How Fraud Experts Fight Fake Content in E-Commerce

Global disruption, adaptation, and constant reports of “fake news” may be prominent themes in 2020, but counterfeit content in e-commerce is as old as the digital marketplace itself. When left unchecked, scams and spam content have the power to do irreversible damage to a company’s reputation and growth—leaving merchants at the mercy of an internet where anyone can say and sell just about anything. 

An Inauthentic Ecosystem

According to Sift research, 50% of businesses will see increased content abuse over the course of the next year. With customer loyalty on the line, spam and scams are a daunting and pervasive problem that can directly impact growth. Fake content—once dominated by phishing emails and malware masquerading as pop-ups—has evolved into something much more scalable and sinister. 

Two-way marketplaces play host to fraudsters looking to scam savvy shoppers with sales that are too good to be true; dating apps have to defend users against catfishing and illicit offers. The sharing economy has even given rise to illegal hotel and transportation scams—all layered on top of the more traditional hacker rings organizing elaborate attacks and selling personal information on the dark web.

But misinformation enters the average consumer’s sphere much more frequently than they might expect in the form of fabricated product and service reviews. Those star-based ratings and the details they provide carry a lot of weight, with 85% of consumers trusting online reviews as much as personal recommendations from family and friends. It’s that baked-in belief, coupled with their versatility, that makes fake reviews an ideal vessel for fraud. Add in sellers willing to pay for that faith, and a profitable ecosystem of inauthenticity was born—leaving users with no concrete information about what they’re buying or who they’re buying it from.

Joining the Fight Against Content Fraud

In a recent virtual session at the KNOW Digital Forum, Kevin Lee, lead Trust and Safety Architect at Sift, shared insights and practical advice for businesses on how to effectively identify and stop fake content.

The impact of positive reviews and other legitimate, user-generated content, notes Lee, links directly to a company’s growth. From high search engine rankings to a brand’s overall credibility, customer engagement and feedback are highly influential when it comes to how consumers buy and behave. In fact, it is such a serious issue that retail monolith Amazon has sued over 1,000 of their sellers since 2015 for using fake reviews to boost business.   

Ultimately, Lee says, a company is responsible for the content it allows on its site. And because spam and scams can manifest in so many ways and in so many places, detecting them—especially before they’ve done any harm—requires a prevention strategy that’s as adaptable, flexible, and far-reaching as the fraud it’s meant to stop. Here’s what merchants need to focus on:

• There’s a not-so-underground market for content fraud. Much of it spawns from expected sources, with malware hidden in messages, or sellers on two-way marketplaces offering products that never arrive. Fake reviews are fruitful, too—often, gig workers will offer to post them for a small fee or free product, and use multiple IP addresses and manual creation to bolster the appearance of legitimacy. 
• Low-quality customer interactions cause poor engagement and churn. Even a small number of spammy or suspicious posts can quickly lead to trusted users spending less time on an app or website, fewer ads and offers getting clicked, and customer abandonment—all of which equal lower revenue.
• Users provide a lot of passive information well before they make a purchase or write a review. Where they’re coming from, when they landed on your site, how long they stayed—all of this data is available, and can help determine whether there’s a risk of content being fraudulent.
• That said, you need strong fraud analysis tools and real-time prevention in place to effectively stop content abuse. Equipping and scaling a team of human analysts is difficult and expensive; machine learning-based platforms, however, can provide unmatched accuracy, adaptability, and integrity to your trust and safety strategy—all critical capabilities in a fraud prevention solution, according to Gartner’s 2020 Market Guide for Online Fraud Detection.

Watch The War on Fake Content: Understanding the Nature of Fake Reviews for Savvier Fraud Prevention to explore these insights and other expert recommendations.