Entity analytics is used to detect non-obvious relationships, resolve entities, and find threats and vulnerabilities that are hiding in your disparate collections of data. Through the medium of three use cases, let’s try to understand how Entity Analytics can help organizations enhance their customer experience.
Entity Analytics can detect non-obvious relationships between entities. It can also analyze new data sources in context leading to new insights and opportunities. In this scenario you have some data in an MDM system and another set of data in a spreadsheet file. Suppose you want to run a marketing campaign to target high-net-worth clients to sell them a premium bank account. The information in the one MDM system in isolation doesn’t give you the needed information. You want to bring these two sources together and determine if you can identify individuals that can be targeted for the new account.
In the MDM system, John Smith lives with Mary Smith. The spreadsheet file shows that John Smyth (spelled differently) is actually a high-net-worth client. Combining this information we can say that John Smith is actually the same person across the data sets. He’s a high-net-worth client, and he has a wife. With this information you want to target Mary Smith with a premium bank account because she lives with a high-net-worth individual. Entity analytics enables you to discover and understand this opportunity.
Entity Analytics can find where threats and vulnerabilities are hiding in big data and respond efficiently. In this scenario for a risk assessor in an insurance firm, severe rainfall is predicted within a geographical area that includes the client’s residential location. When pulling up the client data from MDM and the flood warnings being issued from the environmental agency, we can match across the data sets to identify that a number of properties are at risk. So, the client can then be provided an early warning to help mitigate risk and increase the flood risk value on the client’s property renewal. Also, if you have an elderly customer that is at severe risk; you can take action to notify the emergency service to ensure a proactive resolution to any potential threat.
Lets see how using Entity Analytics, MoneyGram International Inc., a money transfer company gets notified of questionable activities in real time for faster predictive and preventive decision making. This helped them to save $200 million in just two years!
Entity analytics help organizations by launching more target-oriented campaigns and by reducing the risk of fraud. With the help of entity analytics, organizations can predict and preempt suspicious activity faster and with reduced costs. Entity analytics further help by allowing enterprises to detect the entities that are the same, regardless of whether the entities are hidden or masked. So following questions can be raised:
- Does this Analytics require an MDM Ninja or can something be set up easily by a Business user?
- Do we have Entity Analytics available on Cloud for decisions that cannot waaaaiiiiittttt?
Stay tuned for my next blog.