Data Infused Product Design and Insights at LinkedIn

Data Infused Product Design & Insightsat LinkedInYael GartenSenior Data Scientist at LinkedIn,Team Lead for Mobile Data AnalyticsBig Data Innovation Summit, Boston September 13-14, 2012

Our mission: Connect the world’sprofessionals to make them more productiveand successful 2

Whatever you do, wherever you are 3

LinkedIn at a Glance• Founded in 2003• 175M+ members• 2 new signups per second• Executives from all Fortune 500 companies• 80% are “decision makers”• Average Household income in US: $86,000• ~4B annual people searches• Over 200 countries & territories• 17 different languages 4

Your Professional Identity Amazing dataset that we can slice and dice. By seniority, by job function – we can ask many interesting questions. 5

So what data do we have?175M+ professional profiles 6 6

What does the Data Science team atLinkedIn do with the data?• Product and Business Insights• Build Data Products• Extract Insights we Share Externally 7

da·ta noun pl but singular or pl in constr, often attributiveˈdā-tə, ˈda- also ˈdä-Information in numerical form that can be digitally transmitted orprocessed Source : http://www.merriam-webster.com Normalized Data =Web Logs = Data Information Parse, Normalize, Standardize From data to  Information

Knowledge: What’s going on?

If you can’t measureit, you can’t fix it.Measure everything.Know thyself: What’s going on?In the form of reporting, knowing the numbers, understanding usage ofproducts, patterns in the data, segments of users, tracking the growth andhealth of the ecosystem. 10

Insights: what can we improve?

Rethinking our Mobile App: what do people on thispage? Where do they go next? How many drop off? What is the stickiest product? What works, what doesn’t? 12

At what times in the day are people using differentdevices? Desktop usage iPad device accessing linkedin.com via browser Hours of the day 13

data information  knowledge  insights  wisdomWisdom: What’s the next needlemover?

Strategic Analyses:Using data to drive the business.• What is the value of an action that a user takes on the site?• What early behavior on the site is predictive of future engagement?• What is the value of a user?• What is mobile’s impact on social actions?• How does mobile usage impact desktop site engagement? 15

What is Data Science?Using (multiple) data elements in clever ways to solveiterative or auxiliary data problems that when combinedsolve a data problem that might otherwise be intractable.What makes a data scientist?Data Scientist = Curiosity + Intuition + Product & BusinessSense + Data gathering + Standardization+ Statistics+ Modeling + Visualization +Communication analytics & data science 16

Data Products on your LinkedIn homepage 18

Alumni Data Product 19

Our Newest Data Product : Skills 20

How do we do it? Extract 21

Skills: Assigning Skills to People 22

Skills: Who are the Experts? Have Hadoop as an inferred skill 23

Standardized data is the key to building compellingproducts Hadoop skill displays +43% y/y growth 24

Revenue improvementHard Worker Attentive to detail

Data Stories: Growing and ShrinkingIndustries

Where did all the people go from the collapsedfinancial institutions in 2008?

Fun stuff: CEO Names 35

If your name is Chip, you are likely in sales! 36

The 10 Most attractive start ups to Bay AreaEngineers 37

The Power of Aggregation Before employees worked at Yahoo! (169) Google (96) Oracle (78) Microsoft (72) IBM (43) Before employees worked at Google(475) Microsoft (448) LinkedIn (169) Apple, Inc. (154) ebay (133) 38

Market Research Insights through polls 39

Insights: Data Stories 40

Big Data that scales.What Technologies do we use? 41

Some of our Homegrown Solutions 42

It’s all about the people who do end-to-end datascience 43

Our partners to make it all happen• Product and Design: use data to influence the design of the product, and user experience & interaction• Marketing: build models to predict members’ propensity to act on an email campaign "call to action". When is the best time to message that user and what does it depend on?• Business Operations: e.g. How is transition to mobile impacting ads, subscription upsells• Executive team: on strategic questions• Engineering: understanding how data is tracked and implemented• Data Services: how do we build tools &infrastructure to democratize the data?Above all – maintaining the mindset of a data-drivencompany. 44

Questions? ygarten@linkedin.com

Yael Gartenygarten@linkedin.com

Data Infused Product Design and Insights at LinkedIn

by Yael Garten on Sep 19, 2012

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