Predictive Analytics Business Use Cases Ensure Results!

Apply Predictive Analytics to Specific Business Use Cases for Real Results!

Gartner has predicted that, ‘Overall analytics adoption will increase from 35% to 50%, driven by vertical and domain-specific augmented analytics solutions.’ Your business, like every other business in the world, has its own industry, domain and vertical concerns, and these concerns drive your competitive strategy, your products and your services.

Predictive analytics uses sophisticated analytical methodologies to predict future outcomes based on historical data. Using these techniques, the organization can predict future events, customer buying behaviors, and business outcomes. These techniques can help the business drive results, improve revenue, understand customer and client buying behavior, solve problems, plan for new locations and products, create accurate pricing strategies and plan for new resources and training, as well as for appropriate maintenance, supply chain services, etc.

‘Take the guesswork out of the planning process and analyze factors that influence business success. Plan and forecast accurately.’

Predictive Analytics utilizes various techniques including association, correlation, clustering, regression, classification, forecasting and other statistical techniques. These techniques can be targeted to specific business use cases to solve specific, unique business issues and to help the business plan, forecast and compete.

In order to understand how businesses might use assisted predictive modeling and predictive analytics, let’s look at some business use cases and how analytical techniques can help the enterprise derive concise, clear information to support decisions and strategies.

Minimum Viable Products (MVP) Produces Better Business Start-Up Results

Customer Churn

The cost of acquiring and interacting with customers can be expensive and each time a business loses a customer, it must spend money to replace the customer.

Fraud Mitigation

Businesses must mitigate fraud and control business costs and must develop and sustain fraud detection processes to monitor operations.

Quality Control

Businesses must control quality or risk losing customers and market share and exposing the enterprise to legal risk and liability.

Demand Planning

Take the guesswork out of the planning process and analyze factors that influence business success. Plan and forecast accurately.

Product/Service Cross-Selling

Leverage customer satisfaction to cross-sell and upsell products and services and increase revenue and brand loyalty.

Maintenance Management

Focus on equipment maintenance to ensure that downtime is limited and equipment is up and running, anticipate resources, hours on the job and training needs.

Customer Targeting

Identify the reasons customers buy a product or service and use fact-based data to create products, marketing campaigns, ads and customer outreach. Target specific demographics and customers.

Human Resource Attrition

The enterprise must retain team members and to do so, it must understand what makes a team member stay or go, what makes them invest in the future of he business and what issues create issues and dissatisfaction.

Loan Approval

The enterprise must avoid bad loans, so as to enhance profitability and productivity and it must have a dependable process for identifying and attracting the right clients and for reviewing, approving and managing loans.

Marketing Optimization

Create attainable targets and goals with an understanding of what improves and affects sales and how customers choose a product or service, how to market and advertising to achieve objectives.

Predictive Analytics Using External Data

Integrate external data and analyze data to assess the affect on sales, marketing, finances, resources, productivity, etc.

Online Target Marketing

Optimize marketing funds and resources, understand what works and what does not work, and how, when and where to message and the ideal demographic and profile of the target customer.

Student Academic Performance

Predict academic performance of students to effectively manage student interaction and training and improve environment to assure student success.

Crime Type Prediction

Predict the type of crime that is likely to occur to plan for appropriate law enforcement resources, placement and strategies and ensure public safety and appropriate use of funds.

‘Predictive Analytical techniques can be targeted to specific business use cases to solve specific, unique business issues and to help the business plan, forecast and compete.’

Find out how Assisted Predictive Modeling and Augmented Analytics can help your business plan for success, and explore the potential of comprehensive Predictive Analytics here.

Get the Right Predictive Analytics Tools for Users!

Can Predictive Analytics Provide Accurate Results for My Business Without Burdening My Users?

If your business is struggling to forecast and predict outcomes and results, your management team is probably considering predictive analytics. The technology research firm, Gartner, states that, ‘50% of data scientist activities will be automated by artificial intelligence, easing the acute talent shortage.’

For the average team member, the concept of predictive analytics may seem daunting and, if you are a business user whose management team has asked you to embrace and participate in analytics, the addition of predictive analytics to your day-to-day business processes may seem irrelevant or it may seem to mean you will be expected to work harder or produce more output. But don’t be too quick to assume the worst.

‘By providing this type of expanded functionality to the team, the business can enable both data scientists and business users with predictive analytics that will benefit the organization.’

Let’s take a look at Predictive Analytics, the benefits of Assisted Predictive Modeling and its importance in the organization and how intuitive augmented analytics can help business users achieve their goals without requiring advanced training or additional workload.

Predictive Analytics Can Make Business Users Happy!

What is Predictive Analytics?

