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2010 01 11 Lean Startup Cohort meeting #2

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2010 01 11 Lean Startup Cohort meeting #2

  1. Lean Startup Cohort #2Customer Development <br />WIFI<br />SSID: westinsf_conf<br />Username: lean2010<br />Password: westin10<br />
  2. From vision to MVP<br />The goal of customer development is to find a market for the product as currently specified<br />Have a strong vision, be prepared to learn whether it makes sense<br />Feedback from customers tells you about them not you<br />No focus groups<br />
  3. Major Sources of Waste<br />Building something nobody wants<br />Adding features your current customer doesn’t want<br />AKA adding features that don’t validate/refute current hypothesis<br />Arguing about product priorities<br />Flip-flopping between plans (iterating in a circle)<br />(these are in order of costliness)<br />
  4. Problem team, Solution team<br />Problem team: working on customer discovery<br />Solution team: working on Minimum Viable Product (MVP)<br />Both teams are cross-functional<br />Commitment from solution team leader to be personally involved with customer discovery<br />Metrics are people, too<br />
  5. Today’s Agenda<br />Develop deep customer insight: problem presentation, “day in the life”<br />Translate that insight into actionable per-user metrics<br />Build a model of how those metrics lead to massive success<br />Establish a baseline measurement using a minimum viable product<br />… and then move to Customer Validation<br />
  6. Deep Customer Insight (Problem)<br />Get out of the building and meet real and potential customers<br />Figure out what problems they have<br />Where does your problem rank on the hierarchy of pain?<br />Figure out the how, what, where, and why of customers using a product like yours<br />How do they describe the category, problem, and competitors – learn their language<br />Learn to tell an early adopter from a mainstream customer<br />
  7. Deep Customer Insight (Solution)<br />Learn how to describe your solution to potential customers<br />Find out if they agree it solves the problem, assuming it works “by magic”<br />Discover barriers to adoption (would they start using a magic product right away?)<br />Offer to pre-order to discover barriers to actual purchase (and to qualify early adopters)<br />
  8. Customer Archetype<br />Succinct description of insights<br />Designed to be actionable for whole team<br />If more than one, pick one target<br />Rule: always build for the target archetype without humiliating any other archetype<br />Big savings: avoid building features outside archetype description<br />
  9. Actionable Metrics<br />Assume everything you learned in discovery is true – how would you know?<br />Use customer insight to plot out the specific funnel for your customers: <br />how they find out about your product<br />how they acquire/try/adopt it <br />how they pay for it<br />how they engage over time<br />Establish per-customer metrics for this funnel<br />Most important: How do you know you’re making the product better?<br />
  10. Gross metrics don’t work<br />Why not focus on gross revenue, profit, or growth rate?<br />Impossible to predict<br />Keeps team working on high-ROI activities, but innovation tends to be low-ROI (at first)<br />Focus on gross numbers tends to erode differentiation (as everyone does the same “obvious” stuff)<br />
  11. Engine of Growth<br />The goal of actionable metrics is to establish a working and growing business model<br />Need to understand the “ecosystem” of your business at the per-customer level, and make sure it’s value-creating<br />Marginal revenue &gt; marginal cost<br />High volume, low margin<br />Low volume, high margin<br />Need to understand how this ecosystem supports one of three drivers of growth:<br />Paid (CPA &lt; LTV)<br />Viral (Viral coefficient &gt; 1)<br />Sticky (customer retention extremely high)<br />
  12. Build the model<br />Create the usual spreadsheet model of your business, but<br />Focus on inputs instead of outputs<br />Come up with reasonable assumptions, and make sure that the outputs are sufficient<br />Recognize that the model will probably change, so relationships are more important than specific numbers<br />
  13. Establish a baseline<br />Minimum viable product: that version of a new product which allows a team to collect the maximum amount of validated learning about customers with the least effort.<br />Each input in the model represents one key hypothesis about the business<br />Use the MVP to measure each input. Eliminate any features that do not pertain to one of the key inputs.<br />Work on the riskiest hypotheses first<br />
  14. Baseline<br />Once you have baseline numbers for your business, you are ready for customer validation<br />Probably, the numbers will look terrible – that’s OK<br />Figure out what the deltas are between baseline and a good outcome<br />Figure out which numbers are movable and which are fixed<br />
  15. Customer Validation<br />Once you have a MVP, become more dynamic<br />Shift from one-time activities to continuous flow, measured by validated learning<br />As you learn, you will be able to influence the actual customer behavior in your model<br />
  16. Validated Learning<br />It’s as important to know why a metric changed as to be able to show change<br />Growth in gross metrics is always ambiguous, too many external factors<br />Key validation techniques:<br />Revenue per customer<br />Cohort analysis<br />Split-testing<br />
  17. BOD accountability <br />Use validated learning to demonstrate shared sense of progress among:<br />Founders<br />Board of directors<br />Investors/outside stakeholders<br />Each baseline step is progress<br />After baseline, each pivot is progress<br />
  18. Team accountability<br />Charter semi-autonomous cross-functional teams, starting with just one solution team <br />Select a mutually-agreed goal<br />Team agrees to hit the goal or die trying<br />Team has representatives from all functions <br />Owns product, marketing, deployment decisions<br />At the end of a cycle, team can achieve success by:<br />Hitting the actionable-metric target<br />Demonstrating deep learning about what went wrong<br />Over multiple cycles, must show this learning is improving chances of hitting targets<br />
  19. Pivot<br />When customer validation fails, it’s time to pivot<br />Most pivots originate in the solution team: they cannot find a way to make the current hypothesis work.<br />Can’t hit actionable targets<br />Don’t improve on those targets over time<br />Each team must bring key data to a pivot meeting:<br />Solution team must have data about what’s not working<br />Problem team must have evidence for a next hypothesis<br />Both teams must have spent time with current customers<br />Pivot: keep most of the business model the same, change one key part at a time<br />
  20. Types of pivots<br />Customer need pivot: same customer segment, different need/problem<br />Customer segment pivot: same problem, different segment<br />Business architecture pivot: ie from enterprise to consumer<br />Zoom-in feature pivot: remove features to focus on just one key feature<br />Zoom-out feature pivot: add features to become more of a holistic solution<br />Technology pivot: solve same problem but with different technology stack<br />Channel pivot: same problem, same solution, different path to customers<br />Platform pivot: open up an application to third-parties to become a platform (or vice-versa)<br />
  21. Today<br />Develop deep customer insight: problem presentation, “day in the life”<br />Translate that insight into actionable per-user metrics<br />Build a model of how those metrics lead to massive success<br />Establish a baseline measurement using a minimum viable product<br />First up: KISSmetrics<br />

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