SlideShare una empresa de Scribd logo
1 de 13
Lean Startup
             New York City – April 14th
Machine
ORIGINAL PITCH
DATABLE = ♥ + ✓

Problem
• Lack of honesty in online dating
  profiles
Project Name
• Datable
High Level Pitch
• Online Dating Profile Verification,
  Klout for Dating
DATABLE = ♥ + ✓
ONLINE DATING PROFILE VERIFICATION



CUSTOMER            PROBLEM           RISKIEST
HYPOTHESIS         HYPOTHESIS        ASSUMPTION


ONLINE             INACCURATE        PEOPLE CARE
DATING SITE        OF ONLINE         ABOUT
USERS              PROFILES          PROFILE
                                     ACCURACY
DATABLE = ♥ + ✓
VALIDATION PROCESS




FACE TO FACE VALIDATION         ONLINE VALIDATION

 • 32 People Interviewed        • Anonymous profile
 • 7 Online Daters                created
 • Only 2 online daters cared   • Several messages sent
   about online profile         • 1 lengthy reply and one
   accuracy (The Risk             unsolicited date proposal
   Assumption)
DATABLE ≠ ♥ + ✓
NO LOVE IN THE HEART OF THE CITY



CUSTOMER             PROBLEM          RISKIEST
HYPOTHESIS          HYPOTHESIS       ASSUMPTION


ONLINE             DATERS DON’T      PEOPLE CARE
DATING SITE        TRUST INFO        ABOUT
USERS              IN PROFILE        PROFILE
                                     ACCURACY




                                 PIVOT !
KINECTION
THE PIVOT



CUSTOMER      PROBLEM       RISKIEST
HYPOTHESIS   HYPOTHESIS    ASSUMPTION


JOB          SO MANY       EXISTING
SEEKERS      LEADS, SO     TOOLS ARE
             LITTLE TIME   NOT
                           SUFFICIENT
KINECTION
SOLUTION VALIDATION



CUSTOMER         PROBLEM HYPOTHESIS
HYPOTHESIS       SO MANY LEADS,   GETTING
                 SO LITTLE TIME   THROUGH THE
                                  FUNNEL

JOB
SEEKERS


                 SOLUTION HYPOTHESIS
                 RELEVANCY        PRIORITIZE &   PUSH
                 ALGORITH FOR     RANK BEST      NOTIFICATION
                 CONTACTS         CONTACTS AT    ON KEY
                                  POTENTIAL      CONTACTS
                                  COMPANIES      FOLLOWED
KINECTION
TESTIMONIALS
PROCESS MAP
     HYPOTHESIS VERIFICATION

Experimen           1                   2                  3                   4                5
    ts
Customer     Online Dating        Job Seekers         Job Seekers        Current Job     Current Job
              Site Users         w/in the past 2     w/in the past 2      Seekers         Seekers
                                       yrs                 yrs                          Human
                People Care                          Need To Reach          Contact     Recommendations to
                                   Existing Tools
 Riskiest     People Care
               About Honesty                        NeedTo Network
                                                     Out To Reach          Ranking Is   Get Closer To The
                                    Insufficient
Assumption   About Honesty                          Out To Network          Useful      Ideal Job




  Result      2/7; 32 total          11/11              10/11                2/5             4/5
              Invalidated          Validated           Validated          Validated       Validated
 Learned       Difficulty in     Existing Tools     People Are More     Cost Might Be    Difficulty
             gathering data      Creates Sense         Reluctant To      a Sensitive      Utilizing
               due to the       of Uncertainties.    Initiate Contact      Issue.       Contact List
                personal                               From Their                       Especially If
             nature of topic.                            Network.                        You Don’t
               Need new                                                                   Have a
               customer.                                                                Specific End
                                                                                           Goal.
 Decision         Pivot         Persevere. Move     Persevere. Move      Persevere.      Persevere.
                                   onto Next           onto Next         Move Onto
KINECTION
KEY PIVOT POINTS:
• SEARCHING FOR A JOB, like DATING - is about “who you
  know” and the relationships you build
• EVERYONE we talked to said “searching for a job sux” and
  they wish it would have gone faster
• WE SAID: Let’s increase the velocity of the job search process
• LESS IS MORE: Kinection pushes FEWER recommended
  contact actions to the user, rather than more – where the
  timeliness and quality of contact’s proximity to a referral wins
  out over quantity.
• KINECTION KARMA POINTS – you never know who matters
  on your career path – so it pays to build good karma with
  Kinection.
•   Success Metrics: 100 unique Site visits – 13% signup rate since midnight April 13th –
    with minimal marketing.
KINECTION
    MVP - BIG DATA = BEHAVIORAL ANALYTICS FROM CONTACTS IN YOUR SOCIAL GRAPH



