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Final Report for OAP              Team Food Compass
Elevator Pitch    The Food Compass allows users to find restaurants orspecific menu items based on personal food preferenc...
USE CASES       Team Food Compass
Use Case #1Julie Smith is always looking for healthy foods. She registers a profile on TheFood Compass, indicating her foo...
Use Case #2   John Smith, an overweight sales manager in a big corporation, registers a  profile on The Food Compass, indi...
FEATURES /HYPOTHESES        Team Food Compass
Feature Description #1 Configure your profile based on food preferences, allergies and       dietetic needs and enjoy the ...
Hypothesis #1User want a service that helps them find foods nearby based on personal preferences (ie. food allergies, pric...
Results #1 Although 57.8% (11/19) respondents indicated they would find searching for foods based on dietary restrictions ...
Feature Description #2Once you have created a Food Compass profile unique to your preferences, easily share it with meal p...
Hypothesis #2 Users will want to fill out / share a personal food profile with meal planners and reservation makers (conci...
Experiment #2We posed this hypothesis to 31 respondents viaone (1) online survey and several face-to-face                 ...
Results #2Although the survey questions centered on using the Food Compass “while traveling,”the hypothesis has been valid...
Feature Description #3 Users will be incented to rate and recommend meals andrestaurants in exchange for coupons / deals a...
Hypothesis #3Deals and coupons are an essential part of the Food               Compass solution.                          ...
Experiment #3We posed this hypothesis to multiple respondents via two (2) online surveys and via a few face-to-face       ...
Results #3As of now following points came out after the survey1. Offering coupons is good for attracting users; given deal...
Hypothesis #4Restaurants require customer profile information and   statistical data to participate/share menu data.      ...
Experiment #4We posed this hypothesis to 19 respondents          via one online survey.                                Tea...
Results #4    The majority of respondents (15/19) are willing to share their profile data withrestaurants / businesses, ba...
Feature Description #5   After consumption, users can burn off excess calories with our  Burn It index. When users activat...
Hypothesis #5  Users are interested in having an activity ("Burn It Off“feature) recommendation integrated into the Food C...
Experiment #5We posed this hypothesis to several respondentsvia one online survey and several face-to-face                ...
Results #5Respondents were more interested in calorie spend than calorie intake.Because activity tracking is a related, bu...
Market AnalysisTotal Addressable Market (TAM):The typical American aged 8+ consumes an avg. of 4.2 commercially prepared m...
Market AnalysisMarket Statistics [1]:Number of fast food restaurants: 72,221Number of bars/clubs/drinking establishments: ...
Market AnalysisBarrier to entry for a technology change is low.Households (HH) with a pre-tax income of $70,000+ spent a t...
Market AnalysisFindings [2]:Mature (age 61+) diners are more likely than others to try a new restaurant or dish for aweekd...
Market AnalysisONLINE RESTAURANT SERVICES [6]Zagat.com: 333,962 / rank is 5,994Dine.com: 8,738 / rank is 90,031Opentable.c...
Market AnalysisDIET INDUSTRY [6]Weight Watchers: 4,715,662 unique visitors per month / rank is 337JennyCraig.com: 210,800 ...
Market AnalysisSources:[1] http://www.katzvaluation.com/documents/Full-Service-Restaurant.pdf[2] 2008 Market Research Stud...
Market Analysis            Team Food Compass
Revenue Streams• Subscription Fees (individuals)• Licensing Fees (hotels, travel agents, event planners, corporations)• Co...
Final ThoughtsWe plan to continue forward with the Food Compass for the next phase of our class;more research is needed re...
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Food compass: Final Report for OAP

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Food Compass, final report for Opportunity Analysis Project. Venture Lab / Technology Entrepreneur Class from Stanford.

