With the healthcare sector beginning to leverage advanced technologies such as predictive analytics and AI, healthcare organizations, health care agencies, and primary health providers must be aware of its benefits and risks.
What is Predictive Modeling?
The process that uses statistics and data to predict results with the help of data models is said to be predictive modeling. Predictive modeling is used to predict anything from advances in technology to corporate earning. Predictive modeling methods use data mining and advanced analytics that are likely to influence results in the future. Predictive modeling techniques employ a complex network or a simple linear equation to analyze the datasets and then such data is run through algorithms to determine what kind of products or services users might be interested in.
What are the Different Predictive Modeling Techniques?
Technique #1: Behavioral Clustering
The path leading a prospective customer to convert into a buyer is incredibly valuable for a marketer who focuses on leveraging predictive modeling solutions. Behavioral clustering is one of the predictive modeling techniques that empowers marketing teams to determine trends and commonalities that help to create a new target segment. It can help marketers enhance conversions and predict the impact of marketing campaigns more precisely.
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Technique #2: Product-Based Clusters
This is a predictive modeling technique that segment customers together based on similar engagement and activity with the brand. Product-based clusters focus specifically on tracking specific buying trends among target demographics. These product-based clusters also help in forecasting the lifetime value of a customer. Such predictive modeling techniques help companies in identifying services that they can actually sell to the customer over a period of time.
Technique #3: Share of Wallet Estimation
“Share of wallet estimation” is a predictive modeling technique that assists companies to predict how much of their customer’s budget is with competitors. Also, it unveils what specific products or services you can sell to that particular customer in order to increase your share of wallet percentage. In order to attain the desired outcome, companies must leverage this technique along with the product-based clustering techniques.
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Technique #4: Likelihood of Churn
Predictive analytics models are used by most of the marketers for lead generation. But this is a mistake because predictive modeling techniques have strong defensive capabilities that can help in measuring the likelihood of churn. For most companies, customer churn can be a big issue but predictive modeling techniques can help by measuring customer’s propensity to churn by analyzing their behavior. It can help in identifying “red flag” behaviors from previously churned customers and their troubling behavior. Such information can be followed up by the customer service teams and this can be further transitioned into a nurture campaign to reduce churn. The impact can be significant when it comes to retaining current customers and boosting revenue by minimizing churn.
LONDON: Quantzig, a leading analytics services provider, has announced the release of their latest storyboard on predictive modeling techniques and how it can help businesses in proactive decision making and pre-emptive planning. With the availability of data in enormous volumes, it has become quite difficult for businesses to rapidly identify, objectively evaluate, and confidently pursue new market opportunities.
By using predictive modeling techniques, companies can enhance decision making and gain the ability to optimize, direct, and automate decisions, on demand, to achieve defined business goals. By applying predictive analytics models, businesses can not only better manage the present, but can also improve the probability of success in the future. In doing so, such companies become predictive enterprises.
The goal of predictive modeling techniques is to turn data into information and information into insights.
Quantzig’s analytics solutions have helped more than 55 Fortune 500 companies to make data-driven decisions and augment revenues. Below, we have rounded up some of Quantzig’s recent success stories for this week and have also highlighted ways in which predictive modeling techniques have helped businesses to become market leaders.
#1: Predictive modeling techniques improved 85% accuracy in demand forecasting: Providing seamless customer experience and complete customer satisfaction is a challenging task for any business. Don’t you agree? But predictive modeling techniques can help as it helped one of Quantzig’s clients. By utilizing predictive modeling techniques, companies can conduct analysis on historical information on sales, products, and inventory levels. Furthermore, it can reduce irregularities and streamline order management, resulting in better demand forecasting.
#2: Predictive modeling techniques precisely forecasted the roll-out of a new initiative: Predictive analytics models are the best way to improve business operations and predict future trends. This is clearly evident in Quantzig’s latest success story, where the client managed to make accurate predictions about the success and failure points of their new initiative. Moreover, it enabled optimal budget allocation.
#3: How can clustering algorithms uncover relations between invisible variants? If you are looking to upsell your products, this predictive modeling technique can certainly help. Clustering algorithms use data mining techniques to find out the relation between different invisible variants. Furthermore, this helps businesses to obtain desired outcomes.
#4: Predictive modeling techniques optimized inventory management: Optimizing inventory for better customer service is very essential for the success of any business. By leveraging predictive modeling solutions, companies can build better inventory and can discover capabilities to drive continuous market excellence. Furthermore, predictive modeling techniques can be successfully implemented, either independently or in tandem, to offer actionable insights into the performance of the inventory.
#5: How predictive modeling techniques can boost business outcomes? : Changing customer dynamics poses critical challenges before businesses such as managing customer demands. Don’t you feel the same? This is where predictive analytics plays the role of a savior. By leveraging predictive analytics solutions and utilizing predictive modeling techniques, companies can deal with a humongous set of data, which can aid decision-making.
