OS3: The Village 1. Articulate
the core business you will scale up ﬁrst 2. Identify critical steps to scale that business 3. (Hyper)grow an organization to execute it 4. Finance for hypergrowth and future growth
OS3: Articulating the Core Business
Goals for the core business: 1. Create continued growth 2. Generate growing revenue 3. Build competitive advantage 4. Grow strategic assets for later opportunities
Viral Growth Engine Continue viral
engine improvements to drive member growth and critical mass within professional context Example products: Reg. optimization, New User Experience, In-Box, Outlook Integration, SEO, Address Book Tablestakes Professional Identity ecosystem Establish leading identity ecosystem by building upon unique database of 60M+ members Example products: Profile improvements/game dynamics, SEO, Search, APIs, Mobile Professional Insights & Knowledge Sharing Be the essential source for professional shared knowledge and business intelligence Example products: NUS, Sharing tools, Groups V2, Inapps, Outlook & Twitter Integration GamechangersValue Firm Foundation Improve and scale site resilience & reliability, development productivity, data reliability, API’s Measurements: uptime, load time, developer activity, Underlined: New focus in 2010 Data Targeting & analytics WVMP, MyStats Matching PYMK Warehousing Mining Global Monetization Leverage unique business model to monetize assets while adding value to members on a global basis Example products: Online Jobs, Recruiter, Premium subs, Display Ads, Self-serve Ads, Business Pages Strategic Stack
Strategic Stack Security Addressbook bcard
Skills Code Modularity Proﬁle - Engagement Apps / InApps Productivity Tools APIs Career Center Distributed Computing Rec Engine / Intelligence Salary Data Reliability / Scale Engine / WVMP Feature APIs Mobile Reg Optimization / NUX Business Pages PYMK International - Languages SEO Address Book Proﬁle - Data Inbox / Comm Core Search NUS / Sharing Groups Standardization A/B Testing Platform Online Jobs Subs Recruiter Payment Platforms DirectAds Display Support CS Tools Core Strategic Venture
OS3: Organization • Your organization
has to change fundamentally • The right CEO • Key executives for critical areas • Core mission, culture, and values to enable rapid distributed scaling • An HR function that can hypergrow • Necessary processes to allow large groups to work together • Navigate necessary changes among founders and early employees • Robust reporting to allow business not only to learn, but also to plan
People/Recruiting/Hiring ● Best people produce
best outcomes ● Need to keep bar high in the hiring/recruiting process ● Need to understand our limitations and bring outside expertise where needed ● Need to be flexible in our resource allocation (it is okay/desirable to move around the organization to apply key personnel to key projects) ● Onboarding/Ongoing Training/Mentoring are key.
Why technologists want to work
at Linkedin ● Having a positive/lasting impact on the world by developing products that create economic opportunities for people on a global basis. ● Building systems that scale and perform is paramount (think 10X). ● Data drives our solutions: Searching, querying, analysis of this data in real-time, near- real time, or batch creates value for our users, and our paying customers. ● The business models (Subscription, Corporations, Advertising) are a diverse source of revenue that require real value propositions, and technical excellence in delivery. ● Combining speed of execution with quality solutions, while still pushing the envelope on new/improved features requires engineering skill sets that are unheard of in traditional enterprise computing, and are hard to find even in the Internet. ● Engineers will constantly learn/use new technologies to create leading edge solutions. ● Great engineers want to work with great engineers. ● Constant improvement requires new talent/additional expertise to solve new/difficult challenges. ● When you come to work here, you will, by definition, have a large impact. ~ 150 technologists today ● Access to the senior leadership is real, actual, and actionable. CEO->VP->Director- >Manager->Engineer
What do we want? ●
Scrum vs. Waterfall: not the question; want best quality in timely fashion; good outcomes depend on good engineers + good engineering practices (AND function required here) ● Prioritize the list of Infrastructure + Product features merge sorted: We apply resources against that list, and the result is 2 clear choices, either add more people or cut the line higher so that some things don’t get done (ideally there is no distinction between features and infrastructure in our shop) ● Will have multiple serving data centers running: ETA likely > = 1 year ● Architecture: we will tease apart dependencies for our 180 subsystems so that we can have SLA’s for each one that we can trust and adhere to. All calling services must be resilient to failure of called services. (Service oriented architecture) ● The Data scaling concern demands a solution: Examples: Comm, DWH, volume of members, search index. ● Reminder: We have scaled this most excellent service successfully to this point. Now we need to go to the next level. Think 10X and 100X. How would we solve for that?