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Transcript of "Food compass: Final Report for OAP"

  1. 1. Final Report for OAP Team Food Compass
  2. 2. Elevator Pitch The Food Compass allows users to find restaurants orspecific menu items based on personal food preferences (i.e. low-sugar options) and share those food preferences (via their profile) with meal planners and reservation makers. Team Food Compass
  3. 3. USE CASES Team Food Compass
  4. 4. Use Case #1Julie Smith is always looking for healthy foods. She registers a profile on TheFood Compass, indicating her food preferences, allergies, and dietetic needs in order to find nearby restaurants that match her profile. She agrees to receive (free) text alerts asking for her feedback after dining (in exchange for a 10% off coupon on next visit) where she’ll rate her overall food experience. If she signed up for the premium “Burn It” Index, she’ll also have the option of entering meal details (ie. lasagna, chocolate cake) in exchange for preferred activity recommendations. Team Food Compass
  5. 5. Use Case #2 John Smith, an overweight sales manager in a big corporation, registers a profile on The Food Compass, indicating his food allergies and preferences (dietary needs). He attends a vendor luncheon where the lunch organizer requested access to his food profile to learn his preferences (ie. allergic to shellfish); he accepted her share request. He also recently shared his food profile with the airline and travel agent (in-flight meal preference) as well as his hotel concierge so recommended restaurants will meet his dietary needs(low sugar) while traveling. Finally, his personal trainer was granted access to his food profile in order to analyze his eating and/or dining habits. Team Food Compass
  6. 6. FEATURES /HYPOTHESES Team Food Compass
  7. 7. Feature Description #1 Configure your profile based on food preferences, allergies and dietetic needs and enjoy the search results which are automatically tailored to your personal, pre-set preferences. For example, the Food Compass filters out high-calorie, high-sugarentrées if youre watching your diet or leaves out expensive meals when watching your wallet. Team Food Compass
  8. 8. Hypothesis #1User want a service that helps them find foods nearby based on personal preferences (ie. food allergies, price, healthy options, ratings, deals, etc.). Team Food Compass
  9. 9. Results #1 Although 57.8% (11/19) respondents indicated they would find searching for foods based on dietary restrictions to be useful, dietary restrictions and concerns are not a significant primary factor. Other important considerations are taste, price, location, etc. The survey results indicate that (when combined with social sharing options)respondents are more likely to submit their dietary preferences in exchange for faster response times, restaurant incentives or special accommodations. Therefore, dietaryrestrictions form a valid secondary factor for biasing search results (based on custom user profiles, but not necessarily as a primary search criterion). Team Food Compass
  10. 10. Feature Description #2Once you have created a Food Compass profile unique to your preferences, easily share it with meal planners (party hosts / caterers) and reservation makers (concierges, travel agents, office assistants, airlines, event planners, healthcare aides, personal trainers, friends and family) so they can easily plan meals that match your profile. Team Food Compass
  11. 11. Hypothesis #2 Users will want to fill out / share a personal food profile with meal planners and reservation makers (concierges,travel agents, office assistants, event planners, healthcareaides, caterers, friends and family) so they can easily plan meals that consider their food preferences, allergies or dietetic needs. Team Food Compass
  12. 12. Experiment #2We posed this hypothesis to 31 respondents viaone (1) online survey and several face-to-face interviews. Team Food Compass
  13. 13. Results #2Although the survey questions centered on using the Food Compass “while traveling,”the hypothesis has been validated via face-to-face interviews as well as survey results. Team Food Compass
  14. 14. Feature Description #3 Users will be incented to rate and recommend meals andrestaurants in exchange for coupons / deals and vice versa. Team Food Compass
  15. 15. Hypothesis #3Deals and coupons are an essential part of the Food Compass solution. Team Food Compass
  16. 16. Experiment #3We posed this hypothesis to multiple respondents via two (2) online surveys and via a few face-to-face interviews. Team Food Compass
  17. 17. Results #3As of now following points came out after the survey1. Offering coupons is good for attracting users; given deals must be good (obviously)and UI must be neat n clean.2. Coupons will also help restaurants with lower ratings to improve their quality or tosurvive.3. Users need an incentive to interact with the Food Compass while dining. Team Food Compass
  18. 18. Hypothesis #4Restaurants require customer profile information and statistical data to participate/share menu data. Team Food Compass
  19. 19. Experiment #4We posed this hypothesis to 19 respondents via one online survey. Team Food Compass
  20. 20. Results #4 The majority of respondents (15/19) are willing to share their profile data withrestaurants / businesses, based on certain limitations or pre-conditions (ie. speeding up orders, to receive incentives, to have their dietary needs met, etc.)The survey results validate the hypothesis that customer profile data will be available as an incentive for restaurants to participate and share menu data. Team Food Compass
  21. 21. Feature Description #5 After consumption, users can burn off excess calories with our Burn It index. When users activate this Burn It premium feature,they’ll receive a text alert offering user-preferred activities to help you burn the calories consumed. Example alert: It’s time to burn it. You consumed chocolate cake for dessert two hours ago! Walk two miles, do the laundry and dance with your partner for 30 minutes. Team Food Compass
