How Spotify Failed a Push Notification Junkie
Although I try not to, I can’t help but frequently (ok, very frequently) refer to Spotify’s brilliant digital music service throughout different aspects of my work, occasionally to the annoyance of my colleagues. I am such a fan that Spotify has often been at the center of any blog that I’ve written, or the example I’ve cited when speaking at top-tier marketing events.
Today, sadly, I’m not boasting about my love for Spotify, but instead airing a bit of disgruntled disappointment from the perspective of a push notification junkie.
Over the last few years, Spotify has presented me with personalized interactions that have earned my loyalty and turned me into a brand advocate. Additionally, these efforts have served as excellent examples of not only great marketing, but also the value of applied artificial intelligence marketing (AIM).
One such interaction came when Spotify recommended a new version of a song from an artist that I’m particularly keen on. Please note that I listen to this song daily, so I’m a pretty big fan. This was an extremely simple marketing activity, but it was extremely effective. It showed that Spotify was perfectly aware of my musical interests and that they care about providing me with many more hours of happy listening.
- Daniel listens to a song religiously.
- Spotify notes that Daniel is religiously listening to this particular song.
- Artist releases new song on Spotify.
- Spotify alerts Daniel about the new song.
- Daniel listens to new song religiously.
- The madness repeats.
Great, right? Everyone wins in this scenario. I get to listen to more music from an artist I enjoy, the artist’s song gets more plays (more money), and Spotify maintains my engagement and that of other listeners who are fans of the artist.
Unfortunately, the process only works as well as the strategy behind it. And recently, the strategy Spotify put behind this process left me feeling sad and lonely.
Strategy Fail: 10 Long Days
Ten days ago, an artist similar to the one I mentioned above released a new album. I’ve loved this artist for years, and have listened to their songs on repeat many times. But it took ten days for me to discover this, by chance, on my own. Ten days!
A few things immediately came to my mind:
- How dare they!? Spotify KNOWS I like this artist and that I would want to know about this new album immediately. And, yet, they kept it from me!
- Ten days would have been more than enough time for me to have listened to, learned, and bragged to my musical friends about how I “knew about it first”. It also would have been plenty of time to memorize all of the lyrics to that 38 minutes of sweet musical bliss.
- What determines the “who” of who should be notified, and why didn’t I make the cut? There must be some sort of AIM technology in place, and a strategy behind it, that failed to include me in this important notification.
- I’ve learned to know, understand, and rely on these notifications as part of what I expect from Spotify. The brand I love and promote shamelessly let me down.
My Ah-Ha Moment
Eventually, I did calm down and realized that this probably wasn’t a personal vendetta being carried out against me by Spotify. That’s when it became clear that I not only like these notifications, but that I have grown to expect them, and even to rely on them. In fact, I expect them to the point where I’m disgruntled and disappointed if I don’t receive them.
In today’s digital age, consumers are demanding more personalized content than ever before. They want the content brands serve them to be hyper-relevant. They expect brands and marketers to understand their requirements, before they are even aware of them.
For example, I’ve purchased enough books by author Paolo Coelho on Amazon that the retail giant should know to send me a notification whenever he releases a new book, just as Spotify knows to do the same with artists. Achieving this level of customer insight and understanding at scale is only possible with artificial intelligence marketing. Only with a smart machine, aligned with human goals and a strong strategy, can customers be truly understood and treated as individuals.
Robust AIM Surgically Targets Push Notifications
AIM solutions allow brands to gather the most relevant and robust data pertaining to customers, and analyze that data to provide the best, most insightful information for marketers to make decisions. The technology allows marketers to bridge the divide between data science and marketing campaign execution, simply and succinctly, without additional efforts on the part of the marketing team.
Marketers can use AIM to develop key marketing aspects like keyword searches, social profiles, and other online data that allow them to create smarter, more effective notifications, which will likely result in more conversions and more loyal customers.
It’s a tough world for marketers. To cut through the noise of today’s cluttered marketplace, they must produce the right content at the right time and deliver it to the right people in a manner that is relevant, personal, and engaging. To achieve this lofty goal, marketers must leverage consumer data (like the data Spotify has about my musical preferences) to create strategies that deliver such highly effective content.
There is far too much data for any human (or team of humans, even) to compile, analyze, and apply without the help of AIM solutions and machine learning. The increased availability of AIM technology means that companies of all sizes, not just major enterprises like Spotify and Amazon, can send push notifications to the right customers, at the right time, with the right content. It also means that customers like me are accustomed to receiving this level of service. If your brand doesn’t provide this type of personalization, or if the strategy behind it fails to deliver to the right people, the consequences can be dire.
In fact, your biggest advocate may even write a disgruntled and disappointed blog post about it.
Want to learn how Emarsys can help you avoid your own push notification fails? Head here.