Two notable names from different business spectrums, Wayfair and Spotify, are aiming to keep customers happy through technology. While the former is a home retailer and the latter is an audio streaming service, they both focus on delivering personalized customer experiences.
These platform-based companies are now employing machine learning to do this and more. Aside from building around data and customer interactions, they now also offer curated products and content recommendations using the said method. Learn more below how machine learning works.
How They Are Doing It
In the recently concluded EmTech Digital 2022 conference, Wayfair and Spotify machine learning experts gave attendees an idea of how they are using technology to provide customers with one-of-a-kind experiences. Their target is to promote solid relationships with customers while increasing their profits.
Wayfair does it by having over 3,000 specialists working on the platform. This connects customers with suppliers in a marketplace with more than 14 million products on five different websites. On the other hand, Spotify does it by serving more than 400 million active users across 184 markets. Millions of creators on the platform have recorded a whopping 82 million music tracks and over 3 million podcasts.
While these two businesses handle it differently, they have a common denominator. This is the challenge of making on-point recommendations and customized experiences that boil down to scaling problems.
According to Tony Jebara, vice president of engineering and head of machine learning at Spotify, with the millions of content and users, determining value connections can be “multiplicative.” He added that recommendations of millions of choices to a user helps them go beyond what they could find on their own.
How Machine Learning Works for Wayfair
A digital-first retailer, Wayfair focuses on the home category. They understand that taste and style vary from customer to customer. This makes the technology even more beneficial as they can now offer more personalized customer experiences. This will give them a competitive edge, says Fiona Tan, Wayfair’s chief technology officer.
Tan added that Wayfair uses machine learning in the following areas:
- Advertising – a fully automated bidding process for online ad auctions
- Search – interprets what the customers search for and asks suppliers to give product information
- Supply chain – connects customers to nearby suppliers to reduce costs
She also added that the company has two rules in determining the use of automation. Firstly, to identify significant areas with large amounts of accessible data that they can use as insights. Secondly, to find problems with tolerance for uncertainty that they believe are more suitable for higher degrees of automation.
The company aims to balance the product choices, ensuring they are relevant to the customers. The ones that are already close will be boosted to encourage exploration.
How It Is for Spotify
Spotify is now aiming to provide a lifetime of content for its users through the use of machine learning. They want to go beyond finding and curating content to encourage users to explore and find new experiences. According to Jebara, search tools offer less diversity, so machine learning can help them discover new things.
Spotify has already been using machine learning techniques such as collaborative filtering. This is what predicts what a user will like. The new method is now improving to provide better recommendations and customization.
They get their data from user playlists, listening behaviors, track and podcast information, and other analytics. These will give them an idea of what they skip and like and how to understand their tastes better. Jebara believes that this personalization will get them to deliver a lifetime of better content.
And for other tech news and stories, read more here at Owner’s Mag!
