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OnLab Japan introduction to Lean Analytics



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OnLab Japan introduction to Lean Analytics

  1. 1. Lean Analytics Use data to build a better business faster. @byosko | @acroll @leananalytics
  2. 2. Silicon Valley doesn’t love failure.
  3. 3. It just hates it less than the alternative:
  4. 4. Making something nobody needs.
  5. 5. Most startups don’t know what they’ll be when they grow up. Freshbooks Mitel was invoicing Wikipedia was a Paypal for a web was to be lawnmower first built for company design firm written by Palmpilots experts only Flickr Hotmail Twitter Autodesk was going to was a was a made desktop be an MMO database podcasting automation company company
  6. 6. Kevin Costner is a lousy entrepreneur. Don’t sell what you can make. Make what you can sell.
  7. 7. Analytics is the measurement of movement towards your business goals.
  8. 8. Small business example: Solare watches the numbers • Stage: Revenue • Model: Retailer • Solare is an Italian fine-dining restaurant under new management. The new team is trying to identify the key metrics and leading indicators
  9. 9. Solare watches the numbers • A line in the sand: Gross Revenue to Labor Cost • Under 30% is good • Below 24% is great • Lower than 20% and you may be under-staffing, leading to dissatisfied customers • A leading indicator: Total covers is 5x reservations at 5PM • If you have 50 reservations at 5, you’ll have 250 covers that night. • This ratio varies by restaurant.
  10. 10. In a startup, the purpose of analytics is to iterate to a product/market fit before the money runs out.
  11. 11. Qualitative or Quantitative 5 things you Exploratory or Reporting need to know Vanity or Actionable about metrics Correlated or Causal Leading or Lagging
  12. 12. Qualitative Quantitative Unstructured, Numbers and stats; anecdotal, hard facts but less revealing, hard to insight. aggregate. Warm and fuzzy. Cold and hard.
  13. 13. Simply: you can’t count smiles. Discover qualitatively, prove quantitatively. Qualitative is inspiration, quantitative is verification.
  14. 14. Exploratory Reporting Speculative, trying Predictable, keeping to find unexpected you abreast of or interesting normal, managerial insights. operations.
  15. 15. Donald Rumsfeld on analytics Are facts which may be wrong and we know should be checked against data. know we don’t Are questions we can answer by reporting, which we should baseline know & automate. Things we Are intuition which we should we know quantify and teach to improve don’t effectiveness, efficiency. know we don’t Are exploration which is where unfair advantage and interesting know epiphanies live. (Or rather, Avinash Kaushik channeling Rumsfeld)
  16. 16. Vanity Actionable Picks a direction. Makes you feel good, but doesn’t change how you’ll act.
  17. 17. A metric from the early, foolish days of the Web. Hits Count people instead. Marginally better than hits. Unless you’re displaying Page views ad inventory, count people. Is this one person visiting a hundred times, or are a Visits hundred people visiting once? Fail. This tells you nothing about what they did, why they Unique visitors stuck around, or if they left. Followers/ Count actions instead. Find out how many followers friends/likes will do your bidding. Time on site, or Poor version of engagement. Lots of time spent on pages/visit support pages is actually a bad sign. How many recipients will act on what’s in them? Emails collected Number of Outside app stores, downloads alone don’t lead to downloads lifetime value. Measure activations/active accounts.
  18. 18. 2-sided market model: AirBnB and photography • Stage: Revenue • Model: 2-sided marketplace • Rental-by-owner marketplace that allows property owners to list and market their houses. Offers a variety of related services as well.
  19. 19. AirBnB tests a hypothesis • The hypothesis: “Hosts with professional photography will get more business. And hosts will sign up for professional photography as a service.” • Built a concierge MVP • Found that professionally photographed listings got 2-3x more bookings than the market average. • In mid-to-late 2011, AirBnB had 20 photographers in the field taking pictures for hosts.
  20. 20. NIGHTS BOOKED 10 million 8 million 6 million 20 photographers 4 million 2 million 2008 2009 2010 2011 2012
  21. 21. it’s a how you behave, If it won’t change bad metric.
