics solutions to devise effective and highly specific campaigns to reach out to targeted prospects with a curated message. Data analytics solutions help business organizations to make data-driven decisions and pave the way for businesses to identify inefficient processes, spot new opportunities, and cut costs significantly. With the help of algorithms, data analytics solutions assist companies to extract actionable insights from the data and make data visualization simpler. There are various analytics solutions such as web crawling, text mining, predictive analytics, and market mix modeling that act as a silver bullet for companies operating in various sectors.

Here is a brief summary of common business challenges that can be mitigated with the aid of analytics solutions:

Challenges e-commerce businesses face and how web crawling and text mining solutions can help?

Competitor research, dynamic pricing, new product research, assessing the required data, and managing proxies to reliably scrape the web without disruption are some of the major challenges that e-commerce businesses face. Therefore, it becomes important for such businesses to consider the reliability of their data feed. Web crawling and text mining solutions can help e-commerce businesses to do so. Web crawling and data mining solutions can also assist marketers to fine-tune product portfolios, optimize price points, and customize it down to the individual level to boost profitability. 

How can analytics in healthcare help companies deal with challenges in the industry?   

Despite its promising growth prospects, companies in the healthcare sector are hard pressed when it comes to finding solutions to several complicated issues such as shooting costs, medicinal and technological advancements, changes in policy and regulations, maintaining efficient operations, and providing the best care. But this is where leveraging analytics in healthcare can help. The use of data analytics solutions in healthcare can help healthcare service providers in minimizing healthcare waste, reducing hospitals readmissions, and providing cost-effective treatments to patients.

How can B2B companies tackle growing business challenges by utilizing market mix modeling?

Today, it has become really difficult for businesses to measure marketing effectiveness. Analyzing the future impact of a change in marketing metrics and optimizing investments to drive profits is a daunting task for B2B companies. Also, the influence of operational factors and several external factors can lead to an increase in the market spend for B2B businesses. This is where market mix modeling can be taken into account to set the correct foundation for their marketing strategies and branding solutions.

Here is the list of that Quantzig Conducted on the above topics that you can watch for free:

#1: Importance of web crawling and text mining solutions to improve e-commerce business strategy: Customized web crawling and text mining based analytics solutions can help e-commerce businesses to tackle critical challenges created by the recent explosion of data. Web crawling and text mining solutions assist businesses to explore innovative techniques to collect vast volumes of online data and organize it in a structured manner. Furthermore, it helps gain better business insights, improves business planning, and optimizes decision management. Watch out the full webinar here:

#2: How can analytics bring in commercial excellence in the healthcare industry? Healthcare regulations and advancements in medicines have resulted in the restructuring of healthcare provisioning as well as diversification and specialization in life sciences. Organizations in healthcare need to develop commercial strategies that include all stakeholders. Leveraging analytics in healthcare can help organizations to gain real-world insights and maintain a single source of accurate information of customers for segmentation, targeting, and call planning. Check out the full webinar here:

#3: Is market mix modeling a cornerstone for B2B companies?  Marketers across industries are hard pressed to prove the value of their marketing investment decisions based on the performance of their business and identify opportunities for optimizing investment. Market mix modeling helps companies to develop a multi-channel strategy to execute and measure campaigns across digital channels and boost conversions. Watch out the full webinar to know more:

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cloud analytics

Cloud Analytics: A Guide to Enterprise Data Consolidation

What is Cloud Analytics?

Cloud analytics is an approach that involves the application of advanced algorithms to identify data patterns and extract valuable insights. Today companies are increasingly relying on data analysis to improve business operations and gain an edge over competitors. By leveraging cloud analytics approaches, companies can improve their decisions significantly and enhance business performance. Cloud analytics provides an indispensable platform that can help in scaling analytics capabilities and reduce the burden of management and implementation.

Cloud analytics can help organizations to improve their data governance capabilities by consolidating information from all communication channels and resources. Want to know how? Get in touch with our experts right away.

Components of Cloud Analytics

Data sources

Data sources are the original sources of data that comprise ERPs, social media data, CRM, and website usage data. Twitter sentiment data is an example of a cloud-based data source.

Data models

Cloud-based data models explain the relationship between various data points. They are created with structured data types.

