Minneapolis Solr Meetup - May 28, 2014: eCommerce Search with Apache Solr

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eCommerce Search with Apache Solr

Grant IngersollCTO, LucidWorks

Twitter: @gsingers

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Tales from the trenches

• The case of the missing data

• The power of suggestion

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Topics

• Solr powered commerce– Companies– Features

• Relevance, relevance, relevance

• Demo

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Solr Powers Leading eCommerce and Consumer Sites

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Basic Features for eCommerce

• High quality OOTB relevance• Facets

– Range, Term/Category, Hierarchical, Pivot• Highlighting• Did you mean?• Boosting/Blocking/Landing Pages• Easy scale

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Advanced Features

• Spatial– Local– Route finding– Open Hours, etc.

• Function Queries– Inventory, Margin

• Stats Component– Missing data– Bounds, etc.

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Tips and Tricks

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Look Before You Leap

• Before undertaking any relevance tuning, you need to define what “better search” means to you

• Once determined, many ways to test/measure

• Once tested, many ways to fix

http://www.betternetworker.com/files/useruploads/16675/leap.jpg

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Understand your…

• Domain– Types of documents– Languages present– Document structures,

metadata and other features– Lexical resources: jargon,

synonyms, abbreviations...– Relationships between

documents

• Users– Sophistication/Expertise– Search and Discovery needs– Known Item vs. Keyword

• Tolerance for Pain– Managers– Business Interests– Release cycles– Obsession in finding the one

true relevance model (hint, it doesn’t exist)

– “explain() blindness”

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Known Item vs. Keyword

eCommerce search often has a split between known item and keyword search

You probably have more “wiggle” room for relevancy on keyword search

E.g. What should be the top result for a search on “women’s shoes”?

Known Item should have best matches at the top More in a moment

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Debugging

• Check the analysis (more in the next slide)• Check for data quality issues• Check your query constructs (slop, boosts, etc.)

• Try alternate query representations• (exact match)^100 OR (sloppy phrase match)^50 OR (OR query)

• Use Lucene’s explain() or Solr’s &debugQuery

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Signal Processing for Search and Discovery

• Signals power modern relevance– Clicks, conversions, sharing, history, signatures

• LucidWorks 5 makes it easy to capture and leverage signals– Recommendations, analytics, discovery

• Simplifies your data workflow• Simplify your operational footprint

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Solr Powered Signal Processing

• Use Case: eCommerce

• Data: – Product catalog (~1.2m items)– Click data (~3.9M clicks)

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Metadata

• http://www.lucidworks.com

• [email protected]• @gsingers

• Lucene/Solr Revolution – Washington DC, Nov 11-14– http://www.lucenerevolution.org