How does eBay’s use of analytics most significantly contribute to the company’s growing competitive advantage in the marketplace?
eBay offers one of the most robust and comprehensive worldwide databases in the market thanks to its over 160 million active purchasers. We are making concerted efforts not just to utilize our data to explain performance, but also to actively apply real-time machine learning methodologies in order to make the most of the diversity, velocity, and amount of data that we handle on a daily basis. We make it a point to constantly improve our interactions with each and every one of our customers at each and every touchpoint in order to develop experiences that are fully dynamic, relevant, and engaging across all of our channels, including outbound marketing and interactions with our contact center.
Your team makes extensive use of data in order to get a profound comprehension of customers and consumer DNA. In order to do this, you have merged a significant amount of traditional data with data that is less traditional. Could you provide some instances of how this was done and what the effect has been – both on the customers and the business of eBay?
The more facets of a consumer’s activity that you are able to bring together, the more effective the analysis will become, which will ultimately result in an experience that is both more relevant and more motivating. Transaction data is the fundamental starting point, but individual data, both historical and in real-time, from search strings, clickstream paths, contact-center interactions, buyer-seller communications, physical location, off-site internet interactions, type of device used, outbound marketing responses, and even local weather conditions can all play a role. Transaction data is the fundamental starting point. Running the biggest marketplace in the world with a strategy that is more focused on the needs of customers has allowed eBay to continue to generate major positive commercial impacts.
The research firm Gartner predicts that by the end of the year 2022, $2 billion worth of online sales will have been done using a mobile device. What distinguishes a customer who shops from their mobile device from one who shops from their laptop or personal computer, in your experience?
The distinction between mobile and desktop computing is getting less clear all the time. Even though mobile users tend to have shorter and more frequent interactions, mobile touch points are still responsible for 50% of our company’s gross product sales. For instance, every ten seconds, a woman’s handbag is bought in the United States using a mobile device on the online marketplace eBay.
Many retailers are “sitting” on a mountain of customer data, but they are not making effective use of it to change the game. What leads you to believe that is the case?
The pursuit of data collection for the sake of data alone will not lead to success. To be able to act on data involves a mix of active business thinking, analytical thinking, and technological thinking. This is necessary in order to be able to make consistently sound judgments based on analysis and to do so at scale. The vast majority of companies still treat data as if it were the responsibility of a single department inside the company, rather than as an activity that is completely incorporated into the process of making continuous decisions.
Where do you think there will be the most potential in the not-too-distant future for data to play a revolutionary role, either at eBay or more generally within the retail industry?
eBay is capitalizing on two major industry trends—real-time processing and deep learning and artificial intelligence—in order to accelerate its development. In order to provide our consumers, both buyers and sellers, with the highest possible level of relevance, we need to conduct analyses in real time. This is because the volume, variety, and velocity of data are continuing to explode at an exponential rate. And of course, the number of data sources, in conjunction with the ongoing advancements in computing power, are enabling rich applications in the world of machine-assisted or machine-learned applications. Some examples of these applications include suggested pricing on products, the most relevant personalized deals, or identifying and merchandising inspirational products that engage customers at different points in the course of their shopping journey.
What do you consider to be the single most important piece of guidance that you can provide to businesses who are working to maximize the value of their data?
It is not solely the responsibility of the IT department to deal with data; rather, an analytical mindset should permeate every department and facet of the business. It is unacceptable to turn to data simply at set intervals in order to explain your outcomes; rather, data must become an essential component of both the real-time operational and strategic decision-making processes and competitive advantage.
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