                                                          kinection



                                                       Will works at XYZ
                                                          and tweeted about
                                                          #LeanNYC connect
                                                          with him now!
                                                          bit.ly/k42




KINECTION VALUE PROPOSITION – CONCISE, RELEVANT, ACTIONABLE

  REFFERAL RANKING        KINECTION FLOW               KINECTION
       ENGINE            PUSH NOTIFICATIONS           KARMA POINTS
KINECTION
 NEXT STEPS

RISKIEST ASSUMPTION:
• Are job searchers willing to pay? If not, other monetization paths?

BIG VISION:
• Time: There are only so many hours in the day – why waste time on people
  who can’t connect you to hiring managers? Kinection is like a virtual
  recruiter – pointing you in the direction of the exact people you need to talk
  to.
• Accuracy: Most people admit that personal networks are the most powerful
  for job searching – but we’re still focusing on the job and not improving the
  relevancy of points of contact. Kinection energizes the propensity that the
  people you contact will refer you for the job you want.
• Incentive: Kinection Karma Points – the “What’s My Motivation?” of
  referral tools. Users both “pay it forward” and help themselves by accruing
  points they can use to unlock rewards and discount codes on affiliate sites
  (e.g.- SkillShare, General Assembly, Amazon Web Services).

HOW DO WE GET THERE:
• Rock star team, recruit users by illustrating value prop, collect/build data
  models
KINECTION
THE TEAM




            (left to right)
            • Jason Lee - Lead
                COO
            •   (initial concept and pitch deck)
            •   Patrizia Marsura CTO
            •   Jasmin Chun      CMO
            •   Will Kreth       CEO
            •   (pivot concept and revised deck)
            •   Christopher Lee       CFO

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Kinection - Lean Startup Machine NYC - 4.14.13