#6: Utilizing predictive modeling techniques to boost customer retention dramatically: Managing the huge amount of customer data is not an easy task for businesses and we understand that. This success story is an excellent example of that as one of our clients faced the same issue and approached Quantzig to leverage its expertise in offering predictive analytics solutions to reduce customer churn rate. Also, our predictive modeling techniques proved beneficial for the client in integrating traditional and digital data sources to correlate the data and identify potential churners.
#7: Why you can’t afford to ignore predictive modeling techniques? No matter which industry you are in, retail, transport, or healthcare, you cannot ignore the importance of predictive modeling. It helps you to gain a comprehensive understanding of the market trends, customer behavior, or competitor’s approach. Furthermore, by utilizing predictive analytics models, companies can easily track the volatility of different categories, brands, and products. This can result in better business outcomes.
#8: Predictive modeling models identified inefficiencies and improved ROI: Analyzing customer lifecycles to devise better marketing strategies and improve customer service is one of the common issues that every business faces, so don’t be surprised if you are facing the same challenge. If you have a proper predictive modeling technique in place, you have nothing to worry about. A leading firm in the healthcare industry was facing the same issue but witnessed a great change in their approach to risk assessment after leveraging Quantzig’s predictive modeling solutions. Moreover, it reduced inefficiencies drastically and improved their ROI.
#9: Predictive modeling techniques enhanced fraud detection and customer satisfaction: For some businesses, anticipating fraud risk is a herculean task. This impacts their customer service and the customer ends up having a bad experience. So, for such companies, utilizing predictive modeling techniques is a necessity as these techniques can help anticipate potential suspicious claims and fraud risks.
#10: How can predictive modeling increase accuracy and improve efficiency of marketing strategies?: Accuracy in forecasting the impact of several factors on the business outcomes is essential if you want your business to grow. Predictive models, in this context, hold the key to success. These models have the potential to assess and predict the performance of different components and their tentative impact on the future of the business. Furthermore, this can allow companies to make smarter decisions and exit declining markets.
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With the shifting key values of every industry from customer-focused to customer-centric, there is an immense growth in data and information. This has changed customer dynamics and as a result, every business is facing numerous challenges such as market uncertainties, driving efficiency, and effectiveness in their marketing productivity, immense competition, customer demands, fraud detection, and risk management.
Many businesses across all industries, in order to cater customer demands, are trying to utilize the data that their customers leave behind while interacting with the company. Harnessing this pool of data can offer several benefits to organizations. However, many companies still have not realized the importance of data mining and have not gone beyond gathering and storing their data. Although it is difficult to deal with an unstructured set of data by leveraging predictive analytics solutions businesses can fetch optimum results from such data.
At Quantzig, we understand the impact that predictive analytics solutions can have on your business. And to help companies derive actionable insights from large and complex data sets, our team of experts has highlighted three important ways in which predictive analytics solutions can help in managing large volumes of data and setting up analytical frameworks to derive real-time insights that facilitate more informed and wise decisions.
There is an unprecedented amount of information available in the transportation industry today, which contains immense potential for deriving insights that aid in planning and managing transportation networks. This data is captured from various sources such as onboard sensors and data collection points introduced by passenger counting systems, systems scheduling, asset management systems, ticketing and fare collection systems, and vehicle location systems. Players in the transportation industry can leverage advanced analytical techniques such as predictive analytics to use the available data to improve operations, reduce costs and better serve travelers.
How can predictive analytics help?
Any technology that can improve efficiency on a “more is less” paradigm has the capability of making things much easier for both transit agencies and the passengers they serve. Predictive analytics can fill that role to some degree. With the help of predictive analytics, transportation companies can answer the question of “What’s the best possible outcome?” instead of explaining prior history. In this manner, it can help them with many different capacities, from vehicle fleet maintenance to planning new lines of services. Let us explore some of the critical areas in which predictive analytics will help the transportation industry players:
- Predictive analytics can help companies to determine the impact of unplanned events such as a transit labor strike on transportation utilization and the local economy.
- Transit agencies can also understand how subway line closures, planned road-works or transit maintenance projects can affect public transport. They can then use this insight to plan the optimum change in transit schedules and communication strategy to deal with the impact.
- Identify and predict the likely occurrence of routine unplanned service incidents like a traffic accident or vehicle breakdown, and suggest optimum responses.
- Predictive analytics can model the impact of various proposed urban development projects to transportation and help in the identification or alteration of the projects to achieve sustainability objectives while supporting the need for mobility.
- Companies in the transportation industry can pinpoint events such as bus breakdowns, late-arriving buses, or signal outages that have the highest economic impact to a transit agency and recommend ways to eliminate the events or reduce the effect.
- Predictive analytics can help transportation players to predict the impact of the planned expansion of transportation networks by having a clear understanding of the patterns of usage.
