Tag: predictive analytics models

predictive modeling

A Definitive Guide to Predictive Modeling

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.

Request a FREE demo to find out how our predictive analytics solutions can help you gain actionable insights into the performance of your marketing campaigns.

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.

Our predictive analytics solutions can help you curate, process, and analyze  data sets precisely. Request a FREE proposal to know more about our portfolio of services.

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.

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Predictive Analytics in Marketing: Key to Drive Business Profitability in 2019

What is Predictive Analytics?

Predictive analytics is an approach that helps in predicting unknown future events. There are many techniques that are used in predictive analytics such as machine learning, data mining, data modeling, and artificial intelligence to examine current data and make future predictions. Also, it helps in finding patterns in both structured and unstructured data sets, thereby assisting in the identification of future risk and opportunities. Furthermore, predictive analytics has the potential to integrate management and technology together to drive better business outcomes. By leveraging predictive analytics solutions, businesses can become dynamic and can anticipate behaviors and outcomes based on the known facts and data and not merely upon assumptions.

How can predictive analytics solutions help businesses derive successful outcome and boost ROI? Read Quantzig’s recent blog to find out.

3 Ways Predictive Analytics Solutions Can Help Businesses Derive Successful Outcomes

Leveraging Predictive analytics in marketing can help businesses refine their marketing strategies and provide personalized services to customers. Want to know how? Get in touch with us right now!

Predictive Analytics in Marketing Realm

How can predictive analytics in marketing drive profitability for business? Are you thinking the same? The answer to it is, any tool, process or technique that can guide marketers to identify the buying habits of consumers is nothing less than a boon to their business. This is because if the past buying habits of a customer are identified and analyzed well, it can help in projecting the future buying habits, thereby helping in future decision-making based on those projections. Predictive analytics in marketing helps to ensure that these predictions are precise and accurate.

Here are a few things that a business can do when the available data is mined and predictive analytics in the marketing realm is applied:

Analyze and predict the seasonal behavior of customers

Today most of the products and services are sold online. Application of predictive analytics in marketing especially helps in this case. It helps in highlighting the products that are on high demand and those that customers prefer to buy at any given time.

Target the most profitable product category

The second benefit that businesses gain by applying predictive analytics in marketing is that they can target the most profitable products and services.  By administering the technique of artificial intelligence and machine learning, it is easy to identify affluent customers who prefer high-end products. This is an integral part of effective and predictive marketing strategy too.

By applying predictive analytics in marketing businesses can gain insights into new profits streams, better ways to conduct the business, and ultimately lead the game. Request a free proposal to know more.

Employ the most suitable marketing strategy for winning repeat business

Predictive analytics in marketing can inform businesses about customers who are most likely to be repeat customers. Owing to the high competition, businesses need to allocate resources on targeting such customers that are likely to profit the business the most. And applying predictive analytics in marketing is the best step to achieve this.

How can predictive analytics help in forecasting consumer demand precisely? Read our latest success story here to gain better insight.

Forecasting Consumer Demand with the Help of Predictive Analytics – A Quantzig Success Story

Prioritize customers

Finally, predictive analytics in marketing helps in prioritizing customers. It helps in identifying factors that indicate that a particular customer s most likely to become a repeat customer. It guides to recognize customers who buy the highest-margin products and are most likely to initiate returns.

Use-Cases of Predictive Analytics in Marketing

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Use Case #1: Refine segmentation for better campaigns

Applying predictive analytics in marketing helps in refining customer segmentation and creating customized campaigns. It allows to mine behavioral and demographic data to push quality leads further down the sales funnel.

Use Case #2: Improves content distribution strategy

Sometimes even the good content fails to drive business and the reason behind this is an ill-defined content distribution strategy. By applying predictive analytics in developing a marketing strategy, this problem can be tackled head-on. Using predictive analytics in marketing makes it easier to analyze the types of content that resonate most with customers of certain behavioral or demographic backgrounds. Furthermore, this helps in distributing similar content to such customers sharing the same demographic or behavioral habits.

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Use Case #3: Precise prediction of customer lifetime value

Artificial intelligence and machine learning can make predictive analytics in marketing more efficient. It can enable businesses to gauge the historical lifetime value of existing customers that match the backgrounds of new customers. Consequently, this can help in making a fair and precise estimate of the lifetime value of new customers.

Use Case #4: Better insight into the propensity to churn

Protecting your bottom-line becomes much easier by leveraging predictive analytics in marketing. How do you ask? By analyzing and learning from the mistakes committed in the past. By applying predictive analytics in marketing, businesses can analyze the behavioral patterns of previously-churned customers. Furthermore, this can help in identifying the warning signs from current customers. Consequently, businesses can take measures to plug such customers into a churn-prevention nurture campaign.

Use Case #5: Optimization of campaign channels and content

By leveraging predictive analytics in marketing, businesses can optimize their campaign channels as well as the content. With the entry of new customers in the business pipeline, there is an availability of their data which can be utilized for the various purpose. These purposes include identification of most suitable marketing channels, content type and even data and time to target specific and potential customers.

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Predictive Analytics in Healthcare: A Pathway to Personalized Patient Care

Every industry today is transformed virtually by predictive analytics and the healthcare industry is no exception. Predictive analytics in healthcare is advancing patient care significantly by offering detailed insights into the medical history of patients. However, there are many healthcare organizations that are yet to tap into the full potential of predictive analytics in healthcare. Deploying predictive capabilities in extracting actionable, forward-looking insights from the growing pool of data is still a daunting task for many healthcare companies.

However, realizing the power of predictive analytics in healthcare is highly essential as predictive analytics platforms can help healthcare companies to transform medical wisdom into real-world insights. Leveraging predictive analytics in healthcare can help companies to move into the new era of medicine. Consequently, this can improve hospital care, help in the management of chronic diseases and enhance supply chain processes.

At Quantzig, we understand the difference that leveraging predictive analytics solutions can create in the healthcare industry. And to help companies in the healthcare sector stay ahead of the curve, our team of analytics experts have highlighted the ways in which predictive analytics can improve healthcare and also have explained a few use cases for predictive analytics in healthcare.

Are you looking for ways to gain consolidated insights to mitigate risks and resolution of issues for medical cost management and improved patient care? Get in touch with our experts now!

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