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Sep

15

Optimal Data Analytics to Improve Marketing in Lending

Lending Marketing Data Analysis
Being visual creatures, it only makes sense to break down data analytics into a picture that we can better grasp and understand. Visualizing each individual aspect and component of our quantitative data allows us to put our hands on our tools, so to speak. Only then can a data set work to our full advantage.
Data analytics provides lenders the capability of easily recognizing, analyzing and making powerful connections between data profiles. With 30+ years of experience our team of analysts have proven how its data modeling skills can pave the road for future informed predictions that will ultimately improve lead generation and higher customer acquisition.
The Five Levels for Optimal Analysis of Data
Analysis of data can be dissected into five fundamental levels: descriptive, diagnostic, inferential, predictive, and prescriptive. These classes of analysis are assigned different levels based on knowledge, cost, and time. All, however, are essential for lenders to achieve all of their marketing objectives, which is something we are committed to help financial institutions with.
We begin with the most basic form of data analysis that answers the question: “What is happening?” Descriptive Analysis encompasses the main features of a collection of data. It refers to all the primary characteristics of the prospects within the set of data. When analyzing data at the Descriptive level, we help lenders look for characteristics that simplify their large amounts of data in a sensible way. These characteristics vary between the type of lender that you are. For example:
  • Consumer Lending: Credit, Debt History, Demographic
  • Mortgage Lending: Loan Details, Loan History, Demographic
  • Business Lending: SIC, Business Credit Profile, Years of Operation, Revenue
At this point, it’s time for lenders to approach their data set through Diagnostic Analysis. Ask yourselves, “Why did this happen?” Known values and variables can be utilized to allow lenders to control the data set to answer the unknown. This is extremely powerful when it comes to using that data for marketing through Direct Mail. Segmentation based on the different aspects of your data set will also allow you to craft a sales pitch that is personalized for each prospect. This will give you, the lender, the desired response far more frequently.
Inferential analysis sets the scene for making connections and predictions that we were unable to, prior, to breaking down our quantitative data. Lenders can accomplish this by comparing smaller selected data set with a wider set of data. These previously unknown relationships between specific prospects and the broader set of prospects become guides to future practices and tests. Never settle for a single-sourced data set! Collecting data from multiple sources will increase your chances of generating the right kind of leads.
Predictive Analysis asks the question: “What is probably going to happen?” The previous levels of analysis provide us the power to envision likely future results. Lenders can look at the previous behavior of their customers and make an educated prediction of how they and other prospects will behave in the future.
It’s finally time to take all of these levels and do exactly what the Doctor asked for: Write a prescription. Prescriptive Analysis answers the question: “What should I do next?” We’ve dissected our data set, examined each aspect, and now it’s time to take action. We need to combine our predictions and qualities that will enhance our forecasts such as when and why our prospects are behaving in a particular fashion. These five levels build the steps for lenders to put their marketing strategies into overdrive.
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