Machine learning is powering a new class of
personalization solutions that are no longer held back
by modern and legacy challenges. Through greater
scalability, automation, and intelligence, these solutions
can incorporate behavioral data and inferred preferences
to deliver highly relevant, enticing experiences that are
truly tailored to an individual customer—rather than
generic segments of people. Machine learning can do this
by helping to process customer data and then selecting
the right algorithms to dynamically present the most
relevant products or content to each and every customer
at the right time.
Machine learning solutions are easier to manage and
integrate into your existing workflow, allowing you to
address real-time customer needs by creating more
relevant experiences at scale. They can also address
common problems like "popularity bias" (merely showing
a customer the most popular products) and "cold start"
(where no user history exists), helping customers find
more relevant items and discover new products that are
relevant to their interests—even when those products are
not particularly popular or information on that customer
is limited.
In the next section, we'll show you how you can leverage
AWS machine learning to deliver on the promise of
personalization through the use of specific AWS services.
Overcoming personalization challenges
through machine learning
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