  22. 22. Hypothesis #5 Users are interested in having an activity ("Burn It Off“feature) recommendation integrated into the Food Compass. Team Food Compass
  23. 23. Experiment #5We posed this hypothesis to several respondentsvia one online survey and several face-to-face interviews. Team Food Compass
  24. 24. Results #5Respondents were more interested in calorie spend than calorie intake.Because activity tracking is a related, but not vital, part of the Food Compass, we feelthe activity feature should be a premium one. We plan to offer users access to the"Burn It" Index where they can find fitness activities that will compensate for thecalories expended. Team Food Compass
  25. 25. Market AnalysisTotal Addressable Market (TAM):The typical American aged 8+ consumes an avg. of 4.2 commercially prepared meals perweek, according to Meal Consumption Behavior — 2000 [5]. That figure translates to morethan 1 billion commercially prepared meals consumed per week and 53.5 billion per year(Year 2000 numbers)The typical person consumes an average of 2.1 commercially prepared lunches per week,resulting in total annual consumption of 26.7 billion commercially prepared lunchesThe US has an adult population (age 15-65) of 206.8 million. 69.5 million people in theU.S. owned smart phones during the 3 months ending in February 2011 .Projecting from 2000-2001 numbers, estimated TAM for the Food Compass app is 207million users, with estimated total usage of 1.1 billion searches per week (combinedsmartphone and web application usage). Team Food Compass
  26. 26. Market AnalysisMarket Statistics [1]:Number of fast food restaurants: 72,221Number of bars/clubs/drinking establishments: 72,241Number of full-service restaurant businesses: 214,147Full-service Restaurants Revenue (2010): $178.1 billionFull-service Restaurants Profit (2010): $10.7 billion Team Food Compass
  27. 27. Market AnalysisBarrier to entry for a technology change is low.Households (HH) with a pre-tax income of $70,000+ spent a total of 50.5% of total foodexpenditure away from home, even though they comprised 17.0% of all HH [3]20.0% of industry revenue is estimated to be derived from business and business travelers,as well as from tourists, including international visitors.HH with income of more than $50,000 account for about 70.0% of the total personalexpenditure on food eaten away from the home. Of this group, those HH in the highestincome quintile provide about 30.0% of the total away from home food expenditure [4].There have been market changes and some demand for healthy foods and choices, awayfrom high fat, high salt and super-sizes meals, as the obesity epidemic continues to be raisedand recognized.There is currently still a growing number of households with high disposable income of$50,000 or above in the key groups 35- to 55-year-olds and baby boomers. Many have onlylimited time to cook and so are searching for good value and quality meals, and convenienceand service in a hospitable and friendly environment. Team Food Compass
  28. 28. Market AnalysisFindings [2]:Mature (age 61+) diners are more likely than others to try a new restaurant or dish for aweekday meal. The restaurant experience is also seen more as a social and family occasion,and like to share with family and friends, or coworkers28.4% of Generation Y diners prefer to use technology to place orders and pay for mealswithout interacting with counter staff (18.1% for Generation X, 12.1% for baby boomers,7.5% for matures)29% of Generation Y consumers indicated that they like to go to restaurants where the chefinteracts with guests (compared with 17.8% of baby boomers)Most Generation X’s and Y’s like to check a restaurants menu prior to making a reservation25% of Generation Xs and Ys said they like to make changes to the menu items (comparedto 14.5% of mature diners)[2] 2008 Market Research Study by Restaurants and Institutions Magazine Team Food Compass
  29. 29. Market AnalysisONLINE RESTAURANT SERVICES [6]Zagat.com: 333,962 / rank is 5,994Dine.com: 8,738 / rank is 90,031Opentable.com: 499,809 / rank is 4,029Menupages.com: 499,810Fodors.com: 633,170 / rank is 3,149TOTAL 1,975,489(x 10% capture of online restaurant locator industry = 197,448 prospective users) (Source: Compete.com) Team Food Compass
  30. 30. Market AnalysisDIET INDUSTRY [6]Weight Watchers: 4,715,662 unique visitors per month / rank is 337JennyCraig.com: 210,800 / rank is 9,565Nutrisystem.com: 810,334 / rank is 2,470TOTAL: 5,736,796(x 10% of dieting industry = 573,679)(Source: Compete.com) Team Food Compass
  31. 31. Market AnalysisSources:[1] http://www.katzvaluation.com/documents/Full-Service-Restaurant.pdf[2] 2008 Market Research Study by Restaurants and Institutions Magazine[3] US Census Bureau Data[4] US Census Household Expenditure Data[5] http://www.restaurant.org/tools/magazines/rusa/magarchive/year/article/?articleid=138[6] Compete.com Team Food Compass
  32. 32. Market Analysis Team Food Compass
  33. 33. Revenue Streams• Subscription Fees (individuals)• Licensing Fees (hotels, travel agents, event planners, corporations)• Corporate Sales / Membership Fees: HR departments for consistent company-wide F&B guidelines & reducing costs (employees use Food Compass to find pre-approved restaurants that meet their preferences).• Advertising Sales (restaurants, travel agencies, health care providers, dieticians,health clubs, personal trainers)• Sponsorships (National Restaurant Chains, Weight Watchers, evite, etc.)• Deals / Coupons percentage Team Food Compass
  34. 34. Final ThoughtsWe plan to continue forward with the Food Compass for the next phase of our class;more research is needed regarding:• The viability of the different revenue streams.• More in-field testing / face-to-face interviews, specifically targeting end users(corporate travel agents, hotel concierges, personal trainers, health clubs, etc.)• Après-meal alerts / feedback feature. We think there’s more to this feature thanmeets the eye. Team Food Compass
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