Published on February 14, 2014
YAHOO: Analytics – Ajay Sharma Bagavath Subramaniam Productivity Improvement Cases
P r o d u c t i vi t y T h r u A n a l yt i c s PRESENTED BY Ajay Sharma, Director Bagavath Subramaniam, Senior Principal Engineer February 8, 2014
Agenda About Yahoo! & It’s scale Search Primer Business Model BI Productivity Tools Demo Questions
Yahoo! Big Data Scale Yahoo is the most Visited Site on the Internet › › › › › 800M+ Unique Visitors per Month Billions of Page Views per Day Billions of Searches per Month Billions of Emails per Month Terabytes of Data per Day! And we crawl the Web › › › 100+ Billion Pages 5+ Trillion Links Petabytes of data Reading 100 Terabytes could be overwhelming Server – 10Gbps Std PC – 100Mbps ~ 11 days 1000 Std PC ~ 1 day ~ 15 mins
Search Primer Manages campaigns, creates ad listings, bids for keywords Types in a search query on Yahoo or affiliate site (aka the Publisher) Passes search query to the ad platform for servable ad listings Ad serving returns relevant & available ads matching the search query Shows ads returned by ad serving Clicks on Ad
Search Metrics Searches Searches Results Clicks Searches Results Clicks Raw terms that the user queries on Results are impressions of an ad. Click occurs when a user clicks on the ad
More Search Metrics Revenue per Search (RPS) $$$ Price Per Click Searches Coverage Click Yield Clicks $$$ Impressions Revenue Bidded Searches Now what do these mean?
Business Model Performance, Credit Summary Daily, Weekly, Monthly & Yearly Performance, Budget Headroom, AM performance, competitive analysis Daily, Weekly, Monthly & Yearly Performance, Feature Adoption Daily, Hourly, Weekly, Monthly & Yearly Daily, Weekly, Monthly & Yearly Competitive analysis, cross sell, upsell, performance Daily, Hourly, Weekly, Monthly & Yearly
Delivering Business Intelligence Reporting (KPIs, metrics) Dashboards Scorecards Automated Monitoring/Alerting (thresholds) Ad hoc query Statistical/Quantitative Analysis Data Mining Predictive Modeling
Analytical Productivity Tools Simplified everyday work Personalized Flexible Workflow oriented Organization aware Embedded Business Rules
C a s e St u dy I A u t o mated C l i ent E n g agem ent(AC E)
Why? Creates deck with embedded analytics ready to conduct business review with customers
Workflow for QBR Deck generation
ACE Architecture SSL Front End Layer YApache PHP Wrapper YUI3 (HTML5) PHP Power point Memcache Resources Service Layer Model Objects + Data Access Objects Mobstore API Client Spring Jersey PLSQL Client Solr Job Runner Oozie Mail Server Launcher JDBC IBATIS Data Layer Grid Interface Batch Server JAX Web Service Tomcat Middle Layer API Interface PDF Library HBASE Rest Server Database Layer (PLSQL APIs, Meta data, Data, Audit, Security) Apollo Grid S C H E D U L E R A D C E N T E R A P I S
C a s e St u dy I I S a l es D a s hboards
Why? How am I doing with respect to my quarterly goal? How much have I achieved so far and what’s the projection based on current run rate? How is my book performing compared to last week/month/quarter? How is my weekly/monthly/quarterly trend for the last year – Is it going down or up? Where am I losing money – which customer/account/vertical (for an AM/AE)? Where am I losing money – which AE/AM (for director)? Which of my accounts went offline ? What are the top reasons for offline accounts? Am I making use of the targeting options available? How am I doing when compared to my Industry? Which accounts are not utilizing the IO/budget? What are the over pacing accounts where I need customers to add more money?
Low Latency Dashboards to surface actionable insights for account managers and account executives every day Sponsored Search Sales Search Business Insights for Sponsored Search Advertising Sales Teams Dashboard
Q u e st ions? Ajay Sharma Director Bagavath Subramaniam Sr. Principal Engineer
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