Deep Data At Macys v1.0

O C T O B E R 1 3 - 1 6 , 2 0 1 6 • AU S T I N , T X

Deep Data at MacysSearching Hierarchical Documents for eCommerce Merchandising

Denis Kamotsky, Macys.comEugene Steinberg, Grid Dynamics

Peter Gazaryan, Macys.com

3

01Introductions

Denis Kamotsky

Eugene Steinberg

Peter Gazaryan

4

02The Macys Story1858 Entrepreneur R.H. Macy opens R.H. Macy & Company, a small dry goods store.

1902 R.H. Macy & Co. moves uptown to Herald Square and shortens its name to Macy’s.

1924 Macy’s employees march from 145th Street to 34th Street to celebrate Thanksgiving, which sparks an annual tradition.

1976 Macy’s sponsors the first annual Macy’s Fireworks, now a 4th of July tradition.

1994 Federated Department Stores, the largest operator of department stores, acquires Macy’s.

1998 Macys.com is launched and operates out of New York and San Francisco.

2006 Macy’s expands to over 800 locations across the U.S

5

03The Macys.com Story

1997 MCOM operates out of San Francisco, California and Brooklyn, New York.

1998 MCOM is officially launched.2001 New York offices moves from Brooklyn to 1440 Broadway in Manhattan.

2001 Macy’s By Mail catalogue business shuts down, making macys.com the sole provider.

2010 We reach one billion dollars in annual sales volume.2013 Macys.com launches Keyword Search running on Apache Solr.

2013 We reach two billion dollars in annual sales volume.

6

01History of Search Engine at Macys.com

2015Dec 2012 Aug Dec 2013 Aug Dec 2014 Aug Dec

Merchandising Management Tool becomes available to the Users

3/2013

Solr-Based Keyword Search Engine goes live on macys.com

4/2013

Solr-Based Type-Ahead autocomplete functionality goes

live on macys.com9/2013

Legacy Keyword Search Engine is

retired

10/2013

Management of the Category Browse functionality becomes

available in the Saturn Tool3/2014

Category Browse is fully migrated to Solr on macys.com

8/2014

Intra-day SKU availability updates go live

5/2014

Dynamic grouping and ungrouping of

Product Collections is live

on macys.com1/2015

Solr Re-Platform effort begins

12/2011

7

01Solr Delivers Resultssession conversion increase attributed to migration to new Solr-based Search engine

28%

customers clicking on the ungrouped collection convert higher6%

macys.com traffic is Solr-Powered Keyword Search and Category Browse queries

8%increased conversion in type-ahead autocomplete sessions

35%

8

01Types of Retail

Boutique

Mall

Big Box

Specialty

Department

9

01Types of E-Retail

Inventory volume

Cura

tion

10

01Merchandising

11

01Great Expectations

Mary the Shopper Alice the Merchandizer

12

01Dreaded “Relevancy Tuning”

One size doesn’t fit all, even if you can stretch it

13

01Customer facing featuresQuality•Natural relevance•Data quality•Concept search

Refinement•Range, hierarchical facets•Sorting, grouping•Guided navigation

Usability• Input methods•Presentation and productivity•Device form factors

Targeting•Geography, demographics•Personalization•Collaborative shopping

14

01Structured Catalog

15

01Structured Catalog and the Quest of Precise Filtration: Part 1

16

01Structured Catalog and the Quest of Precise Filtration: Part 2

17

01Structured Catalog and the Quest of Precise Filtration: Part 3

Hybrid ApproachMulti-Paradigmatic Information Retrieval

19

01Concept Search and Controlled Precision Reduction

20

01Concept Structured Search Under the Hood

21

01Merchandiser facing featuresCuration• Rule-driven results• Product categorization• Date and time-based campaigns

Bias• Coarse natural scoring• Metric-driven boosting• Context-based placement

Comprehensiveness• Omnichannel data• Real-time availability• Accurate pricing

Referring• Cross-sells, up-sells,

recommendations• Predictive search• “Did you mean”, “do not carry”

suggestions

22

01Dynamic Grouping and Ungrouping

23

01Dynamic Grouping and Ungrouping: Under The Hoodcatalog = SELECT * FROM sku JOIN product JOIN collection

SEARCH "DKNY" FROM catalog GROUP BY collection.id

WHEN ALL(product.brand="DKNY")

SEARCH "white cup" FROM catalog GROUP BY collection.id

WHEN COUNT(product.id)>collection.threshold

SEARCH ”dinnerware" FROM catalog GROUP BY collection.id

WHEN NOT EXISTS(product.id)

24

01Tiered Natural Scoring

25

01Rule Driven Query Rewriting

26

01Make The Magic of Macys!

Inspiring Story

o Great traditionso Versatility of the

business modelo Merchandising as a

key differentiator

Genuine Innovation

o High Precision Concept Search

o Controlled Precision Reduction

o Tiered Natural Scoringo … and much more

Challenging projects ahead

o Omnichannel integration and scalability

o Natural language comprehension

o Merchandising automation

o PersonalizationTechnical challenges hazard

Thank you!

Q&A