How Shippo balances positive experiences with unrivaled fraud protection
Customer Company Size
SME
Country
- Worldwide
- United States
Product
- Shippo API
Tech Stack
- Machine Learning
- API Integration
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Machine Learning
- Application Infrastructure & Middleware - API Integration & Management
Applicable Industries
- E-Commerce
- Retail
Applicable Functions
- Sales & Marketing
- Business Operation
Use Cases
- Fraud Detection
Services
- Software Design & Engineering Services
About The Customer
Shippo is a B2B shipping API that empowers businesses to ship orders through a global network of carriers. Founded in 2013, Shippo’s users include platforms, marketplaces, warehouses, and e-commerce businesses. Through Shippo, a business can easily print shipping labels and track orders. The company is focused on ensuring a positive business experience. In order to keep the flow as seamless as possible, Shippo doesn’t charge for individual shipping labels. Rather, every user is only invoiced after they exceed a certain order threshold. To sign up for Shippo, a user just needs to provide a credit card number – that won’t get charged until that first invoice is sent – and email address.
The Challenge
Shippo, a B2B shipping API provider, was facing a significant challenge with fraud. The company's business model, which allows users to create multiple shipping labels before having to pay, made it a target for fraudsters. The majority of the fraud fell into two categories: users who sign up with a fake email address and use a stolen credit card number, and users who create labels, hit the threshold, and then create a new account to avoid paying their invoices. In both cases, Shippo lost money – either from chargebacks from the accounts with stolen credit card numbers or lost revenue from the unpaid invoices. The company needed a solution that could preemptively identify account abuse and prevent users with stolen credentials from purchasing.
The Solution
Shippo turned to Sift to solve its fraud problem. The company was able to integrate with Sift in just a few hours, and the whole process was smooth and relatively effortless. Shippo began by sending Sift as much historical data as possible and relying on the machine learning technology to make sense of this dense information. Using Sift, Shippo could quickly separate out suspicious users from legitimate ones, and focus their energies on validating accounts and orders. Sift effectively caught fraudsters and was particularly valuable for identifying bad users at the account-creation stage. Shippo no longer had to wait until they saw a chargeback or a pile-up of invoices before spotting malicious users.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Improving Production Line Efficiency with Ethernet Micro RTU Controller
Moxa was asked to provide a connectivity solution for one of the world's leading cosmetics companies. This multinational corporation, with retail presence in 130 countries, 23 global braches, and over 66,000 employees, sought to improve the efficiency of their production process by migrating from manual monitoring to an automatic productivity monitoring system. The production line was being monitored by ABB Real-TPI, a factory information system that offers data collection and analysis to improve plant efficiency. Due to software limitations, the customer needed an OPC server and a corresponding I/O solution to collect data from additional sensor devices for the Real-TPI system. The goal is to enable the factory information system to more thoroughly collect data from every corner of the production line. This will improve its ability to measure Overall Equipment Effectiveness (OEE) and translate into increased production efficiencies. System Requirements • Instant status updates while still consuming minimal bandwidth to relieve strain on limited factory networks • Interoperable with ABB Real-TPI • Small form factor appropriate for deployment where space is scarce • Remote software management and configuration to simplify operations
Case Study
Digital Retail Security Solutions
Sennco wanted to help its retail customers increase sales and profits by developing an innovative alarm system as opposed to conventional connected alarms that are permanently tethered to display products. These traditional security systems were cumbersome and intrusive to the customer shopping experience. Additionally, they provided no useful data or analytics.
Case Study
How Sirqul’s IoT Platform is Crafting Carrefour’s New In-Store Experiences
Carrefour Taiwan’s goal is to be completely digital by end of 2018. Out-dated manual methods for analysis and assumptions limited Carrefour’s ability to change the customer experience and were void of real-time decision-making capabilities. Rather than relying solely on sales data, assumptions, and disparate systems, Carrefour Taiwan’s CEO led an initiative to find a connected IoT solution that could give the team the ability to make real-time changes and more informed decisions. Prior to implementing, Carrefour struggled to address their conversion rates and did not have the proper insights into the customer decision-making process nor how to make an immediate impact without losing customer confidence.
Case Study
Ensures Cold Milk in Your Supermarket
As of 2014, AK-Centralen has over 1,500 Danish supermarkets equipped, and utilizes 16 operators, and is open 24 hours a day, 365 days a year. AK-Centralen needed the ability to monitor the cooling alarms from around the country, 24 hours a day, 365 days a year. Each and every time the door to a milk cooler or a freezer does not close properly, an alarm goes off on a computer screen in a control building in southwestern Odense. This type of alarm will go off approximately 140,000 times per year, equating to roughly 400 alarms in a 24-hour period. Should an alarm go off, then there is only a limited amount of time to act before dairy products or frozen pizza must be disposed of, and this type of waste can quickly start to cost a supermarket a great deal of money.
Case Study
Supermarket Energy Savings
The client had previously deployed a one-meter-per-store monitoring program. Given the manner in which energy consumption changes with external temperature, hour of the day, day of week and month of year, a single meter solution lacked the ability to detect the difference between a true problem and a changing store environment. Most importantly, a single meter solution could never identify root cause of energy consumption changes. This approach never reduced the number of truck-rolls or man-hours required to find and resolve issues.
