Data is the key

Online-shops use data to create a pleasant shopping experience. But what about the final step, paying for what the shopper has collected in their cart? How can data help to increase conversion, prevent fraud and lessen customer care costs?

In times where there is one scandal about the misuse or leak of data after the other, people tend to be protective about their data. Which is generally a good thing, at the same time it can make it more difficult for online shops and payment providers to offer a good service to the shopper. This is because data is not only used to place advertisements, but important to offer a good customer experience and fraud prevention as well. In general, it is not about one data point, it is the combination, which makes the system better. The more data points are available, the more specific merchants or payment providers can differentiate between fraudulent and genuine shoppers and offer useful customer support. This leads to better shopper experience and less contact rate in the customer service teams of merchants.

In general, there are three main categories, we like to focus on: identification and scoring, fraud prevention and customer experience. Let´s have a look at the data points and what can be deduced from them.

Contact data like phone number and email address is not only helpful for correspondences and customer service, it is useful to create a customer friendly dunning process as well. But if you were the shopper, when would you share your correct contact data? Most likely, if you are given a good reason during the checkout process, e.g. to receive the confirmation of your order or to get information about the delivery status. Not only being transparent about data usage in the terms and conditions or data privacy statements, a short explanation in the checkout about what these data can be used for can enhance trust.

For getting the goods to the customer, some data points are obvious to share like the full name as well as the billing and delivery address. But how can these data help to offer good service? In combination with other data they can be used to identify returning customers even if other parameters are changing. If there is no historical data of a shopper available, additional data sources like credit bureaus can be requested to identify and score a shopper and thus achieve higher acceptance rates. Therefore, the name and address is the minimum requirement to get any result. Ratepay tested how the date of birth influenced the identification of unknown customers. Depending on the used data source the identification is up to 11 percentage points higher, if the date of birth is available, which also has a direct impact on acceptance rates.

And how about data points, which are independent from the shopper? The item description not only leads to a better customer service e.g., helping with return issue resolution. In combination, it can be used to prevent fraud as well. Some items are more likely to attract fraud than others, especially when they are easy to resell. Let’s assume there is a fraud attack concerning the newest iPhone. A merchant still wants to offer this article for genuine shoppers instead of blocking it completely. If the criminals always use the same IP address or use fake phone numbers, that start with the same numbers, it is possible to set up very specific rules for the pattern with a high accuracy and less impact on the acceptance rate. The same applies for device fingerprinting. It is an indicator for identity theft, if multiple “shoppers” use one device and in combination with other data points this pattern can be prevented.

It is obvious, a good mixture of data points is not only useful for merchants and payment companies, but as well for the shopper. It helps them to shop conveniently, have a satisfying experience and prevent identity theft at the same time. Still, merchants and payment companies will most likely face the challenge to build trust and convince shoppers to hand over their data.