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Where Search Meets Science and Style Meets Savings: Nordstrom Rack's Journey to Data Science-Driven Digital Experience

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Where Search Meets Science and Style Meets Savings: Nordstrom Rack's Journey to Data Science-Driven Digital Experience

Nordstrom Rack | Hautelook curates and serves customers a wide selection of on-trend apparel, accessories, and shoes at an everyday savings of up to 75 percent off regular prices. With over a million visitors shopping across different platforms every day, and a realization that customers have become accustomed to robust and personalized search interactions, Nordstrom Rack | Hautelook launched an initiative over a year ago to provide data science-driven digital experiences to their customers.

In this session, we’ll discuss Nordstrom Rack | Hautelook’s journey of operationalizing a hefty strategy, optimizing a fickle infrastructure, and rallying troops around a single vision of building an expansible machine-learning driven product discovery engine.

The audience will learn about:

-The key technical challenges and outcomes that come with onboarding a solution
-The lessons learned of creating and executing operational design
-The use of Lucidworks Fusion to plug custom data science models into search and browse applications to understand user intent and deliver personalized experiences

Nordstrom Rack | Hautelook curates and serves customers a wide selection of on-trend apparel, accessories, and shoes at an everyday savings of up to 75 percent off regular prices. With over a million visitors shopping across different platforms every day, and a realization that customers have become accustomed to robust and personalized search interactions, Nordstrom Rack | Hautelook launched an initiative over a year ago to provide data science-driven digital experiences to their customers.

In this session, we’ll discuss Nordstrom Rack | Hautelook’s journey of operationalizing a hefty strategy, optimizing a fickle infrastructure, and rallying troops around a single vision of building an expansible machine-learning driven product discovery engine.

The audience will learn about:

-The key technical challenges and outcomes that come with onboarding a solution
-The lessons learned of creating and executing operational design
-The use of Lucidworks Fusion to plug custom data science models into search and browse applications to understand user intent and deliver personalized experiences

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Where Search Meets Science and Style Meets Savings: Nordstrom Rack's Journey to Data Science-Driven Digital Experience

  1. 1. 11 Where Search Meets Science and Style Meets Savings: Nordstrom Rack's Journey to Data Science-Driven Digital Experience Pankaj Andhale Senior Data Scientist Nordstrom Rack | Hautelook Peter Curran General Manger, Digital Commerce Lucidworks
  2. 2. 2 Outline • Challenges • Road to Relevance • Fusion • Results • Q & A
  3. 3. 3 Search Lenses Relevance ExperiencePerformance
  4. 4. 4 Search Quality Relevance Experience Performance Search Quality
  5. 5. 5 Challenge #1 Bad Customer Experience • Un-tuned index • Customer complaints • No dedicated search team
  6. 6. 6 Challenge #2 Data Driven Culture • No clear KPIs • No definition of success • No A/B testing of algorithms • No dashboards Search Visitors Non Search Visitors 1x 2x to 3x Conversion Rates (Industry) 1.67x
  7. 7. 7 Challenge #3 Speed & Flexibility • No synergy between Search and Merchandising • Simple tweaks required code changes and deployments • Slow to fix simple issues
  8. 8. 8 Challenge #4 Data Management & Processing at Scale • Processing customer behavior & leveraging in near real time • Infrastructure did not support
  9. 9. 99 Addressing Challenges
  10. 10. 10 • 1 Product Manager • 1 Engineering Manager • 1 Architect / Principal Engineer • 1 Solr Engineer • 1 QA • 1 Data Scientist Forming a Team Road to Relevance
  11. 11. 11 Fusion Platform Road to Relevance • Rapid prototyping • Testing • Deployment • Easy AB testing + • Signal aggregation • Versioning • Managed rules • Machine learning
  12. 12. 12 Measuring Quality Road to Relevance ● 42 KPIs and supporting metrics defined, audited, and tracked ● Unlocked power of Google Analytics ● New Search Dashboard automated time- consuming analysis ● Democratized search domain analysis ● AB testing on iOS
  13. 13. 13 Cross-Functional Feedback • 30+ Merch Team issues fixed in two weeks • Reciprocal sharing of knowledge led to quick understanding • Most new issues can now be resolved in the same day • Giant leap in business agility MerchandisersRoad to Relevance
  14. 14. 14 Signal Aggregation Road to Relevance • Query : red dress • Query : red valentino shoes
  15. 15. 15 Noteworthy Example of Relevance Tuning Road To Relevance • Deep dive into the query logs • Understanding the customer intent • Significant increase in the search count
  16. 16. 16 Conversion Rate Search vs. Non-Search Sessions Results 1.7 x
  17. 17. 17 Conversion Rate Search vs. Non-Search Sessions Results 1.7 x 2.9 x
  18. 18. 18 Search Quality https://opensourceconnections.com/blog/2018/11/19/an-introduction-to-search-quality/ Relevance Experience Performance Search Quality
  19. 19. 19 THANK YOU
  20. 20. 2020 Questions

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