  22. 22. A few words on causality.
  23. 23. 50 37.5 25 12.5 0 1 2 3 4 5 6 7 8 9 10 Seat rentals
  24. 24.
  25. 25.
  26. 26. 10000 1000 100 10 1 Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Ice cream consumption Drownings
  27. 27.
  28. 28.
  29. 29.
  30. 30. 10000 1000 100 10 1 Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Ice cream consumption Drownings Temperature
  31. 31.
  32. 32.
  33. 33.
  34. 34. Correlated Causal Two variables that An independent change in similar factor that directly ways , perhaps impacts a because they’re dependent one. linked to something else. Summer al Ca us us Ca Correlated al Drowning Ice cream consumption
  35. 35.
  36. 36. Causality is a superpower, because it lets you change the future. Correlation lets you Causality lets you predict the future change the future “I will have 420 “If I can make more engaged users and first-time visitors stay 75 paying customers on for 17 minutes I next month.” will increase sales in 90 days.” Optimize the Find correlation Test causality causal factor
  37. 37. Leading Lagging Number today that Historical metric that shows metric shows how you’re tomorrow—makes doing—reports the the news. news.
  38. 38. A leading indicator for e-commerce How many of your customers Then you are in Your customers You are just Focus on buy a second this mode will buy from you like time in 90 days? Low CAC, 1-15% Acquisition Once 70% high of retailers checkout 15-30% Hybrid 2-2.5 20% Increasing per year of retailers returns Loyalty, >30% Loyalty >2.5 10% inventory per year of retailers expansion (Thanks to Kevin Hilstrom for this.)
  39. 39. Think about a car •60MPH is twice as fast as 30MPH •Speed limits and mileage are well understood •Kilometres are conveniently decimal; miles map to hours •Ratios everywhere •Miles travelled is good; •Miles per hour is better; •Accelerating or decelerating changes your gas pedal •Custom metrics: “MPH divided by speeding tickets” as a metric of “driving fast without losing my license”
  40. 40. The Lean Analytics Framework.
  41. 41. Eric Ries’ Three engines Stickiness Virality Price Approach Keep people Make people Spend revenue coming back. invite friends. getting customers. Math that Get customers How many they Customers are matters faster than you tell, how fast worth more than lose them. they tell them. they cost to get.
  42. 42. Dave McClure’s Pirate metrics How do your users become aware of you? Acquisition AARRR SEO, SEM, widgets, email, PR, campaigns, blogs ... Do drive-by visitors subscribe, use, etc? Activation Features, design, tone, compensation, affirmation ... Does a one-time user become engaged? Retention Notifications, alerts, reminders, emails, updates... Do you make money from user activity? Revenue Transactions, clicks, subscriptions, DLC, analytics... Do users promote your product? Referral Email, widgets, campaigns, likes, RTs, affiliates...
  43. 43. The five Stages of Lean Analytics Empathy The stage you’re at Stickiness Virality Revenue Scale
  44. 44. Example: a restaurant • Empathy: Before opening, the owner first learns about the diners in its area, their desires, what foods aren’t available, and trends in eating. • Stickiness: Then he develops a menu and tests it out with consumers, making frequent adjustments until tables are full and patrons return regularly. He’s giving things away, testing things, asking diners what they think. Costs are high because of variance and uncertain inventory. • Virality: He starts loyalty programs to bring frequent diners back, or to encourage people to share with their friends. He engages on Yelp and Foursquare. • Revenue: With virality kicked off, he works on margins—fewer free meals, tighter controls on costs, more standardization. • Scale: Finally, knowing he can run a profitable business, he pours some of the revenues into marketing and promotion. He reaches out to food reviewers, travel magazines, and radio stations. He launches a second restaurant, or a franchise based on the initial one.
