The League of Extraordinary Fraud Fighters
By Miguel Veloz /
6 Mar 2015
The night: A crisp San Francisco eve. Waves crash upon the Embarcadero while ferries slice their way through the harbor. The Bay Bridge provides a few last twinkles, illuminating the faces of the League of Extraordinary Fraud Fighters as they gather atop their tower in relative stealth. You’re welcome here, among a motley crew of rag-tag vigilantes holding forum deliberating on how best to beat villainous fraudsters using their most powerful weapon – The Sword of Sift. With flavorful falafel and a bevy of beers (or wine, for the fancier among our humble crowd) in-hand, so begins Sift Science’s latest Customer Meetup.
If you missed our event — or don’t live in the San Francisco Bay Area — we’re so sorry that we couldn’t meet and chat and hear from you on Tuesday. We at Sift Science consider ourselves very fortunate to have such an active community of customers, and strive to provide lots of value through engagement. Ten customer companies were represented, with one bringing 67% of their entire company! The viewpoints were invaluable and the variety of fraud that our guests face sparked much discussion. Amidst all of the great conversation and questions that arose, a key takeaway for everyone was realizing just how universal and diverse fraud is for so many websites. Our customers all have very different businesses, and leveraging data with machine learning offers a trainable, adaptable solution.
We appreciated the candid feedback that our guests provided. In regards to the Sift Science product, we heard that some things, like DeviceID, are extremely useful but not particularly intuitive. Evolving our product to better suit your needs and offer a personalized fraud tool is so important to our team. We hear you loud and clear: being able to send us labels that differentiate between various fraud use-cases would be very useful.
A special feature of the evening was a short presentation by our Product Designer, Tony Chu. Tony walked us through an exciting new product development that Sift Science users can expect in the coming months. Unfortunately, we’re not quite ready to announce these updates yet on the interwebs, but stay tuned! The reactions from our customers were really fantastic, with great questions asked and feedback or insights offered. The voices of our guests will definitely help to guide our roadmap and lead to an even stronger product!
One of the Sift Science features that work really well for our customers — and that might work well for you — is the Network Visualization data view in our console. Several even suggested that they’d like to be able to prioritize the connections highlighted. We brainstormed a few ideas for how to make our user pages even more useful –sticky navigation, bulk labeling capabilities, stronger signals to the top — and our product team is already hard at work weighing these possibilities. We also heard that many Sift Science customers trust our score accuracy and the information that our console provides. We love hearing this success, and want to make every part of Sift Science helpful and intuitive.
It all boils down to this: We love our customers, and hearing from you and facilitating engagement with other folks in the space are the best ways for us to make sure our products work best for you. Given the success of our past two successful meetups, we’d like to continue hosting these events on a quarterly basis, and are excited to invite all customers — new, old, and returning — to drop by. We hope to play a role in building an active community – A League of Extraordinary Fraud Fighters, if you will.
So what would you like to see from us? What discussion topics, presentations, or guests would be interesting to you?
We are so excited to continue learning from and growing with you. Sift on!
Miguel was Director of Account Management at Sift, and enjoys cooking, politics, reading, foreign languages, and all-night discussions on the nexus of art and pop culture. He's on a quest for the perfect London Fog. He graduated from Yale and worked in Google's Large Customer Sales division for several years.