The Internet is a virtual community, empowering anyone in the online world to quickly communicate, create, share, discover, and transact. But any virtual community, relationship, or transaction comes with uncertainty and risk.
As the famous New Yorker cartoon says, “On the Internet, nobody knows you’re a dog.” This is the uncertainty that retailers face with every transaction. Online, a shopper could be an 80-year-old Bostonian buying his granddaughter a graduation trip to Hawaii. Or, this “customer” could be a fraudster, exploiting that grandfather’s stolen credit card details.
Faced with a limited window of time to decide whether a customer is legitimate, how do you decide who to trust? Many merchants rely on security checks and verifications to weed out bad users. But the unintended effect is that your good users have a less-than-optimal customer experience, jumping through extra hoops to make a purchase. And for retailers, this can translate into lower conversion and lost sales, and may deter someone from making a repeat visit to your site.
These unintended consequences are a “trust tax”, reflecting the extra costs that merchants pay when they don’t have a trusted relationship with the users who visit their website.
Developing trust
In both the online and offline worlds, trust develops slowly, over time. Think of a bartender. The first few times you visit a particular watering hole, you hand over your credit card to start a tab. But if you become a regular at that bar, you build trust with the bartender and she eventually stops asking for your card. She knows you’re good for it.
It’s the same online. If you’re a repeat buyer at an online store, you may use your saved info to zoom through checkout without filling out all your credit card details. You’re familiar, so the retailer deems you sufficiently trustworthy to skip a step.
But the first time you visit that site, the company probably views you – by default – as an unknown quantity, a risk. You’re guilty until proven innocent. Needing to test your trustworthiness, the retailer may throw up a barrier like CAPTCHA, 3D Secure (Mastercard and Visa’s authentication step), or other identity checks.
That’s when you start paying the trust tax. Faced with extra form fields or steps, a good customer may pause, reconsider, and even abandon their cart completely. In fact, 3D Secure has been shown to ding conversion rates by as much as 43% in the U.S. That’s the trust tax at work.
Reducing your trust tax
How do you reduce your trust tax – or even eliminate it completely? It starts with having the intelligence to know who’s visiting your site, and then extending good customers your trust – even if you haven’t seen them before – in the form of a smooth, frictionless buying experience.
But how do you know who your good customers are if they haven’t bought from you before? Big data and machine learning can help. Taken in combination, across a large user base, large-scale machine learning can use those patterns to predict – before they take any action on your site – whether someone is more likely to be buying their granddaughter a trip, or just pretending to be that generous grandfather. That means you have the intel and insights to make smarter decisions, even tailoring your checkout experience to ask for less information.
The Internet operates at unmatched speed and scale. While there may be countless dogs pretending to be people and fraudsters pretending to be grandfathers online, the reality is that most users visiting your site are attempting to complete entirely legitimate actions and transactions. They deserve your trust. Do you have the technology required to enable this trust?