  45. 45. Example: a software company • Empathy: The founder finds an unmet need, often because she has a background in a particular industry or has worked with existing solutions that are being disrupted. • Stickiness: She meets with an initial group of prospects, and signs contracts that look more like consulting agreements, which she uses to build an initial product. She’s careful not to commit to exclusivity, and tries to steer customers towards standardized solutions, charging heavily for custom features. She supports the customers directly from the engineering team until the product is stable and usable. • Virality: Product in hand, she asks for references from satisfied customers, and uses them as testimonials. She starts direct sales, and grows the customer base. She launches a user group, and starts to automate support. She releases an API, encouraging third-party development and scaling potential market size without direct development. • Revenue: She focuses on growing the pipeline, sales margins, and revenues while controlling costs. Tasks are automated, outsourced, or offshored. Feature enhancements are scored based on anticipated payoff and development cost. Recurring license and support revenue becomes an increasingly large component of overall revenues. • Scale: She signs deals with large distributors, and works with global consulting firms to have them deploy and integrate her tool. She attends trade shows to collect leads, carefully measuring cost of acquisition against close rate and lead value.
  46. 46. Empathy Get inside their head.
  47. 47. Mobile app model: Localmind hacks Twitter • Stage: Empathy • Model: UGC/mobile • Real-time question and answer platform tied to locations. • Needed to find out if a core behavior—answering questions about a place— happened enough to make the business real
  48. 48. Localmind hacks Twitter • Before writing a line of code, Localmind was concerned that people would never answer questions. • This was their biggest risk: if questions went unanswered users would have a terrible experience and stop using Localmind. • Ran an experiment on Twitter • Tracked geolocated tweets in Times Square • Sent @ messages to people who had just tweeted, asking questions about the area: how busy is it; is the subway running on time; is something open; etc. • The response rate to their tweeted questions was very high. • Good enough proxy to de-risk the solution, and convince the team and investors that it was worth building Localmind.
  49. 49. When it’s time to move on • Have you conducted enough quality customer interviews to feel confident that I’ve found a problem worth solving? • Do you understand your customer well enough? • Do you believe your solution will meet the needs of customers?
  50. 50. Stickiness The dogs like the dogfood.
  51. 51. 1995 Hits 1997 Visits 1999 Visitors 2002 Conversions Who did you add? Where from? Why? 2010 Engagement What did they do? How did it benefit? Who did you lose? Why did they leave?
  52. 52. Stickiness stage: WP Engine discovers the 2% cancellation rate • Stage: Stickiness • Model: SaaS • Wordpress hosting company founded in July 2010, it raised $1.2M in November 2011
  53. 53. WP-Engine discovers the 2% cancellation rate • All companies have cancellations, but founder Jason Cohen was alarmed that he was losing a quarter of customers every year. • Jason called customers himself. “Not everyone wanted to speak with me, but enough people were willing to talk, even after they had left, that I learned a lot about why they were leaving.” • Asked around. Turns out 2% is best case for most hosting companies. • Without this, the company would have been getting diminishing returns over- optimizing churn; instead, they could focus on maximizing revenues or lowering acquisition costs.
  54. 54. When it’s time to move on • Are people using the product as expected? • Define an active user. What percentage of your users/customers is active? Write this down. Could this be higher? What can you do to improve engagement? • Evaluate your feature roadmap against the 7 questions to ask before building more features. Does this change the priorities of feature development? • Evaluate the complaints you’re getting from users. How does this impact feature development going forward?
  55. 55. Virality I told two friends.
  56. 56. Virality stage: Timehop’s content sharing • Stage: Virality • Model: Mobile app • Social network around the past • Focused on virality (but not necessarily the coefficient!)
  57. 57. The one metric that matters: content sharing • Focused on percent of daily active users that share their content • Aiming for 20-30% of DAU sharing “All that matters now is virality. Everything else—be it press, publicity stunts or something else— is like pushing a rock up a mountain: it will never scale. But being viral will.” - Jonathan Wegener, co-founder
  58. 58. 3 kinds of virality • Inherent virality is built into the product, and happens as a function of use. • Artificial virality is forced, and often built into a reward system. • Word of mouth virality is simply conversations generated by satisfied users.
  59. 59. When it’s time to move on • Are you using one of the three types of virality (inherent, artificial, word of mouth) for your startup? Describe how. If virality is a weak aspect of your startup, write down 3-5 ideas for how you could build more virality into your product. • What’s your viral coefficient? Even if it’s below 1 (which it likely is), do you feel like the virality that exists is good enough to help sustain growth and lower customer acquisition costs? • What’s your viral cycle time? How could you speed it up?