Release Process Gap – Changes
Needed ● The Current Process – What we do today ● Testing earlier for features: Example: the 26 feature branches in R951. ● Stabilizing the code base for integration ● Practice on staging ● Deploy a well tested reliable solution on prod ● Concern with this model ● It’s a long cycle (see previous slide) 2.5 week duration due to merges, compatibility testing, configuration validation, heavy track team involvement etc… ● We still have large releases with many dependencies (some of which are not understood) which increases our risk ● Inconsistent tooling across environments (Do we have enough envs?) ● Many release processes are still manual ● Post release hangover that says fix on fail: Bug fix releases are an assumed part of the Release Process. Our goal should be to eliminate the need for this step. ● What do we want? ● Shorter cycle ● Smaller releases with “no” dependencies decreasing the risk. Each component released must be able to be pushed and rolled back if needed. ● Automation for push-button releases (What if we were deploying to 5,000 servers not 500?) ● Don’t need to be fixing on fail because there are no bugs introduced into Prod ● Release when ready: (What does this mean?) a) Don’t release it on schedule because it didn’t pass our tests OR b) Release any module anytime with low risk. I want B.
LinkedIn - Confidential 2 Investment
Snapshot 2008E Rev $82 million / 2.6x 2007 Members 20 million, adding 1M+ per month at ~ $0 CPA Unique visitors1 6.6 million / 2.8x y-o-y Email addresses 384 million Connections 260 million Bookings ($MM) 2006 2007 2008 Subscriptions $6.3 $17.3 $33.0 Jobs 2.1 6.3 15.1 Advertising 2.1 7.8 30.1 Corporate 1.8 7.9 34.5 Total $12.4 $39.2 $112.6 Investors Sequoia, Greylock, Bessemer, Marc Andreessen, Peter Thiel 1 comScore January 2008 data The next massive business model in technology ▪ ~ $0 CPA per member, 1M+ / month ▪ High margin product: all digital goods, micro cost of sale ▪ Highly scalable: digital goods, infinitely replicable ▪ Network effects: network between users, network between business lines ▪ Huge markets: recruiting, media, services, sales, productivity software and others ➢ Google for finding professionals ➢ eBay for Labor Markets ➢ Microsoft for Internet productivity
LinkedIn - Confidential 5 Summary
The Network Key Differentiation: - Business focus: features, brand, network - Viral growth: entirely by individuals’ actions - Value scales with entire network (network effects) - Growing in every industry, globally - Organic growth into every business
LinkedIn - Confidential 6 Largest
Professional Network Domestic Growth Days 0 to 1MM members 477 1 to 2MM members 181 5 to 6MM members 102 9 to 10MM members 60 18 to 19MM members 28 199 of top 200 markets grew 70%+ in 2007; 155 grew 100%+ 0 5 10 15 20 5/1/03 9/1/03 1/1/04 5/1/04 9/1/04 1/1/05 5/1/05 9/1/05 1/1/06 5/1/06 9/1/06 1/1/07 5/1/07 9/1/07 2/1/08 Domestic International Millionsofmembers Globally x4 larger than nearest competitor; 50x larger in the U.S.
LinkedIn - Confidential 7 Best
and Broad Demographics School: 58K HBS: 17K School: 50K GSB: 8K 13K 32K 19K 13M University Alumni 31K Employees: 58K Alumni: 23K 19K Employees: 15K Alumni: 12K Employees: 116K Alumni: 71K 1.9M F500 Employees 41 27% $109,762 Demographics Average Age Average HHI HHI >$150K 78%College Grad Portfolio $250K+ 28% 1.2M Small Business Owners 2.2M Senior Executives VPs at every F500 company Source: @plan Winter 2007/2008, internal data 13K Employees: 13K Alumni: 9K
LinkedIn - Confidential 11 Summary
Media Key Differentiation: - User generated content - Best of class demographics - Unique targeting capabilities - Organic growth in every industry, globally - Ability to scale across the web - Future possibilities with self-service, B2B lead gen
The Bullseye Jeff’s articulation of
LinkedIn’s bullseye: Talent Solutions Description of the business: Passive Recruiting and how it works. Main point is the clarity with which we chose this target, and were willing to subordinate almost everything but user growth to it.
User Growth User Growth understood
as: Viral tuning SEO and Public Proﬁles Some known user value (network updates via email, receiving job offers) Some user value experiments (news, app platform, etc.)
Revenue Growth Main focus on
revenue growth will be growth of ﬁeld sales Reasoning for this Some online sales, but not for big-$$ accounts Other revenue sources beginning to enter the mix, but not core
Strategic Moats Professional Identity would
be primary moat Deﬁned roughly as size of network x quality of average proﬁle Main contributors were user growth and user activity. Also ﬁrst-mover advantage on passive recruiting would allow us to lock in customers. But we also felt we needed to respond to Facebook’s F8 announcement, which might have created a competitor built on top of FB.
Summary A growing network of
professionals with valuable proﬁles, driven by viral tuning and value experimentation Will form the foundation for a sales-driven business focused on large enterprise accounts… And we will do some competitive blocking on App Platforms.
