Personalize the customer experience with recommendations that grow revenue

Build a recommendation engine that uses various sources of data in a timely and efficient manner to enable recommendations that convert. This solution uses transaction, demographics, clickstream, digital journey and marketing analytics data to provide a 360-view of the customer that powers personalized recommendations that pay off.
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Content-Based Recommenders

Solution Accelerator - How to build: Recommendation engines

How to Build an AI Recommendations Engine to Drive Stronger Personalization

Benefits and business value

Solution Accelerator - How to build: Recommendation engines benefits icon 1

Achieve unprecedented customer-centricity

Process massive volumes of highly detailed and frequently changing customer data to understand users

Solution Accelerator - How to build: Recommendation engines benefits icon 2

Gain a 360-view

Identify and stitch together all customer touchpoints in one place to drive accurate and precise recommendations

Solution Accelerator - How to build: Recommendation engines benefits icon 3

Boost customer value

Apt and accurate recommendations increase customer basket size, loyalty and revenue

Reference architecture

Solution Accelerator - How to build: Recommendation engines diagram

Additional assets

recommendation engines customer starbucks

recommendation engines customer dollar shave club
recommendation engines apache spark

implicit recommendation engines

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