  60. 60. Revenue Pour some of the money back into acquisition.
  61. 61. Revenue stage: Backupify’s customer lifecycle • Stage: Revenue • Model: SaaS • Leading backup provider for cloud based data. • The company was founded in 2008 by Robert May and Vik Chadha • Has gone on to raise $19.5M in several rounds of financing.
  62. 62. Shifting to Customer Acquisition Payback as a key metric • Initially focused on site visitors • Then focused on trials • Then switched to signups • Today, MRR • In early 2010, CAC was $243 and ARPU was only $39 • Pivoted to target business users • CLV-to-CAC today is 5-6x • Now they track Customer Acquisition Payback • Target is less than 12 months
  63. 63. Sergio Zyman’s many “mores” • If you’re dependent on physical, per-transaction costs (like direct sales, or shipping products to a buyer, or signing up merchants) then more efficiently will figure prominently on either the supply or demand side of your business model. • If you’ve found a high viral coefficient, then more people makes sense, because you’ve got a strong force multiplier added to every dollar you pour into customer acquisition. • If you’ve got a loyal, returning set of customers who buy from you every time, then more often makes sense, and you’re going to emphasize getting them to come back more frequently. • If you’ve got a one-time, big-ticket transaction, then more money will help a lot, because you’ve only got one chance to extract revenue from the customer and need to leave as little money as possible on the table. • If you’re a subscription model, and you’re fighting churn, then upselling customers to higher-capacity packages with broader features to additional subscribers within their organization is your best way of growing existing revenues, so you’ll spend a lot of time on more stuff.
  64. 64. When it’s time to move on You’re making money You’re sustainable You’re tracking growth metrics
  65. 65. Scale Let others grow your business for you.
  66. 66. The hole in the middle Differentiation Efficiency Apple Costco Here be dragons Your local sustainable gluten-free cupcake shop Niche
  67. 67. Guerrilla Data- marketing driven learning GROWTH HACKING Subversiveness
  68. 68. The trust equation Your expertise & Do what you Are you one of reputation; say; say what us? Morality & certifications you do. personality. Credibility + Reliability + Intimacy Trustworthiness = Self-orientation What’s in it for you? Maister, Green and Galford
  69. 69. • A Facebook user reaching 7 friends within 10 days of signing up (Chamath Palihapitiya) • If someone comes back to Zynga a day after signing up for a game, they’ll probably become an engaged, paying user (Nabeel Hyatt) • A Dropbox user who puts at least one file in one folder on one device (ChenLi Wang) • Twitter user following a certain number of people, and a certain percentage of those people following the user back (Josh Elman) • A LinkedIn user getting to X connections in Y days (Elliot Schmukler) (These are also great segments to analyze.) (from the 2012 Growth Hacking conference)
  70. 70. The growth hack • Growth hacking is simply what marketing should have been doing, but it fell in love with Don Draper and opinions along the way • At its most basic: Optimize a factor you think is correlated with growth
  71. 71. AirBnB and Craigslist
  72. 72. Getsatisfaction extortion
  73. 73. Coveting GMail invites
  74. 74. Farmville and wall posts
  75. 75. The five Stages of Lean Analytics The business you’re in E- 2-sided Mobile User-gen SaaS Media commerce market app content
  76. 76. UGC model: Reddit goes from links to community • Stage: Virality • Model: UGC • A graduate of the first YCombinator class, reddit was acquired by Conde Nast but left largely to its own devices. Thanks to a vibrant community and some good guidance by its founders, it’s a traffic powerhouse.
  77. 77. Reddit goes from links to community • Product evolution • Started as a simple link-sharing site with voting • Then added the ability to comment, with votes on comments • Then created the ability to make “self-posts” rather than only comment on off- site traffic • Now self-posts are more than half of all posts
  78. 78. Reddit goes from links to community • Revenue from ads and “reddit gold” • Started as a joke, but turned into a revenue source • One person paid $1000 for a month; some paid $0.01. Avg. around $4. • Paying users get early access to features, since they’re an engaged beta
  79. 79. The five Stages of Lean Analytics The business you’re in E- 2-sided Mobile User-gen SaaS Media commerce market app content Empathy The stage you’re at One Metric Stickiness Virality Revenue That Matters. Scale
  80. 80. Choose only one metric.