Predictive analytics is comprised of sophisticated analytical methodologies that allow businesses to predict future outcomes based on historical data. Using these techniques, the organization can predict future events, customer buying behaviors, and business outcomes. Predictive Analytics utilizes various techniques including association, correlation, clustering, regression, classification, forecasting and other statistical techniques.

Understanding Assisted Predictive Modeling

When a business provides augmented analytics tools for business users, it allows the team to perform predictive analytics on a daily basis without the assistance or skills of a Data Scientist or an IT professional. Assisted Predictive Modeling provides auto-suggestions and recommendations to guide business users with recommended techniques, selecting the most appropriate techniques for the type and volume of data the user wishes to analyze. If the business chooses an augmented analytics tool with intuitive predictive modeling features, it allows users to work quickly and receive clear, concise results for decision-making so user adoption of the tools is more likely and forecasting and predictions are accurate and timely. All popular predictive modeling techniques are incorporated into the solution, so users have access to the most sophisticated predictive analytics and tools and can use these tools to model and review business use cases and issues.

The Benefits and Importance of Assisted Predictive Modeling

These tools allow the organization to apply predictive analytics to real use cases to analyze customer churn, to target customers, to identify cross-selling and product bundling, to find and set appropriate price points, to forecast where and when to open new locations, when the business will need new suppliers, when equipment will require maintenance, etc. A comprehensive augmented analytics solution also includes the benefit of integration with R Script, so that data scientists can capitalize on expertise and leverage enterprise investments in R open-source platforms, to perform statistical and predictive algorithms, and complex analysis to provide the depth of detail and advanced analytics and reporting the organization needs for strategic decision-making. By providing this type of expanded functionality to the team, the business can enable both data scientists and business users with predictive analytics that will benefit the organization, encourage collaboration and data sharing, and improve data literacy – all without increasing workload or frustrating users and team members.

‘Intuitive assisted predictive modeling and augmented analytics can help business users achieve their goals without requiring advanced training or additional workload.’

Find out more about Assisted Predictive Modeling and Augmented Analytics and explore the potential of comprehensive Predictive Analytics here. Find out how it can improve user adoption of analytics and increase accuracy of forecasting and results.

Plug n’ Play Predictive Analysis for Business User Data Prototyping!

Whether your business is a small, single location brick and mortar enterprise or a large, multi-facility organization that spans the global market, you need access to sophisticated, easy-to-use business intelligence tools in order to compete in local, regional and global markets.

Predictive Analytics for Every Skill and Use!

Assisted Predictive Modeling That is Suitable for All Users!

Your Business Users Will LOVE Predictive Analytics Tools!

Predictive Analytics used to involve a crystal ball but, today, there are other options and they are more widely accepted in the business community! With the right predictive analytics tool, your business can hypothesize, test theories, discover the effects of a possible price increase, discover and address changing buying behavior and develop appropriate competitive strategies.

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What is Predictive Analytics and Can it Help You Achieve Business Objectives?

What is Predictive Analytics and Can it Help You Achieve Business Objectives?

The process of predictive analytics has come far in the past decade. No longer is this process the sole responsibility of data scientists or IT staff. Today’s self-serve predictive analytics and forecasting tools are designed to support business users and data analysts alike.

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Assisted Predictive Modeling for Simple Business Analytics!

Predictive Analytics for Business Users

No Guesswork! Just Simple, Assisted Predictive Modeling for Every Business User!

No matter the market or type of business, there is no room in today’s business landscape for guesswork. You can’t get a business loan, join with a business partner, successfully bid on a project, open a new location, hire the right employees or plan for the future without predictive analytics.

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Can Plug n’ Play Predictive Analytics Be Used in Hospitals?

Predictive Analytics Tools Can Help Hospitals Plan

How Can Predictive Analysis Tools Help My Hospital or Healthcare Organization?

Hospitals and healthcare systems are turning to predictive analytics tools to plan and forecast and understand what, when and how to support patients.

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Is Plug & Play Predictive Analytics Good for Business Users?

Plug n' Play Predictive Analytics Helps Business Users

Can Plug & Play Predictive Analytics Help Business Users Function Effectively?

Plug & Play Predictive Analytics is not an exotic process that is limited to data scientists or IT staff. Plug & play predictive analysis is so named because it really is a plug and play process. This type of predictive analytics tool is designed to be accessible and usable by business users.

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Plug n’ Play Predictive Analytics for Your Business

Assistive Predictive Modeling for Every Business User

How Can Assistive Predictive Modeling Help My Business Users?

Assistive Predictive Modeling allows business users to leverage a self-serve advanced analytical tool and to enjoy complex, sophisticated forecasting and business predictions in a simple, user-friendly dashboard environment – all without the skills of an analyst, data scientist or IT professional.

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