Using lwe solr lucene for e com - By Grant Ingersoll

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Using LWE/Solr/Lucene for eCom Grant Ingersoll, Lucid Imagination @gsingers Apache Solr and Lucene and their logos are trademarks of the Apache Software Foundation

Difference Makers Case Study 1: Relevance Matters Large Electronics Manufacturer Top selling product on page 10 for a search by product name Case Study 2: Don’t Overthink it Large Online Retailer Simply adding auto-suggest added millions to bottom line at very little cost Case Study 3: Test, Test, Test Amazon Recommendation System http://glinden.blogspot.com/2006/04/early-amazon-shopping-cart.html 3

Topics The Stack Knowing Users ,[object Object]

Extended FeaturesNot Just Search What’s Missing? What’s Next? 4

eCom Stack Choices 5 Apache Solr and Lucene and their logos are trademarks of the Apache Software Foundation

Users: Get to Know Them! Audience Poll: How many of you are developers? How many of the developers know what the top 10 queries are on your site? How many of the non-developers know? Your users represent 100% of your opportunity to sell your products ;-) Shouldn’t you know what they are searching for? 6

Search Analytics “If you can’t measure it, you can’t manage it” Attributed to Peter Drucker, however, see * Ultimately, it’s all about conversion May not be the best measure for judging search Is there One Right Answer on your Site or Multiple? Known Item search vs Keyword/Category 7 *http://edkless.com/2009/06/peter-drucker-and-time-sheets/

Useful Metrics Mean Reciprocal Rank or Precision @ 10 Known Item vs. Keyword/Category “Show me the money” -- Top Product Analysis Identity Search - If your top product is named X and someone searches for X, is X on the first page? Is it number 1? Is a top product underperforming as it relates to search? Top X Queries and Query Terms Zero Results and % of Zero Results Avg. # of facets/filters/spellchecks clicked per session Avg # of searches per user session Auto-suggest usage 8

Minimum Search Features High Quality Relevance for keyword and known item search P@10 or MRR close to 1 Sub-second response time under load All achievable in LWE/Solr/Lucene 9

Faceting LWE/Solr support faceting by: Field Date/Number Ranges Pivot (“what if” faceting) Hierarchical (via domain modeling) Dynamic (via Carrot^2) Single and multi-select faceting supported Facet by Function In Development https://issues.apache.org/jira/browse/SOLR-1581 http://wiki.apache.org/solr/SimpleFacetParameters 10

More Features Extensible Language Analysis Multilingual Support Synonyms Overrides on a per-word basis Pluggable Framework Frequent/Incremental Updates How often do you update your index? Near Real Time (IndexReader.open() ) Column Stride Fields (4.0) 11

Relevance Controls Function Queries Ratings/Reviews Margin/Inventory/Price/Location Can Sort by Functions …/solr/browse?q=ipod&bf=price Editorial Controls (QueryElevationComponent) Fine grained controls …/solr/elevate?q=YYYY&enableElevation=true Landing Pages (if done in search…) Implement: Docs with field that is filtered on or a separate index/core Editorial Controls Click Scoring (LWE only) Popularity based ranking 12

Beyond the Search Box Many eCom sites actually power all navigation by the search engine Many other tools in the Stack to help users discover content Auto Suggest Spell Checking More Like This Spatial 13

Complementary Tools Apache Mahout Recommendation Systems Crude Solr/Mahout Rec Integration at https://github.com/gsingers/ApacheCon2010 Classifiers/Clustering User Analysis, Content Analysis, etc. Social BazaarVoice, etc. Business Rules Engine Drools or others 14

What’s Missing? UI Controls for non-devs: Synonyms (LWE has UI/REST support) Facets (Field support in LWE) Relevance Control (LWE REST API Support) Business Rules Integration Deeper Taxonomy Support More performance reports (LWE has some) Facet Management tools Labels Sort order other than Count or Alphabetical Editorial facet control 15

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Using lwe solr lucene for e com - By Grant Ingersoll

1. Using LWE/Solr/Lucene for eCom Grant Ingersoll, Lucid Imagination @gsingers Apache Solr and Lucene and their logos are trademarks of the Apache Software Foundation

2. Difference Makers Case Study 1: Relevance Matters Large Electronics Manufacturer Top selling product on page 10 for a search by product name Case Study 2: Don’t Overthink it Large Online Retailer Simply adding auto-suggest added millions to bottom line at very little cost Case Study 3: Test, Test, Test Amazon Recommendation System http://glinden.blogspot.com/2006/04/early-amazon-shopping-cart.html 3

