Adjusting Anti-Fraud Measures To Hit Revenue Goals
Analyze data better
Learn how to break down historical holiday data
Gain better insights
Find out how fraud fluctuates throughout the holiday season
Sell more & grow
See how adjusting rules to reflect variations can drive accuracy & revenue
The winter holiday season is widely recognised as one of the biggest online shopping periods of the year. Ecommerce revenue from the upcoming holiday season is predicted to grow 13% over 2017. For merchants, it’s an incredible opportunity to bolster annual revenue over the course of a month or two, and to dramatically grow their customer base. But managing the influx in traffic and shoppers is no easy task.
With large order volumes, merchants need to make sure their websites can accommodate heavy traffic without crashing. Similarly, fraud operations must prepare to review massive amounts of transactions. Without proper preparation, fraud systems can lead to fulfillment delays, false declines, and costly chargebacks. Reviewing data from previous years and past performance is crucial to forecasting and ensuring preparedness. Once shopping and fraud trends have been identified, fraud operations can be automated to reach better decisions more quickly.
Analysis of Riskified data from previous holiday seasons reveals that shopping behavior and fraud trends are not consistent throughout the holiday season. In fact, the data suggests that the holiday season is comprised of 4 ‘sub-seasons’, each with its unique consumer preferences and fraud trends.
In this guide, we’ll explain how eCommerce merchants can identify and determine what their own holiday ‘sub-seasons’ may be, in order to make the most of the end of year online sales.