Search Analytics at Enterprise Search Summit Fall 2011
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The document discusses search analytics, its importance, and how it can enhance user experience through data collection, analysis, and reporting. It emphasizes the need for proper measurement to identify failures and improve search relevance, highlighting various analytics tools and methodologies. Additionally, it touches on the technological framework supporting search analytics, including software like Flume and HBase, advocating for their use in understanding and optimizing search functionalities.
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Search Analytics at Enterprise Search Summit Fall 2011
- 1. Search Analytics What ? Why ? How ? Otis Gospodneti ć – Sematext International @otisg ◦ @sematext ◦ sematext.com sematext.com/search-analytics
- 2. About Otis Gospodneti ć ASF Member : Lucene, Solr, Nutch, Mahout Author : Lucene in Action 1 & 2 Entrepreneur : Sematext , Simpy
- 3. Sematext Metrics 100% organic : no GMO, no VC 4 years old < 10 people 7 countries 3 timezones 2 continents > 100 customers
- 4. About Sematext Products & Services Consulting, Development, Tech Support: Search (Lucene, Solr, ElasticSearch...) Big Data (Hadoop, HBase, Voldemort...) Web Crawling (Nutch, Droids) Machine Learning (Mahout)
- 5. Agenda What is Search Analytics and why it matters Example reports and their value Optional: Search Analytics in the Cloud
- 6. Communication twitter.com/ sematext twitter.com/ otisg hash tags: # stsa or # stanalytics http://sematext.com/search-analytics/index.html Raise your hand ! otis @sematext.com
- 7. Why search users search providers search experience
- 8. Why Oh Why search providers search experience This search sucks! It takes 17 tries to find anything here! F!?@#$%^&?!? search users Cool, the latest search tweaks made our site really sticky! Awesome!
- 9. Fill in the Missing Piece Search Analytics Performance Monitoring Quality Assurance Tuning UI
- 10. Blind Leading the Blind
- 11. Analytics as Compass Search logs are your Map Search Analytics is your Compass
- 12. The Bottom Line Why Measure and monitor everything . Supports (re)design, navigation choices Helps with content acquisition & enhancement Improve search experience Mula
- 13. The Moment of Truth Question for the audience #1 What do you use for Search Analytics? a) Home grown stuff b) Google Analytics c) Omniture d) Webtrends e) Other f ) Nothing
- 14. Search Analytics Basics Collect : queries & clicks & interactions & ... Analyze : actions / xactions / conversions Output : reports – over time Output++ : feedback loop The means, not the goal Ongoing, not one-off remember this
- 15. Search vs. Web Analytics User intent and information needs vs. inferring Hand in hand Ideally you can relate data from both or even unify it
- 16. Report Types Failures vs. non-failures Actionable vs. non-actionable Trends vs. summaries
- 17. Failures vs. Non-Failures Zero hits Low CTR Low MRR High bounce rate Low conversion rate Deep paging Deep clicking High latency Query rate Query volume Top seen & clicked docs Top queries Terms per query Search sessions Search users Distinct queries
- 18. Value of Failure Fixes Zero hits Low CTR Low MRR High bounce rate Low conversion rate Deep paging Deep clicking High latency Re-search Findability Relevance Tuning Performance Tuning
- 19. Measure, then Fix If you can't measure , it you can't fix it!
- 22. Watching Latency
- 23. Search Analytics & Measuring If you can't measure it, you can't fix it! You can't measure it if you don't have Analytics
- 24. Actionable vs. Non-Actionable Zero hits Low CTR Low MRR High bounce rate Low conversion rate Deep paging Deep clicking High latency Query rate Query volume Top seen & clicked docs Top queries Terms per query Search sessions Search users Distinct queries
- 25. More Fixin' Query rate Query volume Search sessions Search users Top seen & clicked docs Top queries Terms per query Distinct queries Navigation & Design Results Shuffling Diversification Recommendations AutoComplete Search box size
- 26. Output++: Data is Power AutoComplete - $MM improvement Better DYM Spellchecker Related Searches Recommendations Relevance Feedback ...
- 27. Closing the Loop search users search providers search experience
- 28. Resources http://rosenfeldmedia.com/books/searchanalytics/ Search Analytics for Your Site Louis Rosenfeld Search Analytics What? Why? How? Search Analytics with Flume and HBase Search Analytics Business Value & NoSQL Backend http://blog.sematext.com/tag/analytics/
- 29. Key Take-aways Without Analytics you are blind If you can't measure it, you can't fix it Use Search Analytics to understand , measure and improve search Using Search Analytics means having a competitive advantage
- 30. Time permitting: Behind the scenes of Sematext Search Analytics Behind the Scenes
- 31. sematext.com blog.sematext.com @sematext @otisg [email_address] Want SA? Grab me or go to: sematext.com/search-analytics Hash tags: # stsa or # stanalytics Contact
- 32. What We've Built Search Analytics SaaS Numerous reports (e.g. query volume, rate, latency, term frequencies / comparisons, hit buckets, search origins, etc.) Trending over time Comparisons of time periods Top N reports Filter , slice and dice
- 34. Big Dreams SaaS Multitenant Large Scale – Massive Data Cloud
- 35. Storage Choices RDBMS: MySQL, PostgreSQL HDFS Hive HBase Cassandra
- 36. SaaS vs. In-House Question for the audience #2 SaaS vs in-house Search Analytics? a) SaaS b) in-house
- 41. Data Flow See Search Analytics with Flume and HBase http://blog.sematext.com/2010/10/16/search-analytics-hadoop-world-flume-hbase/
- 42. Data Collection See Search Analytics with Flume and HBase http://blog.sematext.com/2010/10/16/search-analytics-hadoop-world-flume-hbase/
- 43. Core Tech JavaScript Beacons Metric Capture Web App aka Receiver Flume Agents, Collectors, Sinks HBase MapReduce Aggregations Search Analytics Reporting Web App
- 44. What is Flume Distributed data/log collection service Scalable, configurable, extensible Centrally manageable, open source Agents get data from app, Collectors save it Abstractions: Source -> Decorator(s) -> Sink
- 45. What is HBase Scalable, reliable, distributed, column-oriented DB On top of HDFS MapReducable
- 47. Why Flume Reliable delivery e.g. queue msgs locally if destination unreachable Easy, centralized management via Web UI or console Good community, good progress, now @ASF But: more complex, more moving parts On Flume: slideshare.net/cloudera/inside-flume Alternatives: Kafka, Scribe...
- 48. Why HBase Scalable raw & aggregate data storage MapReduce data input Fast scans for time ranges, fast key lookups Easy storage and compute power expansion Good looking roadmap, community, progress
- 49. Open Sourcing 2 open-source projects: github.com/sematext/HBaseWD github.com/sematext/HBaseHUT See sematext.com/open-source/index.html Patches for Flume and HBase blog.sematext.com/tag/flume/
- 50. Challenges Data size. Solutions: Compression (4-5x smaller with lzo) Data pruning (variable levels) Query string distribution: very long-tail Lots of data to process, update, aggregate Young tools: Flume, HBase Poor IO on EC2 Hadoop distributions
- 51. sematext.com blog.sematext.com @sematext @otisg [email_address] Want SA? Grab me or go to: sematext.com/search-analytics Hash tags: # stsa or # stanalytics Contact