What Is The Biggest Challenge For Fraud Detection API SiftScience?
15 Oct 2014
I’m spending more time reaching out directly to API providers, in an effort to better understand what they are up to. A couple weeks ago, I asked Sarfaraz Rydhan (@safoo) from the Fraud Detection API platform SiftScience, what is the biggest challenge you face in attracting developers to your system?
In many cases, the biggest challenge is developers needing context into the business and operations side of the companies they work for. We offer a machine learning powered fraud detection product to help internet companies in many verticals fight fraud. In an e-commerce integration, for example, a developer may need to know about how users interact with the store, when a customer's credit card is charged, how order information is sent to the warehouse for fulfillment, how operations analysts work within the e-commerce system.
Context--something that is so important, and is often lost in translation, or forgotten entirely when APIs are purely an IT or developer led initiative. As a developer I can easily see the many uses of an API, but articulating to someone who is actually living within one of these use-case scenarios, is very difficult—something that takes a lot of practice.
You can see SiftScience working to provide context to its users via its website, blog, twitter, and other tutorials and resources. As API providers, this is why we provide essential storytelling building blocks like a blog, tutorials, and other resources—to provide the critical context someone needs to understand the value that our APIs deliver.
Are you providing enugh context for your users?