  81. 81. Yes, one metric.
  82. 82. It will soon change.
  83. 83. In a startup, focus is hard to achieve.
  84. 84. Having only one metric addresses this problem.
  85. 85. Metrics are like squeeze toys.
  86. 86. What’s your OMTM? E- 2-sided Mobile User-gen SaaS Media commerce market app content Empathy Interviews; qualitative results; quantitative scoring; surveys Loyalty, Inventory, Engagement, Downloads, Content, Traffic, visits, Stickiness conversion listings churn churn, virality spam returns CAC, shares, Inherent WoM, app Invites, Content Virality reactivation SEM, sharing virality, CAC ratings, CAC sharing virality, SEM (Money from transactions) (Money from active users) (Money from ad clicks) Transaction, Transactions, Upselling, CLV, Ads, CPE, affiliate Revenue CLV commission CAC, CLV ARPDAU donations %, eyeballs Affiliates, Other API, magic Spinoffs, Analytics, Syndication, Scale white-label verticals #, mktplace publishers user data licenses
  87. 87. B2B: Selling to the enterprise
  88. 88. The B2B stereotype • Domain expert knows industry and the problem domain. Has a Rolodex; proxy for customers. • Disruption expert knows tech that will produce a change Sees beyond the current model. Domain Disruption expert expert Operations
  89. 89. Three typical approaches Create a popular consumer Dropbox Enterprise pivot product then pivot to tackle the enterprise Take an existing consumer or Yammer, Copy and rebuild open source idea and make it MapR enterprise-ready Convince the enterprise to Taleo, Disrupt a problem discard the old way because of Google overwhelming advantages. Apps
  90. 90. Enterprise example: Coradiant pivots from service to appliance • Stage: Revenue • Model: Enterprise sale • Coradiant started as a research firm, then moved into managed services. As the market’s needs changed and data center preferences ossified, the company switched from services to a physical appliance for web performance management.
  91. 91. Coradiant pivots from service to appliance • Started as an MSP in colocated spaces, offering service and virtual infrastructure. • Data center partners became competitors • Talked to customers, who liked the monitoring interface and performance management • Hibernated the company and turned the internal tool for monitoring web health (OutSight) into an appliance • MVP focused on the core value—what was actually happening on the wire • Reporting etc. was introduced as Excel exports initially • Made it easy to get data off the box to mitigate limited feature sets • Scaled through channels and partnerships (Splunk, Akamai, etc.)
  92. 92. Lean Analytics lifecycle for an enterprise-focused startup Stage Do this Fear this Consulting to test ideas and Lock-in, IP Empathy bootstrap the business control, overfitting Standardization and integration; Ability to Stickiness shift from custom to generic integrate; support Word of mouth, references, case Bad vibes; Virality studies exclusivity Growing direct sales, professional Pipeline, revenue Revenue services, support recognition, comp Channels, analysts, ecosystems, Crossing the Scale APIs, vertically targeted products chasm; Gorillas
  93. 93. The Zero Overhead principle A central theme to this new wave of innovation is the application of core product tenets from the consumer space to the enterprise. In particular, a universal lesson that I keep sharing with all entrepreneurs building for the enterprise is the Zero Overhead Principle: no feature may add training costs to the user. DJ Patil
  94. 94. Intrapreneur
  95. 95. Skunk Works for intrapreneurs • The Lockheed Martin Skunk Works
  96. 96. Span of control and the railroads • Daniel C. McCallum
  97. 97. The BCG matrix • How businesses think about products or Question marks! increase
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 high growth rate) through
 high market share) May be the next big thing. virality,
 What everyone wants. As • Lean is about moving Consumes investment, but attention market invariably stops will require money to growing, should become up and to the right Growth rate increase market share. cash cows. Milk with
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 redefine problem/
 increase growth
 optimization as
 solution through
 rate through
 growth slows empathy disruption Dogs! Cash cows! (low market share, (high market share, low growth rate) low growth rate) Barely breaks even, may Boring sources of cash, to be a distraction from better be milked but not worth opportunities. Sell off or additional investment. shut down. Market share
  98. 98. Intrapreneur example: P&G changes the mop instead of the soap • Stage: Empathy • Model: Retail/consumer packaged goods • P&G is constantly looking for better soaps. But innovation was slowing. Frustrated, they hired a design team to help them.