4. Minimum Features for eCom

5. Extended FeaturesNot Just Search What’s Missing? What’s Next? 4

6. eCom Stack Choices 5 Apache Solr and Lucene and their logos are trademarks of the Apache Software Foundation

7. Users: Get to Know Them! Audience Poll: How many of you are developers? How many of the developers know what the top 10 queries are on your site? How many of the non-developers know? Your users represent 100% of your opportunity to sell your products ;-) Shouldn’t you know what they are searching for? 6

8. Search Analytics “If you can’t measure it, you can’t manage it” Attributed to Peter Drucker, however, see * Ultimately, it’s all about conversion May not be the best measure for judging search Is there One Right Answer on your Site or Multiple? Known Item search vs Keyword/Category 7 *http://edkless.com/2009/06/peter-drucker-and-time-sheets/

9. Useful Metrics Mean Reciprocal Rank or Precision @ 10 Known Item vs. Keyword/Category “Show me the money” -- Top Product Analysis Identity Search - If your top product is named X and someone searches for X, is X on the first page? Is it number 1? Is a top product underperforming as it relates to search? Top X Queries and Query Terms Zero Results and % of Zero Results Avg. # of facets/filters/spellchecks clicked per session Avg # of searches per user session Auto-suggest usage 8

10. Minimum Search Features High Quality Relevance for keyword and known item search P@10 or MRR close to 1 Sub-second response time under load All achievable in LWE/Solr/Lucene 9

11. Faceting LWE/Solr support faceting by: Field Date/Number Ranges Pivot (“what if” faceting) Hierarchical (via domain modeling) Dynamic (via Carrot^2) Single and multi-select faceting supported Facet by Function In Development https://issues.apache.org/jira/browse/SOLR-1581 http://wiki.apache.org/solr/SimpleFacetParameters 10

12. More Features Extensible Language Analysis Multilingual Support Synonyms Overrides on a per-word basis Pluggable Framework Frequent/Incremental Updates How often do you update your index? Near Real Time (IndexReader.open() ) Column Stride Fields (4.0) 11

13. Relevance Controls Function Queries Ratings/Reviews Margin/Inventory/Price/Location Can Sort by Functions …/solr/browse?q=ipod&bf=price Editorial Controls (QueryElevationComponent) Fine grained controls …/solr/elevate?q=YYYY&enableElevation=true Landing Pages (if done in search…) Implement: Docs with field that is filtered on or a separate index/core Editorial Controls Click Scoring (LWE only) Popularity based ranking 12

14. Beyond the Search Box Many eCom sites actually power all navigation by the search engine Many other tools in the Stack to help users discover content Auto Suggest Spell Checking More Like This Spatial 13

15. Complementary Tools Apache Mahout Recommendation Systems Crude Solr/Mahout Rec Integration at https://github.com/gsingers/ApacheCon2010 Classifiers/Clustering User Analysis, Content Analysis, etc. Social BazaarVoice, etc. Business Rules Engine Drools or others 14

16. What’s Missing? UI Controls for non-devs: Synonyms (LWE has UI/REST support) Facets (Field support in LWE) Relevance Control (LWE REST API Support) Business Rules Integration Deeper Taxonomy Support More performance reports (LWE has some) Facet Management tools Labels Sort order other than Count or Alphabetical Editorial facet control 15

17. What’s Next? Some sample code and more discussion at http://www.lucidimagination.com/blog/2011/01/25/implementing-the-ecommerce-checklist-with-apache-solr-and-lucidworks/ 16

18. Resources Principles for Effective Search in E-Commerce Design http://lucene.li/2T http://www.lucidimagination.com/search/?q=ecommerce grant@lucidimagination.com @gsingers 17 http://www.lucidimagination.com

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Case 1: Don’t think relevance matters? This single result was costing lots of money every single dayCase 2: Think about how long it takes to add auto-suggest… How long to add NLP to search?Case 3: take a long term view, test hypotheses
Many things can go wrong between search and conversion that aren’t related to searchEstimate MRR or P@10 based on click stream analysis
Is a top product underperforming as it relates to search? In other words, is a user less likely to buy when searching for a top product versus other navigation options?Also, the usual performance metricsOthers?
http://localhost:8983/solr/browse?q=ipod&bf=price
All of these things are fairly easily built

Using lwe solr lucene for e com - By Grant Ingersoll

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Using lwe solr lucene for e com - By Grant Ingersoll

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