ORIGINAL PITCHDATABLE = ♥ + ✓Problem• Lack of honesty in online dating profilesProject Name• DatableHigh Level Pitch• Online Dating Profile Verification, Klout for Dating
DATABLE = ♥ + ✓ONLINE DATING PROFILE VERIFICATIONCUSTOMER PROBLEM RISKIESTHYPOTHESIS HYPOTHESIS ASSUMPTIONONLINE INACCURATE PEOPLE CAREDATING SITE OF ONLINE ABOUTUSERS PROFILES PROFILE ACCURACY
DATABLE = ♥ + ✓VALIDATION PROCESSFACE 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 CITYCUSTOMER PROBLEM RISKIESTHYPOTHESIS HYPOTHESIS ASSUMPTIONONLINE DATERS DON’T PEOPLE CAREDATING SITE TRUST INFO ABOUTUSERS IN PROFILE PROFILE ACCURACY PIVOT !
KINECTIONTHE PIVOTCUSTOMER PROBLEM RISKIESTHYPOTHESIS HYPOTHESIS ASSUMPTIONJOB SO MANY EXISTINGSEEKERS LEADS, SO TOOLS ARE LITTLE TIME NOT SUFFICIENT
KINECTIONSOLUTION VALIDATIONCUSTOMER PROBLEM HYPOTHESISHYPOTHESIS SO MANY LEADS, GETTING SO LITTLE TIME THROUGH THE FUNNELJOBSEEKERS SOLUTION HYPOTHESIS RELEVANCY PRIORITIZE & PUSH ALGORITH FOR RANK BEST NOTIFICATION CONTACTS CONTACTS AT ON KEY POTENTIAL CONTACTS COMPANIES FOLLOWED
PROCESS MAP HYPOTHESIS VERIFICATIONExperimen 1 2 3 4 5 tsCustomer 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 InsufficientAssumption 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
KINECTIONKEY 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/k42KINECTION VALUE PROPOSITION – CONCISE, RELEVANT, ACTIONABLE REFFERAL RANKING KINECTION FLOW KINECTION ENGINE PUSH NOTIFICATIONS KARMA POINTS
KINECTION NEXT STEPSRISKIEST 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
KINECTIONTHE 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