Using Data Quality to Create the “Golden Record” – Part 3: Common Use Cases in an Online World
In part 1 of this “Golden Record” series, I defined the term and spoke to the importance of verifying a customer email address. In part 2, I wrote about using telephone, mailing and IP address validation to maximize the accuracy of customer information to attract and retain customers. Now, let’s look at some of the most common data quality use cases that require “Golden Records.”
Data Quality Use Cases: Covering the Pros & Cons of Online Retail
Per an article in Forbes, more and more consumers are shopping online. If you ask me, Black Friday has a new “competitor,” Cyber Monday. According to a recent survey over 50% of customers purchase their items online and the trend is growing. People shop on their smartphones, tablets and computers when they find the time to shop with all the other things that seem to keep us busy on a day-to-day basis. Forrester Research has reported around 190 million US consumers – more than half of the population – shop online.
What does that mean for retailers? I see both opportunity and challenges. On the positive side, they have a great opportunity to capture online data for future segmenting and marketing. One of the major challenges is fraud prevention. The data quality use cases outlined below cover both the pros and cons of online retail.
Make Online Transactions Safer
It is no secret the use of stolen credit cards on the internet is rising, as criminals make more fraudulent purchases online to bypass stricter in-person retail security measures. To prevent fraud, organizations can use Trillium DQ.
For each transaction, your organization can check to see if the name, phone, address, email and IP address match and also return additional information about the input record. It can help you make decisions during the retailer’s order process and add an extra layer of security can help ensure that you’re processing a legitimate order.
How? If Trillium DQ returns a different name than what is submitted on the order, it may be flagged for further review. Let me explain. If, for example, a phone number is not valid, an address is not active, or an email is proxy, this should also raise a red flag.
Another indicator would be the domain. If the email domain is brand new, this is a very strong indicator of fraud. Disposable email and auto-generated email are also warning signs of possible forgery. Non-fixed VOIP phone is yet another very strong signal of fraudulent activity.
On the positive side, the following items would indicate a legitimate order is being processed:
- the input data matches the records returned
- the IP geolocation is near the physical address or phone on the transaction
- the address that is provided is actively receiving mail
Make Marketing More Targeted
In addition to helping retailers foil fraudulent purchases, there are other great reasons for using Trillium DQ. By processing your orders, you can generate additional valuable information. Here are three examples around segmentation and marketing.
1. Phone Number: Based on your input of a telephone number, you can capture:
- if the phone matches to the input name.
- the name of the subscriber of that phone number
- the subscriber’s address
- demographic information such as the subscriber’s age range and gender
2. Mailing Address: For the input on the address you get the following information
- know if the address is actively receiving mail
- the resident’s name and phone number
- demographic information such as gender .
3. Email Address: For every email entered in the system, you can find out:
- whether the email address is valid and deliverable
- if the email matches the name on the input
Based on the information above, you can now figure out where your customers live, including what town and zip code, as well as their age range as well as their gender. Through basic analysis, you discover that most of your customers are in their early 40s, female and live in a specific, affluent zip code. Perhaps your organization should invest a higher percentage of your buying spend for merchandise to cater to more to that customer profile?
Or, you may find your closest store is several miles away, and yet, based on their purchases, you should consider opening a store in or near their zip code. There are several areas where this information can be helpful to grow your customer base as well as save money on marketing to a zip code that may not fit your customer’s profile.
Download our new eBook, Getting Closer to Your Customers in a Big Data World to learn more about the different sources of customer data, which data points are critical in obtaining, and tips for customer 360 success.