Building and delivering data-driven products at Nordstrom

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Building and delivering data-driven products at Nordstrom

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novo-nordisk-talk

Data Lab presentation to Novo Nordisk.

On Github Nordstrom / novo-nordisk-talk

Building and delivering data-driven products at Nordstrom

Elissa Brown - Data Scientist - @missmisslissErin Shellman - Data Scientist - @erinshellman

Building and delivering data-driven products at Nordstrom

Elissa Brown - Data Scientist - @missmisslissErin Shellman - Data Scientist - @erinshellman

The Nordstrom Data Lab Mission

Delighting customers through data-driven products.

Nordstrom Data Lab Timeline

Multidisciplinary Team

Our Powers Combined

The Nordstrom Data Ecosystem

There has been a shift in our thinking. A part of our resources are now more human curated...our engineers evolve the algorithm, and humans help us see if a suggested change is really an improvement.

- Scott HuffmanEngineering Director at Google

EASE

Emulate

Automate

Scale

Evaluate

Applications

Our Stylists Suggest Returns Fulfillment My Color Palette Segmento!

Stylists at Nordstrom

Our Stylists Suggest

Our Stylists Suggest is a recommendation engine that analyzes transactions in Nordstrom stores that were facilitated by a personal stylist.

How to Emulate a stylist?

Stylist-based Market Basket Analysis

How to Emulate a stylist?

Stylist-based Market Basket Analysis

How to Emulate a stylist?

Stylist-based Market Basket Analysis

How to Emulate a stylist?

Stylist-based Market Basket Analysis

How to Emulate a stylist?

Stylist-based Market Basket Analysis

Evaluate

Test internally with a light-weight prototype

Compare to incumbent

Automate

Evaluate

Introducing Recommendo

Recommendo 2.0 Preview Tool

Lessons Learned

  • Quick prototyping is the fastest way to internal advocacy.
  • We don't always need a complicated solution.
  • Play to your differentiating strengths.
  • Cloud == Speed
We ask our people in the stores to use good judgment. The ultimate objective is taking care of the customer. You really can't have a rule book that takes into account every scenario. We're just going to stand behind our merchandise.

Returns at Nordstrom

Returns at Nordstrom

Returns Applications

  • Help customers find products in the best size for them to prevent returns
  • Serving better recommendations by incorporating knowledge about return patterns
  • Email outreach for high-risk customers

Fulfillment Forecasting

Each store is a special snowflake!

Evaluation station!

Color is Data

Color Extraction

Color Extraction

Color Extraction

Color Extraction

Color Patterns

Colors of the Season

Swimwear Trends by City

Customer Color Fingerprints

Empower our Customers with Data

What are the colors I buy?

What are the colors I should try?

Precise Color Match

Now what?

Segmento! Segmentation as a service.

Wrap Up

  • It Takes a Village
  • Experience >> Data
  • KISS
  • Ship It!
  • EASE!!

Acknowledgements

Sara Hogenson, Paul Payne and the Nordstrom Innovation Lab

Scott Jones, Prashanth Nair, Jim Steck, Abid Saifee and the Advanced Analytics, Personalization, and Mobile Teams, @nordysanda

Thank You!

Questions? Ask ds@nordstrom.com

This Presentationhttp://nordstrom.github.io/novo-nordisk-talk/

Nordstrom Technology is Hiringtechcareers.nordstrom.com

Nordstrom Shoeboxwww.nordstromshoebox.com

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