Beyond Accuracy: Embracing Serendipity and Novelty in Recommendations for Long Term User Retention
<h2>A Bond of Trust Formed at a Coffee Shop</h2>
<p>You’re sitting in a coffee shop, savoring your favorite coffee variation (a cappuccino, <em>of course</em>) and engrossed in conversation with a friend. As the conversation flows, the topic shifts to the latest gripping TV series that you both have been hooked on. The shared excitement creates a bond of trust, to the extent that your friend eagerly turns to you and asks, “What should I watch next? Do you have any recommendations?”</p>
<p>At that moment, you become the curator of their entertainment experience. You feel a sense of responsibility to preserve their trust and provide suggestions that are guaranteed to captivate them. Additionally, you’re excited at the opportunity to, perhaps, introduce them to a slightly new genre or storyline they hadn’t explored before.</p>
<p><strong>But what factors influence your decision-making process as you consider the perfect recommendations for your friend?</strong></p>
<h1>What makes a good recommendation?</h1>
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<p>First, you tap into your understanding of your friend’s tastes and interests. You recall their fondness for intricate plot twists and dark humor; furthermore, you know they enjoyed crime dramas like “<em>Sherlock</em>” and psychological thrillers like “<em>Black Mirror</em>.” Armed with this knowledge, you navigate your mental library of TV shows.</p>
<p><a href="https://towardsdatascience.com/beyond-accuracy-embracing-serendipity-and-novelty-in-recommendations-for-long-term-user-retention-701a23b1cb34"><strong>Learn More</strong></a></p>