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I’m always listening to music. At work, in the car, at the gym, right now, even. So, as you can imagine, I was intrigued when last week, the music streaming service Spotify rolled out another new playlist feature, called “Release Radar”. This special playlist takes a selection of the newest releases from a user’s favorite bands and compiles them in one convenient location. Spotify “takes stock of your entire listening history, then narrows the range of possible suggestions down to tracks that have been released in the last two to three weeks,” to form a playlist specific to each user. This is a very similar methodology to determining how the tracks for Spotify’s much lauded “Discover Weekly” playlists are selected, but the crucial difference is that “Discover Weekly” songs are picked based on a user’s recent listening history, whereas “Release Radar” takes a big picture approach based on a user’s entire listening history.
All of which is to say this: Spotify has shown all of us a glimpse of the future with this new playlist feature. How have they done this you might ask? Not just by offering a cool way to hear new music, but by making anticipation and personalization a key facet of their service.
The secret lies in the deep learning algorithms the music streaming giant uses to analyze data. These little bits of technology allow for Spotify to not only build a product that accurately anticipates each user’s tastes, but is also deliverable on a large scale. It seems so simple: take what users are actually listening to, and make it easier for them to listen to more music like that. But “Release Radar” and “Discover Weekly” have been embraced so openly because they are so unique. Sure, companies like Netflix and Amazon have “Just For You” menus, but they are not nearly as personalized as Spotify’s. This type of data driven approach must become the norm for all, as customers will slowly stop doing business with those companies that do not anticipate their needs.
Take contact centers as an example. Technology will be paramount in the industry, as it will better equip the human agents with the tools to provide excellent customer experiences if automation cannot resolve the issue. Customer feedback and user data must be the driving force behind customer service or those customers will go find someone else to do business with.
Over 1.7 billion people streamed their uniquely crafted “Discover Weekly” playlists in the first five months, and the numbers for “Release Radar” are likely to be much higher as the level of personalization is even more detailed. By using the vast amount of data they had collected on each subscriber’s listening habits, Spotify has made the act of listening to music, already a very personal endeavor, even more personal and completely effortless. They have set the industry standard for curation, and businesses in other fields must take notice of the effectiveness of this strategy.
This is the template that we in the customer engagement industry must follow as well. We must be able to use data to make informed decisions to meet customer needs when they reach out to contact centers. We at Humach have done that with the Humach Connect button, which draws upon a customer’s location, purchase history, call history, and other factors to help agents anticipate the needs of the customer before they even call, in addition to bypassing the telephony platform completely. Customers, including myself, will no longer settle for cookie cutter service interactions with companies. This time, it’s personal.
It’s time for you business to be proactive, not reactive. Make your move today.
