The more you know about your customer, from the first point of contact onwards, the better you can respond. Companies who use behavioral data efficiently are more profitable. They react more quickly and appropriately to customer and market demands.
Behavioral data is derived from human, device or system behavior, as opposed to structured, application data. Typically, during a 1 minute, on-line session, between 5,000 - 12,000 items of behavioral data/features can be collected.
Behavioral data allows you to build a 360° picture of your clients. It can be used for far more than just simple scoring, (e.g. credit scores etc.). Typically, predictive behavior data is combined with “conventional” data such as, application data, credit bureau data. This can significantly boost the accuracy and range of predictive results.
Read more about collecting and using behavioral data in your digital product
Just a random thoughts on software development, programming, data science.. and some of my projects.
2017-02-07
Decision Engine - an Essential Component for Digital Products
In many ways selling digitally is no different to selling face to face. You need to understand as much as possible about your customer and ask the right questions. Then, you can continually adapt your approach as you learn more and make consistent, accurate decisions.
If you are selling financial products via the Internet or an App, you need to make automated, reliable decisions. These are no different to the ones you would make if selling face to face. For example, if you receive a lead or referral to your web site, they might be,
- do I want to pay for this lead? Is it likely to turn into a sale and a profitable customer?
- which product should sell?
- if they don’t qualify for product A, should I sell product B?
- what is the risk? how should I price? do I underwrite this client?
- will they pay on time?
- will they renew or churn?
- are they who they say they are? is this a fraud?
The core of any decision engine is that business users can easily/quickly capture the logic underlying the business’ operation. This is done by creating, testing and managing executable business rules in a human understandable form or graphical notation, without the need of IT involvement. The order of execution and optimization of rules execution is automatically resolved, so is not dependent on business user ability to create optimal logic.
Read more about intelligent decision engine
Subscribe to:
Posts (Atom)