Kickdynamic Taps TigerGraph on Amazon Web Services (AWS) Cloud to Power Its Next-Generation Hyper-Personalized Marketing

REDWOOD CITY, CA – Aug. 14, 2019 – TigerGraph, the only scalable graph database for the enterprise, today announced that Kickdynamic has chosen TigerGraph’s technology to help its more than 200 global customers in fashion, retail, travel, and other sectors achieve maximum email personalization and relevancy.

Studies have shown that businesses able to develop content that’s highly relevant and personalized to each individual recipient will see increases in open and conversion rates. In addition, a Gartner survey showed that 38 percent of customers will stop doing business with a company because of poor marketing personalization efforts.

Kickdynamic is tapping into the power of TigerGraph’s native parallel graph database on AWS Cloud for its open time platform that hyper-personalizes email with dynamic, real-time content based on multiple factors, such as demographics, user preferences, product features, location and browsing, search and purchase history.

“At Kickdynamic we know that compelling, individualized experiences are the most effective way to create customer loyalty and drive revenue,” said Gabriele Corti, Chief Product Officer at Kickdynamic. “Having tried various other solutions, we found that TigerGraph offered the best combination of performance and advanced, real-time, analytical capabilities. TigerGraph’s scalable graph database will enhance our platform and enable us to continue to achieve our vision of delivering advanced personalization in email.”

As the digital era has given consumers unprecedented choices, all just a click away, simple recommendations such as “customers who bought this item also bought” or “these products are often bought together” are no longer enough. To foster brand loyalty, businesses must gain a more sophisticated understanding of the unique, varied, and complex characteristics of every customer and deliver, on the fly, offers and recommendations that truly speak to them.

A standard collaborative filtering algorithm, used by popular sites such as, creates a recommendation based on the buying behavior of other users delving only one or two levels or hops into the data. The first hop is from the customer to the product they are reviewing or have purchased. The second hop is from the product to other customers who have bought that product. The third hop is from these customers to other products they have bought over time that aren’t yet purchased by the customer. Simple next best offer recommendations — such as “Customers who viewed/bought this product, also bought (these other products)” or “Frequently bought together” are losing the competitive advantage and revenue to companies that leverage advanced technologies like Kickdynamic with more personalized and meaningful communications.

By using TigerGraph’s native parallel graph database on AWS Cloud, Kickdynamic is able to go 10 or more hops deeper and provide real-time deep link analytics that opens up vastly more information about a customer’s likes, needs, desires, and intent. This supports their advanced personalization capabilities that can display products that customers have browsed on site and live in email, automatically at open time.

Ted Baker, a luxury clothing retail company, works with Kickdynamic to offer live, automated, and personalized email to their customers. Kickdynamic enables the company to reduce its internal manual email build processes, increasing customer engagement and enhancing the performance of its email marketing by delivering relevant content in real time. Product feeds are used to fully automate the products displayed, including live pricing and CRM data to add personalization layers based on factors such as preference and browse data.

By leveraging the Kickdynamic partnership with TigerGraph, it will become possible to instantly understand the recipients’ profiles and deliver relevant recommendations showing products that are more likely to capture their interest, exploiting past onsite browsing behavior, similarities across products and users, and cross-user behavioral patterns to discover and extract similarities between users, products, or both. All in real time, on-demand using the latest data, the brand will continue to gain insights into their customers’ buying and browse behaviors over time to deliver highly relevant and engaging content.

“Kickdynamic is on the leading edge of marketing personalization and working with them is a vivid illustration of how our industry-leading graph database can improve customer engagement,” said Dr. Yu Xu, CEO of TigerGraph. “Working with London-based Kickdynamic is all the more gratifying because TigerGraph recently opened a new European headquarters in London to help support our rapid global growth.”

Helpful Links

About Kickdynamic

London-based Kickdynamic helps more than 200 brands achieve their email automation, personalization and relevant content goals. Compelling, individualized and exceptional email experiences are the most effective way to create loyal, engaged customers and drive revenue. The Kickdynamic platform provides a sophisticated suite of email enhancement tools that enable brands to automate and personalize pixel-perfect images live at email open. From one HTML, unlimited personalized versions can be automatically generated based on individual customer information and contextual cues including device, time, weather and location.

About TigerGraph

TigerGraph is the only scalable graph database for the enterprise. Based on the industry’s first Native and Parallel Graph technology, TigerGraph unleashes the power of interconnected data, offering organizations deeper insights and better outcomes. TigerGraph fulfills the true promise and benefits of the graph platform by tackling the toughest data challenges in real time, no matter how large or complex the dataset. TigerGraph’s proven technology supports applications such as fraud detection, customer 360, MDM, IoT, AI and machine learning to make sense of ever-changing big data, and is used by customers including Amgen, China Mobile, Intuit, VISA, Wish and Zillow. The company is headquartered in Redwood City, CA, and is backed by investors including the founders of Yahoo!, Walmart Labs, DCVC and Morado Ventures. Follow TigerGraph on Twitter at @TigerGraphDB or visit


Media Contact

Tanya Carlsson
Offleash PR for TigerGraph
[email protected]

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Dr. Jay Yu

Dr. Jay Yu | VP of Product and Innovation

Dr. Jay Yu is the VP of Product and Innovation at TigerGraph, responsible for driving product strategy and roadmap, as well as fostering innovation in graph database engine and graph solutions. He is a proven hands-on full-stack innovator, strategic thinker, leader, and evangelist for new technology and product, with 25+ years of industry experience ranging from highly scalable distributed database engine company (Teradata), B2B e-commerce services startup, to consumer-facing financial applications company (Intuit). He received his PhD from the University of Wisconsin - Madison, where he specialized in large scale parallel database systems

Todd Blaschka | COO

Todd Blaschka is a veteran in the enterprise software industry. He is passionate about creating entirely new segments in data, analytics and AI, with the distinction of establishing graph analytics as a Gartner Top 10 Data & Analytics trend two years in a row. By fervently focusing on critical industry and customer challenges, the companies under Todd's leadership have delivered significant quantifiable results to the largest brands in the world through channel and solution sales approach. Prior to TigerGraph, Todd led go to market and customer experience functions at Clustrix (acquired by MariaDB), Dataguise and IBM.