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Blitzscaling Session 9: Village Stage

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Slides from Class 9 (10/20/15) of Stanford CS183C, Technology-enabled Blitzscaling.

Instructors: Reid Hoffman, John Lilly, Allen Blue and Chris Yeh.

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Blitzscaling Session 9: Village Stage

  1. CS183C: Blitzscaling Instructors: Allen Blue, Reid Hoffman, John Lilly & Chris Yeh October 20, 2015
  2. Organizational Scale 3: Village
  3. Now for the big shift.
  4. Class Structure: Organizational Scale Org Scale (employees) User Scale (B2C users) Customer Scale (B2B) Business Scale (rev) OS1: Family 1s 10,000s 0 <$10M OS2: Tribe 10s 100,000s 1s $10M+ O3: Village 100s 1,000,000s 10s $100M+ OS4: City 1,000s 10,000,000s 100s $1B+ OS5: Nation 10,000s 100,000,00+ 1,000+ $5B+
  5. OS1: The Household Identify a non-obvious market opportunity where you have a unique advantage and/or approach. Iteratively build a product with strong product/ market fit
  6. OS2: The Tribe Execute & iteratively improve a plan which gets you to significant market share.
  7. OS3: The Village Identify, plan and execute the core business you will scale up.
  8. OS3: The Village Identify, plan and execute the core business you will scale up. … with a plan to scale more
  9. OS3: The Village Identify, plan and execute the core business you will scale up. … with a plan to scale more … and do it fast
  10. 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
  11. 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
  12. LinkedIn All-Hands February 17, 2010
  13. OS3: Critical Components to Scale the Core Business • What must you do to scale the core business? • Across growth, revenue • Product and Technology • Go-to-market (sales, marketing) • Partnerships
  14. Product Plan February, 2010
  15. 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
  16. 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
  17. Talent Solutions GTM March, 2010
  18. LinkedIn 3.0 / Scaling 10x February, 2010
  19. 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
  20. Leadership, Culture, Hiring, Process 2008-2010
  21. © 2009 LinkedIn All rights reserved. Confidential 60 LinkedIn Values and Culture Members Come First - Candidates are also our members, leave them feeling great about LinkedIn regardless of our decision to hire or not. Be compassionate, offer to take a candidate for a quick walk, for a break, offer snack/beverages if they look tired. Relationships Matter - Candidates will either advocate us, say nothing about us, or speak negatively about us based on how we treat them. Glassdoor.com and other sites/blogs keep all companies on their toes in terms of reputation and sharing stories. Open, Honest and Constructive - consider this as you answer the candidate’s questions and as you write your own feedback after the interview. Demand Excellence - consider this not only of the candidate but yourself regarding how you conduct the interview... don’t focus too much on technical/analytical skills so they overshadow your assessment of the candidate’s creativity and vision. Take Intelligent Risks - If the candidate doesn’t have the experience in the talent solutions space or social media, or if you initially rate as B + rather than A+, as yourself if they have the raw materials and potential to become an A+ within a short timeframe. Act Like an Owner - Talent is our most important asset. We expect our employees to act as an owner in each decision they make, no matter how big or small. Transformation of world, company and self Integrity Collaboration Humor Results
  22. Tech All-Hands December, 2009
  23. 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.
  24. 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
  25. Site Up -> Company Up
  26. 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?
  27. Current Release Process

  28. 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.
  29. LinkedIn Series D Summer, 2008
  30. Global Internet Business Platform and Applications
  31. 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
  32. 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
  33. 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.
  34. 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
  35. 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
  36. LinkedIn - Confidential 26 0$100 12.5$100 25$100 37.5$100 $100$100 Dice Monster HotJobs eBay Google Xing LinkedIn Revenue Upside $86.91 Mean:
 $34.05 Mean:
 $21.08 Mean: $10.52 Upside revenue opportunity Current revenue projections Job boards Internet 
 leaders Business/ 
 social 
 networking Revenue/worldwide unique visitors $0 $200 $400 $600 $800 $1,000 2007 2008E 2009E ($34.05 Ave Rev/User) x 5.5MM Uniques) ($34.05 Ave Rev/User) x13.4MM Uniques) ($34.05 Ave Rev/User) x25.0MM Uniques) LinkedIn potential revenue
  37. Appendix
  38. Articulating biz
  39. 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.
  40. 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.)
  41. 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
  42. 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.
  43. Future strategic assets Non-Jobs brand Potential discover of additional value propositions improves brand, Drives growth and profile moats builds additional platforms for future businesses
  44. 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.
  45. Key steps to succed
  46. Changing roles for founders/early team Jean-Luc, engineering changes New engineering group leaders Turnover with new execs
  47. Data Building our data function
  48. 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

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