Ebay is perhaps the best example of a tech and a retail company. Long before we heard the tired examples of Uber and Airbnb innovatively matching supply and demand, eBay was bringing sellers and buyers together using its auction platform.
So it’s no surprise that its use of big data analytics is more advanced than some of its competitors in the retail sector. Indeed, it believes the insights gained from this have the power to humble even the most stubborn of CEOs and change the industry forever.
“Tech companies in general are more ahead of the curve in terms of processes and culture [for analytics] as opposed to a guy coming in with a big salary and just hoping for the best,” Davide Cervellin, head of EU analytics at eBay, told Big Data World in London.
The next big thing
Like the rest of retail, mobile changed everything for eBay. Whereas previously customers were chained to desks and computers, they could now shop anywhere at any time. Not only did this transition change their behaviour, it also meant eBay had a lot more data it could work with, such as location.
“Before things were separate: people were offline and online,” he said. “Companies know where you are and can deliver you a better service. I’m not talking about the creepy stuff.
“Companies need to use this wisdom and give you a better service from information you allow them to use. For companies like eBay where we can sell you everything, we know more about you. You can give a tailored service that tries to anticipate your needs.”
Whereas mobile was the last big revolution, the Internet of Things (IoT) and big data is the next. Retailers can predict customer needs and retain and acquire new clients.
Social media is a treasure trove of data in this respect as every customer can recommend a product and every post is an opportunity to sell something, making it far more valuable than print or television advertising and allowing for a more personalised experience.
“One thing I can never stress enough is post-purchase,” said Cervellin.” In the era of social media, this can cost you a lot because they’re going to shout about it and the CEO will ask questions. A happy customer is the cheapest marketing channel you can have.”
Big Data culture
As a tech company, eBay had the natural advantage of being online.
“We used this advantage to try and leverage our unique selling proposition against traditional channels,” he added, noting that others would have to implement the correct hardware, software and processes.
Machine Learning, he argued, would be the only way to process the data quick enough and individual teams would have to be given ownership of the project so they could accept responsibility and deliver insights to the people that make the ultimate decision.
Organisations would need to figure out a basic need, then analyse the data against trends before making data-based decisions
“You need software and tools but you also need people to see the value of the questions,” he declared, adding that any executive at eBay needed to spend some time in the analytics department if they wanted to progress to a senior level.
“We have ownership, accountability and the ability to vet or stop investments because of the quality of what we do. We make sure whatever business case we approve, we have an expectation model.
“It allows us to make decisions with confidence because we have a model of reference. If the decision is good, then good. If it’s bad, we learn something.”
Traditional brick and mortar retailers have long been investing in ecommerce platforms to compete with their online rivals and have taken steps to gain more of this ‘online’ data in the ‘offline’ world.
This includes free Wi-Fi, companion applications and beacons to track a customer’s journey round the store and to offer personalised offers and information.
eBay itself has worked with physical retailers, most notably through a partnership with Argos, and Cervellin spoke of a pilot it held with upmarket fashion retailer Kate Spade Saturday in New York.
A ‘shoppable window’ was installed outside and allowed customers to browse the collection using a giant tablet. They could see the clothes on another person and enable custom backgrounds, such as Paris, to envisage the outfit.
The result was that items were purchased even at 3am, but there were other purchases that Cervellin speculated wouldn’t have happened otherwise.
“This is probably an indication that the future of retail is going to change,” he prophesised. “Perhaps [stores] are going to move from less front end [display] to more storage.
“All the things we can do today are measurable and therefore we have more opportunities, not problems.”