Personalisation is music to my ears
Real-time data enables businesses to personalise their services and better understand the customer at every stage of their journey. How personalisation is understood and developed across business functions will vary from brand to brand, but, for me, one of the best examples is Spotify.
?Spotify uses machine learning to analyse my listening behaviour and then group me with others who have similar tastes. It then recommends any tunes that the group has been listening to that are not in my playlists. Spotify also analyses a song’s beat, its musical key and loudness, and aligns them against my musical preferences. Even the home screen uses a ML algorithm to provide me with music recommendations in real-time.?
?As Spotify clearly demonstrates, when you leverage all your data across systems and touch points, you can create a more comprehensive view of your customer that builds your brand and drives business growth.?
If you’re looking to unlock the power of data to better understand your customers, check out how we do it at Cloudera: https://bit.ly/3hZMBH6
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3 年Love this. On top of the power that this historical listening trend uncovers, session-based recommendations show another way to reveal users' preferences. Recently listened, or recently purchased songs tend to have more of an impact on my daily listening habits. This model could be great for the content provider too as a user could log in anonymously or incognito and still gain insights from the provider's recommendation engine with little to no historical data! Cloudera Fast Forward Labs produced a great report on it https://session-based-recommenders.fastforwardlabs.com/