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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
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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
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01Concept Structured Search Under the Hood
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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
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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