Dongyang Li
1 Year Ago

There are many reasons why predictive analytics should be a high priority for your company’s strategy.  First, the competitive landscape is changing every day and customers’ access to competitor information is driving:  Thinner margins in most verticals, and customers have become more demanding and selective, and have more choices.  It is clear from research that companies that are thriving in the new global digital environment are those that are will to adapt to changes and innovate ahead of the competition. This provides companies the ability to stay leaner, be more agile, and embrace predictive analytics.

Understanding Predictive Analytics

Let’s start talking about predictive analytics with a simple but important question: What is Predictive Analytics?  Predictive Analytics examines patterns found in internal and external data to identify future risks and opportunities.  It is necessary to clarify that predictive analytics is not only about predictions or the future, but also offers more data analysis and data mining capabilities to identify patterns where potential issues and opportunities exist.  Predictive analytics has the ability to drive innovation in most areas of your business.

There are many areas in marketing such as, cross-sell, up-sell, customer retention, direct marketing, pricing and customer relationship management (CRM).  Other potential areas where predictive analytics has had a major impact are:  Risk assessment and management, fraud detection, disease prevention and disease management.  

Examples of Companies Embracing Predictive Analytics

Some companies that have embraced predictive analytics in all aspects of their business are Amazon, Netflix, LinkedIn and Facebook.  Amazon and Netflix have been using predictive analytics almost from the beginning, about two decades, to drive sales through recommendation engines and customer satisfaction.  LinkedIn and Facebook have been around for about a decade and use predictive analytics in almost all of their business decisions.  Although these companies are relatively new in comparison to blue-chip giants like Walmart and IBM, they are now some of the biggest companies in the world. One major reason is:  These companies have pioneered the use of predictive analytics in managing customer relationships and target marketing.  

Real-Life Examples

If you feel these examples are too “abstract” then let me provide you with some real-life examples that Dunn Solutions Group (DSG) has done for its clients!

Case One:

Client: Online Mass Retailor

Business Area: Cross-sell, Up-sell

Challenge: Online Mass Retailer was missing out on the opportunity to add additional revenue by providing differentiated customer experiences and by offering the right items in the right order to increase cross-selling

Solution: Identified optimal product mix and cross-sell offering. Helped to customize the consumer experience and optimize revenue through more revenue per customer.

Result: Recurring annual benefits of more than $80 M in additional cross-sell revenue and an average increase of $.94 per customer purchase

Case Two:

Client: Fortune 100 Insurance Company

Business Area: Target Marketing, Product Performance Simulation, Pricing

Challenge: A subsidiary of a Fortune 100 insurance company provides health insurance services
in 29 states and was facing specific new competition. Products were underpriced for claims experience. Larger competitors were quickly gaining market share.

Solution: Performed Segmentation of Customers. Developed Forecasting Simulation Tool to predict product performance. Developed Marketing Mix and Market Potential. Market based assessments to better target customers

Result: Transformed the subsidiary into the fastest growing individual health insurance company in the nation at a time when most in the industry were shrinking. Doubled the portfolio with targeted high-value customers in just 18 months to over 370,000 customers and $500 million in new annual revenue.

Case Three:

Client: Top U.S. Bank

Business Area: Operational Optimization, Intervention Modeling

Challenge: Top 10 U.S. Bank faced with mounting delinquencies in all banking areas. A huge backlog of foreclosures.

Solution: Designed a predictive analytics modeling engine and dashboard reporting environment
that tracked all consumer lending and mortgages. Tracked customers through models to help determine when and what action best fit the situation.

Result: Generated models on defaulting loans which justified an additional $2.2 billion in TARP money. Staffing Model and Capacity Planning for Collections and Defaults. Use automated dialers to call customers. Using targeted messages to better handle the collections and default, saving $9 million each month in extra phone capacity. Increased collections and curing by 25% Better Customer Risk targeting $40 Million. Which collections and foreclose first? Which properties and customers were best to restructure and make other offers? Prioritize properties, loans and targeted outcomes.

Case Four:

Client: Higher Education

Business Area:  Student/Customer Retention Analysis

Challenge:  A large online higher education organization was facing ever increasing student churn.

Solution:  Identified key drivers that were causing higher than normal student churn.  Also, developed a series of intervention and reacquisition models for admissions and professors that identified key drivers that contribute to student churn at critical points in time to save the student. 

Result:  This drove an ROI on the project of 328 times the cost of the project and 15% student retention from intervention five year program and one time 5% reactivation campaign of inactive students

Therefore, there are many competitive advantages that you can gain over the competition by using predictive analytics and the expertise that Dunn Solutions Group can provide.  Why fall behind when leading companies are enjoying and thriving because they are using predictive analytics and Dunn Solutions Group.  Feel free to contact our Sales Team (Email: sales@dunnsolutions.com Tel: (847) 673-0900 x104) at Dunn Solutions Group to take advantage of our ability to help our customers return an average of $100 dollars for every dollar spent on predictive analytics.  Why Dunn Solutions Group? and not someone else because most firms only return and average of $10.66 for every dollar spent because they may not take the time to understand your business the way we do!!!!