Lucidworks Recognizes Innovative Digital Leaders in the Second Annual Lucidworks Connector Awards
The 2020 Connector Awards recognized Lucidworks customers Goop and Regeneron as leaders in Personalized Commerce and Knowledge Management.
At Lucidworks, we believe in honoring innovative leaders who solve modern enterprise challenges and deliver connected experiences for their users. Last year we created the Lucidworks Connector Awards to acknowledge organizations and people that drive personalized experiences that delight customers and empower employees.
Read about the 2019 winners, Nordstrom Rack | Hautelook and PwC here.
This year, we were thrilled to receive an influx of nominations for our 2020 categories, Personalized Commerce and Knowledge Management. Today we are proud to announce the winners: Goop and Regeneron.
Introducing the 2020 Lucidworks Connector Awards Winners
Personalized Commerce Connector |
Juan Paul Ramirez – CTO |
Goop was founded by Gwyneth Paltrow as a lifestyle brand that offers high quality content and curated wellness products. Juan Paul Ramirez, Goop CTO, leads his team in using Lucidworks Fusion to streamline merchandising control over their unique search engine.
Goop has a wide range of content including products, articles, podcasts, recipes and videos. The range and depth of their content, built up by Paltrow over decades, adds a layer of complexity to search. Goop leverages Fusion’s AI and machine learning capabilities to analyze on-site signals and map relationships between content to provide personalized recommendations to customers. For example, if a customer regularly searches for recipes, Goop can provide recommendations for new herbs and frying pans.
Goop has become a leader in the commerce and wellness space by creating a personalized, contextual experience for their consumers. With Lucidworks Fusion, Goop reduced their time to resolve search issues from weeks to minutes. Using signals from customers, including purchases, browsing behavior, queries, and preferences, Goop is able to quickly fine-tune search to provide relevant search results and recommendations without having to wait for help from IT. They’ve also achieved dramatic improvements in exit rates, product engagement, and conversion from product pages.
Knowledge Management Connector |
Abdul Shaik – Head of Data Platform Engineering |
Regeneron is a leading biotechnology company that creates pharmaceutical products for people with serious illnesses, such as cancer and infectious diseases.
Abdul Shaik, Head of Data Platform Engineering, uses Fusion to power search on Regeneron’s internal research & clinical development application and make it easy for employees to access publicly available COVID-19 data sets, research, and events. Shaik’s team uses AI and machine learning to implement self-learning capabilities within their app by leveraging signals to understand user intent and business context.
In addition to leveraging signals, Regeneron can expedite their data discovery for publicly available data sources with Fusion’s pipeline framework that accelerates the data ingestion and index process of over 60,000 COVID-19 related research documents and journals. Fusion automates the data acquisition and indexing steps and applies machine learning at the moment of data ingest to add deeper understanding and context to every data set. With Fusion, Regeneron can empower their scientists with the data they need, when they need it, by eliminating data silos and personalizing their knowledge discovery experiences.
Lucidworks Connector Awards 2021
Are you leveraging Fusion to empower customers and employees? Nominate your team for next year’s Lucidworks Connector Awards. Visit our webpage here to learn more. You could have the opportunity to present your submission to a team of leading analysts who are experts in their fields and who are deeply familiar with the latest technology trends in digital transformation and ecommerce.
Be sure to contact us today if you’d like to see how Lucidworks can help provide a connected experience for your users.
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