  99. 99. P&G changes the mop instead of the soap • Heavy internal investment in R&D, but limited results • Brought in an outside agency (Continuum) to help • The team watched people as they mopped, recording and iterating their research approach • Watched someone pick up spilled coffee. Rather than mopping, the person swept up with a broom, then wiped with a cloth • Realized the mop, not the liquid, mattered • Studied the makeup of floor dirt; realized much of it is dust • Swiffer is a $500M innovation in a stalled industry
  100. 100. The Lean Analytics lifecycle for an Intrapreneur Stage Do this Fear this Get buy-in Political fallout Beforehand Find problems; don’t test demand. Entitled, aggrieved Empathy Skip the business case, do analytics customers Know your real minimum based on Hidden “must haves”, Stickiness expectations, regulations feature creep Build inherent virality in from the Luddites who don’t Virality start; attention is the new currency understand sharing Consider the ecosystem, channels, Channel conflict, Revenue and established agreements resistance, contracts Hand the baton to others gracefully Hating what happens Scale to your baby
  101. 101. Metrics in practice: The Lean Analytics Cycle Success! Pick OMTM Draw a line in the sand Pivot or give up Draw a new line Find a potential Try again improvement Did we move the needle? Without With data: data: make a find a good guess commonality Design a test Measure the results Hypothesis Make changes in production
  102. 102. Virality stage: Circle of Moms finds an engaged market • Stage: Stickiness • Model: UGC • Launched as Circle of Friends in 2007, it was a way for small groups to interact atop Facebook’s platform; but when engagement wasn’t good enough, the founders decided to dig deeper.
  103. 103. The problem: Not enough engagement • Too few people were actually using the product • Less than 20% of any circles had any activity after their initial creation • A few million monthly uniques from 10M registered users, but no sustained traction
  104. 104. What Circle of Moms found • They found moms were far more engaged • Their messages to one another were on average 50% longer • They were 115% more likely to attach a picture to a post they wrote • They were 110% more likely to engage in a threaded (i.e. deep) conversation • Circle owners’ friends were 50% more likely to engage with the circle • They were 75% more likely to click on Facebook notifications • They were 180% more likely to click on Facebook news feed items • They were 60% more likely to accept invitations to the app • Pivoted to the new market, including a name change • By late 2009, 4.5M users and strong engagement • Sold to Sugar, inc. in early 2012
  105. 105. Virality stage: qidiq streamlines invites • Stage: Virality • Model: SaaS • Tool to poll small groups, built in the Year One Labs accelerator
  106. 106. Initial design Redesigned workflow Survey owner adds recipient to group Survey owner adds recipient to group 70-90% RESPONSE RATE Survey owner asks question Survey owner asks question Recipient gets invite Recipient reads survey question 10-25% RESPONSE RATE Recipient installs mobile app Recipient responds to question Recipient sees survey results Recipient creates account, profile Recipient can edit profile, view past (Later, if needed…) questions, etc. Recipient visits website Recipient reads survey question Recipient has no password! Recipient responds to question Recipient does password recovery Recipient sees survey results One-time link sent to email Recipient creates password Recipient can edit profile, view past questions, etc.
  107. 107. “The most important figures that one needs for management are unknown or unknowable, but successful management must nevertheless take account of them.” Lloyd S. Nelson
  108. 108. Pic by Twodolla on Flickr.
  110. 110. Once, a leader convinced others in the absence of data.
  111. 111. Now, a leader knows what questions to ask.
  112. 112. Ben Yoskovitz @byosko Alistair Croll @acroll