Top 10 Use Cases: Real-Time Recommendations
By Bryce Merkl Sasaki
January 25, 2021 2 mins read
Discover how graph databases support sophisticated real-time recommendations of highly relevant products or content.
Explore: eBay • product recommendations • purchase history • real-time recommendations • Recommendation Engine • use case
Powering Recommendations with a Graph Database: Connect Buyer and Product Data
By Jocelyn Hoppa
August 20, 2018 4 mins read
Effective recommendations increase revenue and drive up average order value. But delivering highly relevant, real-time recommendations requires as much context as possible. Connecting the user to the perfect recommendation is an art. In this three-part series, we explore using recommendations… Read more →
Explore: customer relationship management • graph database • graph technology • nosql • personalized promotions • product recommendations • rdbms • real-time recommendations • Recommendations • relational database
Retail & Neo4j: Personalized Promotion & Product Recommendations
By Bryce Merkl Sasaki
November 6, 2017 7 mins read
Today’s retailers face a number of complex and emerging challenges. Thanks to lower overhead and higher volume, online behemoths like Amazon can deliver products faster and at a lower price, driving smaller retailers out of business. In order to compete,… Read more →
Explore: Connected Data • Cyber Monday • ecommerce • graph technology • personalized promotion • product recommendations • real-time recommendations • Recommendation Engine • Retail • Walmart
Content Is Still King: How We Use Neo4j at Packt Publishing
By Bryce Merkl Sasaki
April 8, 2016 8 mins read
‘Content is King,’ Bill Gates famously said twenty years ago, making his prediction that soon ‘anyone with a PC and a modem can publish whatever content they can create’. As time has gone by, this has only become more true.… Read more →
Explore: collaborative filtering • content marketing • cypher • metadata • Packt Publishing • product recommendations • Recommendation Engine • Stack Exchange API • stack overflow • tf-idf
How Walmart Uses Neo4j for Retail Competitive Advantage
By Bryce Merkl Sasaki
December 14, 2015 3 mins read
In a little over 50 years, Walmart grew from a small, family-owned business to become the world’s largest public corporation, with over 2 million employees and annual revenues of $470 billion. But Walmart didn’t just become the world’s largest retailer… Read more →
Explore: competitive advantage • ecommerce • graph database • neo4j • product recommendations • real-time recommendation • Recommendation Engine • retail competitive advantage • sustainable competitive advantage • Walmart