Team Ainsley OConnell Emmanuel A. Simon Hemanth Setty Wyeth Mendoza Robert Deng
Original Pitch A freemium travel concierge service that provides real-time recommendations and advice for travelers during the trip.
Hypothesis 1 Assumption to test • Travelerswould use a service that provides • Greater comfort speaking to a real-time advice human being than using an from local experts app or tool when looking for over apps, random locals, advice etc.
Experiment • Saturday morning • Distribute ﬂyers to tourists downtown • Provide recommendations to tourists who convert
Results and Lessons Learned • One customer used • Customers weren t sure the service for lunch in what to ask—“plans for Soho tonight” too broad, ambiguous • Others(17) conﬁrmed human preference • To simplify customer hypothesis in education, focus on interviews restaurants and nightlife
Pivot: Hypothesis 2, Part 1 Assumptions • Travelers would text/ tweet restaurant • Travelers needed help ﬁnding and nightlife restaurants and nightlife requests to an expert on the ﬂy advisor able to respond in 5 min or less with • Matching competitors in terms of recommendations on time will enable switching how to eat and drink like a local
Experiment • Saturday afternoon • Differentmessage, different locations, same tactic
Results and Lessons Learned • Of ~100 ﬂyers distributed, 25 • Focusmarketing efforts on travelers said they would be word of mouth, targeting interested in the service, with international travelers particular interest expressed by international • Relyon SMS to ensure travelers compatibility with intern l traveler needs • In interviews, travelers said word of mouth marketing would be crucial to winning their trust
Hypothesis 2, Part 2 Assumptions to test • Travelers would text restaurant and • Travelers don t plan where nightlife requests to they ll eat and drink in advance an expert advisor able to respond in 5 min or less look for local • Travelers with recommendations expertise when it comes to on how to eat and drink restaurants and nightlife like a local
Experiment • Onlinesurvey of traveler behavior sent to team s social networks
Results and Lessons Learned • Only 21% of respondents plan restaurant destinations in detail in advance of their trip; 0% plan nightlife destinations in detail in advance Assumptions conﬁrmed • 68% research restaurants & nightlife during their trip by talking with local professionals (concierges, etc.) and 53% talk with locals they encounter on the street
Hypothesis 2, Part 3 Assumptions to test • Travelers would text restaurant and • Tripo!local experts can offer nightlife requests to higher quality an expert advisor able to recommendations than respond in 5 min or less competitors such as Yelp, random with recommendations local experts, etc., in a on how to eat and drink competitive time frame like a local
Experiment 10:42 PM 10:36 PM Which part of Brooklyn? River Deli on Joralemon romantic italian in Bklyn Heights has restaurant in brooklyn great homemade pasta. my wifes a vegetarian Or Locanda Vini e Olii in Clinton Hill is also great. 10:37 PM 10:41 PM 10:42 PM Tommaso Restaurant at 1464 86th St (old school) or Villabate-Alba (lessbensonhurst Thanks expensive) at 7001 Eighteenth Ave, both have veg options
Experiment Best Burger place near Grand Central PatroonBurger King Black Shack Burger Burger Heaven (69 sec) (115 sec) (110 sec for 2)
Experiment OMG! My 10:00 PM favorite place! Im at 84th and Amsterdam. Im looking for a Italian restaurant that isnt too expensive for a romantic date.10:02 PMYoud love Celeste on Amsterdamnear 84th -- pizza in a wood-firedoven. Or a few blocks away -Salumeria Rosi Parmacotto, 73rd andAmsterdam
Results and Lessons Learned • In shootouts, Tripo! matched competitors time and • Assumption conﬁrmed exceeded competitors quality
Hypothesis 3 Assumptions to test • Travelerswould pay for an app that • Travelers would pay $1.99 for provides them with a weekend of unlimited access access (via SMS) to a to Tripo! or $4.99 for a local expert advisor able month of access to respond to restaurant and nightlife requests in • A free weekend would entice less than 5 min travelers to try the service
Results and Lessons Learned • Conversion rate of 11% • Travelersare willing to pay for (5 sign-ups out of 44 visitors, expert, real-time advice ran test for 2 hours) • Need to further explore price• One customer interview points, business models yielded price point of $10/ question for high-quality service
Learning Summary Interested in real- Value proposition Travelers do not Real-time advice Travelers aretime advice from a better understood plan for restaurant from experts willing to pay forlocal expert when limited to and nightlife provide better service restaurants and quality results nightlife
Looking ahead Customer validation = customer acquisition Customer validation = scalable business model Customer validation = product-market ﬁt
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