Analytic models

Analytics-based models are mathematical models that are used to forecast business outcomes and drive change using data-driven and fact-based information.

Cloud analytics solutions can help companies to improve flexibility and serve their customers better by consolidating critical data. Request a FREE proposal to gain better insights.

Types of Cloud Analytics

Public cloud

Public clouds are operated by third-party cloud service providers and within a public cloud, all hardware, software, and other supporting infrastructure is managed by the cloud service providers.

Private cloud

A private cloud is a cloud computing resource that is used exclusively by a single organization. A private cloud is usually located on the company’s on-site datacenter. Also, some companies pay third-party service providers for hosting their private cloud. A private cloud facilitates the maintenance of the services and infrastructure on a private network.

Hybrid cloud

Hybrid clouds comprise both public and private clouds which are connected by technology that allows the sharing of data and applications between them. A hybrid cloud-based platform provides better flexibility and deployment options to the business by allowing data and applications to move between private and public clouds. Furthermore, this helps organizations to optimize existing security, compliance, and infrastructure.

Request a FREE demo below to know how our advanced analytics services can help your business.

Benefits of Cloud Analytics

Performance

Cloud analytics helps businesses to improve performances through fast and efficient computing hardware. This offers several benefits over a single corporate data center, including reduced network latency for applications and greater economies of scale.

A better understanding of the bottom line

Cloud analytics can transform every segment of an organization by giving access to human resources, marketing, and operations to the important financial information they need to execute the visual analysis. This can provide a better understanding of the bottom-line impact of their decisions.

Breaking down departmental silos

For any organization financial data is very important. Therefore, if business users outside the finance department have access to this data, it can help in improving the business functions. Cloud analytics provides the ability to query and analyze data from a single source. Furthermore, cloud analytics solutions help in sharing strategy and discipline across the core business operations.

Want to know more about the benefits of cloud analytics? Request for more information below.

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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.

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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.

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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.

Marketing

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.

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4 Ways Procurement Analytics Can Help Add Real Value to Your Business

In this age of digital intelligence, procurement data is no longer restricted to spend data. Now, data from multiple sources including both internal and external is easily accessible to the procurement team. There is immense opportunity to deploy advanced analytics on this combined data to understand market dynamics, purchasing trends, behaviors of business stakeholder, and team performance. The derived insights can be used to brace future procurement decisions and drive value for the whole organization. Moreover, today procurement managers need to assess their real position on the ‘analytics value chain’, to get a true picture of where they actually stand. Once they gain clarity on this, actions can be taken to move ahead based on the level of maturity. The analytics experts at Quantzig have identified four metrics through which procurement analytics can help businesses reduce overall cost base and achieve more for less:

How can procurement analytics help your business?

#1. Financial metricsContact US

Procurement analytics can help to optimize the working capital. Furthermore, it helps in controlling spend over budget by comparing the purchase order value or the budget with the actual invoicing. Procurement analytics also aids in analyzing “Incoterms” to identify cost-effective opportunities.

#2. Pricing metrics

Procurement analytics helps organizations to understand whether they are paying different prices for a similar service or product across its geographies and divisions. It helps identify price variance by division or geography. Furthermore, it also helps analyze spend or price development to assess whether there is an increase in spending for an SKU or category and if it is resulting in a per unit cost reduction.demo

#3. Compliance metrics

Procurement analytics helps organizations to identify any variance from the agreed KPIs and defined process. Typically, these cannot be avoided completely but can be definitely controlled as they always come with a higher price point. Moreover, procurement analytics identifies spend from non- preferred and unapproved suppliers. Also, it aids in fraud detection by analyzing factors like spend near approval limits and large spend without a point of sales.

#4. Supplier base metrics

Procurement analytics helps organizations to understand the existing supplier base’s performance and identify opportunities to integrate further by using more global contracts and secure better pricing. Furthermore, procurement analytics helps to analyze the geography or division that has a high supplier base built up over the years. It aids in leveraging the geographic reach of existing suppliers to secure global competitive rates.


If you want to employ robust procurement analytics and uncover better insights from data for better vendor management, negotiation tactics, and purchasing strategy- request a free proposal now!

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