IronPlanet, a leading online marketplace for selling and buying used equipment and other durable assets, is using machine learning and rich data in order to optimize used heavy equipment sales for their clients.
“in the context of IronPlanet, machine learning is about creating artificial intelligence in a market-place business,” says Ken Calhoon, Vice President, Data Analytics and Machine Learning, IronPlanet. Calhoon was hired into this position in January of this year; he is responsible for increasing the company’s analytics and artificial intelligence efforts, further expanding its advanced, data-driven technology platform.
In this role, Calhoon is applying business and data analytic expertise to improve online and onsite event performance identifying key data-based performance drivers across IronPlanet’s marketplaces and delivering ever-improving equipment recommendations to both buyers and sellers.
In simple terms, this can mean deciding when to sell a piece of equipment and how to position it in order to get the most money by using predictive analysis models and data.
“IronPlanet is really in a unique position to do this, since they have 17 years of really rich data, including equipment pricing and bidders’ behaviours during an auction event,” says Calhoon. “Plus, all of our predictive models work within a closed loop system. We know what the end result will be. The equipment will be sold. Plus, we know all of the variables. This leads to very accurate and actionable predictive models.”
Machine learning equals better price
Wit this technology, IronPlanet can better manage its auctions and better coach the equipment seller in order to get the best price for that equipment. The technology works in real time, so that changes can be made even during an auction event; the company can focus marketing efforts to help present items on sight or to push equipment to potential buyers, improving chances of getting a better price.
This information doesn’t only benefit the seller, but also the buyer. The same data can be used to determine when prices are likely to be low and when there might be oversupply of certain equipment types.
“Using machine learning and data in this way is a quantum leap for IronPlanet and for equipment sales,” says Calhoon. “If you look at eBay, people went from making purchases on the online marketplace as a novelty to using it as a serious buying tool. We are going to see a similar change in the heavy equipment industry.”
Calhoon has a business background and worked for eBay from 2000-2007; during that time, online sales for the company went from 431 million to 7.7 billion.
“I wish eBay had some of the abilities and procedures that IronPlanet has. IronPlanet has a lot going for it—the company’s buyer protection program, its inspection program, and the intermediation of payments between buyer and seller does a lot to create trust. It is one thing for people to buy toys from an online marketplace, but machines cost 100,000s dollars, and people trust IronPlanet with their payments. The seller doesn’t receive the money until the buyer receives the equipment. Its great. Plus, IronPlanet has a technology platform that is superior to any other. I am very excited to be working for the company in this capacity.