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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)
    View slide
  • 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
    View slide
  • 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