- Transportation agencies can understand when the vehicles require maintenance well in advance with the help of predictive analytics. Such advanced analytics capabilities help to identify irregularities and forecast a range of asset performance risks before trouble arises in the case of vehicles owned by the transportation agency.
- With the help of predictive analytics, public transportation companies can predict significant events or days during which they would experience high demand for services. They can adjust or supplement their facilities accordingly to accommodate visitors better and avoid putting additional cars on the road that cause congestion.
In the healthcare sector, consumers’ preferences are changing, and the customers are looking for fast, cost-effective, and convenient care options. With the growing popularity of healthcare retail, the number of retail clinics is expected to increase in the coming years. With customers becoming more informed than ever before, it becomes vital for businesses in the retail space to improve the supply chain visibility – right from the manufacturing stage to their final destination. In the healthcare retail space, supply chain visibility helps businesses streamline their logistics plan to combat issues pertaining to disruptions and supply chain complexity. In many large organizations, managing inventory becomes a primary concern. Supply chain visibility can address this issue by maintaining an all-transit inventory. Moreover, effectively gauging the supply chain visibility helps retailers gain real-time information about the production status and determine the actual costs of the products. In this patient-centric environment, supply chain visibility helps businesses compare the performance of the products.
To effectively address the market challenges, leading healthcare retail clients are approaching renowned solution providers such as Quantzig. Quantzig’s supply chain process is tuned to provide a seamless and efficient flow of materials. The solutions offered by Quantzig help businesses reduce potential bottlenecks associated with supply chain and improve lead times and the overall performance. Leading businesses in healthcare retail can further identify shortage and quality problems in the supply processes.
The Business Challenge
A leading healthcare retail client was facing certain predicaments reducing costs and improving operational performance. The client wanted to identify best practices in revenue management and improve profit margins to enhance visibility and reduce supply chain complexity. With the help of our supply chain visibility study, the client wanted to enable faster and more efficient responses to changing customer demands. The primary concern of the client was to reduce costs associated with the supply chain and inventory management. Furthermore, the healthcare retail client wanted to outsource, optimize, and manage logistics services in an efficient manner.
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Benefits of Quantzig’s solution
The solution offered helped the client address issues pertaining to logistics and combat supply chain complexities and disruptions. The engagement also focused on identifying shortage and quality problems to improve lead times and performance. Moreover, the engagement completely focused on identifying the visibility blind spots to respond to disruptions in a timely manner. The engagement also focused on satisfying the future demand of the customers in an effective and efficient manner.
Additional Benefits of Quantzig’s Engagement Include:
- Gained a unified view across the enterprise and gained an accurate understanding of current business realities
- Retail players were able to expand their service portfolio and enhance patient experience
- Identified the bottlenecks in the healthcare retail space and revamped the continuum of care
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In the current business scenario, technology plays a pivotal role in the sustenance of any business organization, and for the same, organizations are implementing IT services across their platforms. While IT services, assist individuals and enterprises in implementing, managing, and operating process, it becomes important to understand the customers and their business requirements. In any service-level organization, customers are the king, and to effectively reach out to them; organizations in the financial industry require a rigid and robust sentiment analysis solution. In the IT services space, sentiment analysis helps businesses analyze customers’ feelings, attitudes, and opinions and how people are responding to these services. Moreover, sentiment analysis also helps businesses adapt to different strategies if the touch points are resonating with the customers. With the help of sentiment analysis, leading IT services providers can understand the impact of their media campaigning efforts by tracking customers’ opinions in terms of comments, shares, likes, and re-tweets.
To better understand the brand’s perception and analyze quality metrics, renowned IT services providers are approaching companies like Quantzig. With years of expertise in offering a plethora of services, Quantzig’s sentiment analysis solutions help IT services providers analyze social media channels in terms of opinions, feelings, and satisfaction levels and further generate leads for the brands and businesses.
The Business Challenge
A renowned IT services provider with a considerable number of service offerings spread across the globe was facing certain predicaments analyzing the customers sentiments and profiling potential target segments. The client wanted to actively listen to the audience and identify the initiatives which would deliver the desired outcomes. With the help of sentiment analysis solution, the IT services provider wanted to uncover new insights to better understand their target audience. Furthermore, the client also wanted to efficiently track the competitors and devise effective marketing campaigns to improve business outcomes.
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Benefits of Sentiment Analysis
The sentiment analysis solutions offered by Quantzig helped the IT services firm effectively manage and measure the social networks and gain valuable insights into the online channels. Moreover, the client was able to measure their performance at each stage and analyze how the content is shared across different platforms. Also, the engagement further helped the client keep track of the inbound marketing initiatives and gather, analyze, and manage conversations.
Sentiment Analysis Predictive Insights
- Gain an overview of the wider public opinion and make agile and informed decisions
- Quickly understand customer attitudes and measure the brand’s reputation
- Monitor social media posts and discussions and analyze the reaction of customers to the specific brands
- Improve revenues by 10% and enhanced market shares
- Stay relevant in the business and expand their customer base by 20%