tdwi exec 16 case study: linkedin voices of the member – a scalable analytics platform to create...
TRANSCRIPT
Case Study: LinkedIn Voices of the Member – A Scalable Analytics Platform to Create a
Customer-First Environment
Feb 2, 2016
Weidong ZhangManager of Data & Analytics
Chi-Yi KuanDirector of Business Analytics
Agenda
§ Introduction of LinkedIn business § Introduction of Voices: a home-grown advanced analytics
platform to listen to our members § Overview of end-to-end technologies that power Voices
platform § Case Study: how we build a member first environment &
what we are working towards
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Who are we?
www.linkedin.com/in/chiyikuan
Chi-Yi Kuan
• Director, Business Analytics & Data Mining • Big data evangelist and practitioner
www.linkedin.com/in/weidongzhang1
Weidong Zhang
• Manager, Data & Analytics • Build big data and analytics products
Create economic opportunity for every member of the
global workforce
Our vision
Create economic opportunity
Realize your dream job
Find work Be great at what you do
LinkedIn’s BIG data
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Customer Care Tickets 2015-05-30
NPS – feedback 2015-06-03
In-app review 2015-06-03
App store review 2015-06-06
WHAT ARE PEOPLE SAYING? 380+ million members = a lot of data
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The impact of our Voices analytics platform
Developed game-changing solutions to drive Voice of Member impact
Improved analytics efficiency with unstructured data by 20X
Drove end-to-end technological integration on big data and embedding NLP solutions
Piloting operational solutions to scale advanced analytics impact for broader organization
Voices - A tool to listen to our members on what they are talking about LinkedIn and our products
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Member “Voices” Internal & External
VOMC Transform Member Experiences
How does Voices alleviate data wrangling pain points?
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Member info
• Identity • Behavior • Social
Social data
Customer feedback
• Customer service • Group updates • Network updates
Survey results
Relevance solution
Topic mining
Classification engine
What’s trending
Products
Sentiments
Value Propositions
PYMK Group
Home Page Mobile Inbox
Identity Network
Hire Market Sell
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Trending Insights
§ Multi-channel, automatic intelligent solutions to provide trending information and help drive business actions
Machine Generated
Topics
Influencer/Top Executive Posts
Product Launch/ PR Events, etc.
What’s trending
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LinkedIn Hadoop Ecosystem
HDFS
Map-Reduce Spark Tez
Pig Hive Scalding
YARN AZK
AB
AN
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3 Major Design Principles for Voices Platform
Scalability Availability Easy to Use
Process Platform
Data Systems
Application Framework
Kafka, Hadoop, Spark Gobblin
Elasticsearch, NoSql Phoenix, Elasticsearch, Highcharts
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E2E Technologies that power Voices platform to achieve game-changing solutions
Case Study: LinkedIn’s customer support has evolved into an intelligence platform…
Scaling to have a broader impact across LinkedIn
▪ GCO cases ▪ Issue resolution ▪ Support focused
▪ Internal data (GCO, surveys, site feedback)
▪ App review ▪ LI.com ▪ Social data
▪ Product insight ▪ Member insight ▪ Launch tracking
▪ Social sentiment ▪ Brand tracking ▪ Viral mentions
Reactive Multi-channel Intelligent Predictive
Support Feedback Insights Anticipation
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…breaks down into sentiment and drivers…
4
(For LI data ) deep dive into MLC segmentation…
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…geographic locations…
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…and audience segmentation…
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…generates automatic reporting, alerts and escalations…
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…and close the feedback loop with support and PR solutions
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This is what the future could look like From the first time we pick up an isolated comment…
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Machine determines if there is significant reach…
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…and whether it is a trending topic…
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