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2010 01 11 Lean Startup Cohort meeting #2
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2010 01 11 Lean Startup Cohort meeting #2

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    2010 01 11 Lean Startup Cohort meeting #2 2010 01 11 Lean Startup Cohort meeting #2 Presentation Transcript

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