Daily, 7-Day Cumulative Avg, Week
over Avg 4 Weeks, Year over YearMetrics: Signups 0 22,500 45,000 67,500 90,000 112,500 -40% 0% 40% 80% 120% 6/8/09 6/17/09 6/26/09 7/5/09 7/14/09 7/23/09 8/1/09 8/10/09 8/19/09 8/28/09 9/6/09 9/15/09 Daily 7-Day Cumulative Avg Week over Avg 4 Weeks Year over Year Guest Invites 0 100,000 200,000 300,000 400,000 500,000 600,000 -100% 0% 100% 200% 300% 6/8/09 6/17/09 6/26/09 7/5/09 7/14/09 7/23/09 8/1/09 8/10/09 8/19/09 8/28/09 9/6/09 9/15/09 Daily 7-Day Cumulative Avg Week over Avg 4 Weeks Year over Year Uniques 0 1,600,000 3,200,000 -80% 0% 80% 160% 6/8/09 6/17/09 6/26/09 7/5/09 7/14/09 7/23/09 8/1/09 8/10/09 8/19/09 8/28/09 9/6/09 9/15/09 Daily 7-Day Cumulative Avg Week over Avg 4 Weeks Year over Year Page Views 0 10,000,000 20,000,000 30,000,000 40,000,000 50,000,000 -100% 0% 100% 200% 300% 6/8/09 6/17/09 6/26/09 7/5/09 7/14/09 7/23/09 8/1/09 8/10/09 8/19/09 8/28/09 9/6/09 9/15/09 Daily 7-Day Cumulative Avg Week over Avg 4 Weeks Year over Year Searches 0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 -160% 0% 160% 320% 6/8/09 6/17/09 6/26/09 7/5/09 7/14/09 7/23/09 8/1/09 8/10/09 8/19/09 8/28/09 9/6/09 9/15/09 Daily 7-Day Cumulative Avg Week over Avg 4 Weeks Year over Year Premium Subs (New + Recurring) $0 $40,000 $80,000 $120,000 $160,000 -80% 0% 80% 150% 6/8/09 6/17/09 6/26/09 7/5/09 7/14/09 7/23/09 8/1/09 8/10/09 8/19/09 8/28/09 9/6/09 9/15/09 Daily 7-Day Cumulative Avg Week over Avg 4 Weeks Year over Year Members Joining Groups 0 40,000 80,000 120,000 160,000 -80% 0% 80% 160% 240% 320% 6/8/09 6/17/09 6/26/09 7/5/09 7/14/09 7/23/09 8/1/09 8/10/09 8/19/09 8/28/09 9/6/09 9/15/09 Daily 7-Day Cumulative Avg Week over Avg 4 Weeks Year over Year Groups Created 0 500 1,000 1,500 2,000 2,500 -100% 0% 100% 200% 300% 6/8/09 6/15/09 6/22/09 6/29/09 7/6/09 7/13/09 7/20/09 7/27/09 8/3/09 8/10/09 8/17/09 8/24/09 8/31/09 9/7/09 9/14/09 Daily 7-Day Cumulative Avg Week over Avg 4 Weeks Year over Year Job Dollars $0 $10,000 $20,000 $30,000 $40,000 $50,000 -80% 0% 80% 150% 6/8/09 6/17/09 6/26/09 7/5/09 7/14/09 7/23/09 8/1/09 8/10/09 8/19/09 8/28/09 9/6/09 9/15/09 Daily 7-Day Cumulative Avg Week over Avg 4 Weeks Year over Year Add a Comment Comments 9/9/2009 4:10:27 PM 8/20/2009 9:05:35 PM 8/20/2009 6:13:53 PM 8/19/2009 7:34:57 PM 8/19/2009 6:54:30 PM 8/19/2009 6:54:12 PM 8/19/2009 6:53:46 PM 8/11/2009 8:42:25 PM W/W jobs increase driven by 10% more spend per buyer due to job pack purchases and 8% better conversion For Jobs on Wednesday, 8/19: Conversion decreased 9% W/W but spend per buyer increased 6% and traffic to the flow increased 3%. We’re investigating the root cause of the conversion decreases that we’ve been seeing. New subs bookings growth driven by greater number of annual plans purchased relative to monthly plans (Business YR up 24% wk/wk and Business Plus YR up 18% wk/wk) “W/W declines driven by drops in conversion and spend per buyer. All hands are on deck investigating if something in last week's release or Saturday's Oracle upgrade is causing this.” Online Job sales were down –17% Y/Y at $39.7K but are trending towards being up Y/Y in the next 3 weeks. Page Views came in at 45.8M for Tuesday, the largest day since 27th January and the second highest day ever, up 78% Y/Y. Signups came in at 108.5K for Tuesday, the largest day since 27th January. The spike in the year over year numbers towards the end of May 09 is due to a site outage in May 08 Daily Executive Dashboard