  • 1. Lean Startup New York City – April 14th Machine
  • 2. ORIGINAL PITCH DATABLE = ♥ + ✓ Problem • Lack of honesty in online dating profiles Project Name • Datable High Level Pitch • Online Dating Profile Verification, Klout for Dating
  • 3. DATABLE = ♥ + ✓ ONLINE DATING PROFILE VERIFICATION CUSTOMER PROBLEM RISKIEST HYPOTHESIS HYPOTHESIS ASSUMPTION ONLINE INACCURATE PEOPLE CARE DATING SITE OF ONLINE ABOUT USERS PROFILES PROFILE ACCURACY
  • 4. DATABLE = ♥ + ✓ VALIDATION PROCESS FACE TO FACE VALIDATION ONLINE VALIDATION • 32 People Interviewed • Anonymous profile • 7 Online Daters created • Only 2 online daters cared • Several messages sent about online profile • 1 lengthy reply and one accuracy (The Risk unsolicited date proposal Assumption)
  • 5. DATABLE ≠ ♥ + ✓ NO LOVE IN THE HEART OF THE CITY CUSTOMER PROBLEM RISKIEST HYPOTHESIS HYPOTHESIS ASSUMPTION ONLINE DATERS DON’T PEOPLE CARE DATING SITE TRUST INFO ABOUT USERS IN PROFILE PROFILE ACCURACY PIVOT !
  • 6. KINECTION THE PIVOT CUSTOMER PROBLEM RISKIEST HYPOTHESIS HYPOTHESIS ASSUMPTION JOB SO MANY EXISTING SEEKERS LEADS, SO TOOLS ARE LITTLE TIME NOT SUFFICIENT
  • 7. KINECTION SOLUTION VALIDATION CUSTOMER PROBLEM HYPOTHESIS HYPOTHESIS SO MANY LEADS, GETTING SO LITTLE TIME THROUGH THE FUNNEL JOB SEEKERS SOLUTION HYPOTHESIS RELEVANCY PRIORITIZE & PUSH ALGORITH FOR RANK BEST NOTIFICATION CONTACTS CONTACTS AT ON KEY POTENTIAL CONTACTS COMPANIES FOLLOWED
  • 9. PROCESS MAP HYPOTHESIS VERIFICATION Experimen 1 2 3 4 5 ts Customer Online Dating Job Seekers Job Seekers Current Job Current Job Site Users w/in the past 2 w/in the past 2 Seekers Seekers yrs yrs Human People Care Need To Reach Contact Recommendations to Existing Tools Riskiest People Care About Honesty NeedTo Network Out To Reach Ranking Is Get Closer To The Insufficient Assumption About Honesty Out To Network Useful Ideal Job Result 2/7; 32 total 11/11 10/11 2/5 4/5 Invalidated Validated Validated Validated Validated Learned Difficulty in Existing Tools People Are More Cost Might Be Difficulty gathering data Creates Sense Reluctant To a Sensitive Utilizing due to the of Uncertainties. Initiate Contact Issue. Contact List personal From Their Especially If nature of topic. Network. You Don’t Need new Have a customer. Specific End Goal. Decision Pivot Persevere. Move Persevere. Move Persevere. Persevere. onto Next onto Next Move Onto
  • 10. KINECTION KEY PIVOT POINTS: • SEARCHING FOR A JOB, like DATING - is about “who you know” and the relationships you build • EVERYONE we talked to said “searching for a job sux” and they wish it would have gone faster • WE SAID: Let’s increase the velocity of the job search process • LESS IS MORE: Kinection pushes FEWER recommended contact actions to the user, rather than more – where the timeliness and quality of contact’s proximity to a referral wins out over quantity. • KINECTION KARMA POINTS – you never know who matters on your career path – so it pays to build good karma with Kinection. • Success Metrics: 100 unique Site visits – 13% signup rate since midnight April 13th – with minimal marketing.
  • 11. KINECTION MVP - BIG DATA = BEHAVIORAL ANALYTICS FROM CONTACTS IN YOUR SOCIAL GRAPH kinection    Will works at XYZ and tweeted about #LeanNYC connect with him now! bit.ly/k42 KINECTION VALUE PROPOSITION – CONCISE, RELEVANT, ACTIONABLE REFFERAL RANKING KINECTION FLOW KINECTION ENGINE PUSH NOTIFICATIONS KARMA POINTS
  • 12. KINECTION NEXT STEPS RISKIEST ASSUMPTION: • Are job searchers willing to pay? If not, other monetization paths? BIG VISION: • Time: There are only so many hours in the day – why waste time on people who can’t connect you to hiring managers? Kinection is like a virtual recruiter – pointing you in the direction of the exact people you need to talk to. • Accuracy: Most people admit that personal networks are the most powerful for job searching – but we’re still focusing on the job and not improving the relevancy of points of contact. Kinection energizes the propensity that the people you contact will refer you for the job you want. • Incentive: Kinection Karma Points – the “What’s My Motivation?” of referral tools. Users both “pay it forward” and help themselves by accruing points they can use to unlock rewards and discount codes on affiliate sites (e.g.- SkillShare, General Assembly, Amazon Web Services). HOW DO WE GET THERE: • Rock star team, recruit users by illustrating value prop, collect/build data models
  • 13. KINECTION THE TEAM (left to right) • Jason Lee - Lead COO • (initial concept and pitch deck) • Patrizia Marsura CTO • Jasmin Chun CMO • Will Kreth CEO • (pivot concept and revised deck) • Christopher Lee CFO