MCommerce revenue is predicted to hit $415 billion in 2016. The use of smartphones for B2C transactions has grown exponentially, and it’s been amazing to see mobile’s growing role in the percentage of card-not-present (CNP) transactions. Unfortunately, a growing number of mobile transactions has shown a larger number of fraud via phone. Read how TireBuyer and Under Armour became successful at fraud prevention.
As a professional data buyer at Whitepages, there are a number of things I look for when researching and evaluating a new data source for one of our products. The specifics may vary based on the type of product, data source, or use case, but there tend to be consistent characteristics I always want to see. Many of these traits are things I have learned over the years through countless conversations, evaluations, contract negotiations and integrations. If your business is looking into sourcing data through vendors, then there are a few things you need to know.
Join us for this Bootstrap Tutorial to learn the secret recipe behind spam detection. These days spam is everywhere – it’s in your breakfast (egg and Spam), it’s in your Python (spam, ham, and eggs), but above all, it’s on your phone.
Media headlines on incredibly savvy and frightening phone scams were unavoidable this year. Over $350 million is lost in phone scams every year, as estimated by the Consumer Union. Although, others estimate it’s closer to $8.4 billion with $3 billion stolen from senior citizens alone. A look at 2015 shows the top four fraudulent phone scams of the year.
While IP telephony technology saves businesses and consumers money on their Telco costs; it allows for naughty numbers to emerge from VoIP. Businesses with customer support departments, call centers, and inbound sales and marketing programs will continue to lose revenue from lost employee productivity due to spam calls. Using phone data, businesses can discover insights and take action based on known phone behavior and patterns to block and filter spam calls.
Whitepages Pro now provides call centers an even more effective and efficient way to optimize the customer experience using Cisco systems with our industry leading phone identity data. We are excited to announce two new Cisco applications that empower call centers to improve workforce productivity and the customer experience. We’ve jointly developed two pre-built integrations with Cisco certified partner Cloverhound, making them simple to add into your call center environment.
In order to protect and satisfy our customers, we focus on both the quality and security of our data. We are pleased to announce three new product enhancements that make it easier for companies to implement, use, and manage Whitepages Pro users to fit their unique security requirements: Single Sign On, Concurrent Login Block, & IP Designated Access.
What can you do about the customers that weren’t fraudsters but had their orders delayed or rejected? Well, they might not return after having a bad experience. Being able to approve those flagged transactions faster with confidence will save you time and money. The right identity data can keep you from insulting your customers.
Jack is always challenging himself to be uncomfortable, to break from routine. He says this gives him the creative edge he needs to stay fresh and relevant. While I may not take this to the extreme Jack does, I completely buy into the fact that our fraud strategy has to continuously evolve with emerging trends. As the sources of fraud shift and change the data points that effectively capture them will as well. The data we analyze has to stay relevant for us to be successful. This may not win us any Grammys here at GameStop, but I know the great experience we provide will continue to win over our customers.
You’ve seen the fraud statistics, but how do those stats potentially impact your business? Give us a couple of numbers and our fraud calculator will show you how fraud could be affecting you. See the potential impact of fraud on your business – from the number of good orders being rejected to the average amount of time employees spend reviewing flagged orders.