Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Share and Tell Stanford 2016

69,712 views

Published on

agile, business model, corporate innovation, customer development, lean, lean startup, lean launchpad, stanford, steve blank, video, engr 245

Published in: Education

Share and Tell Stanford 2016

  1. Lessons learned after 130 interviews Yegor Tkachenko, MS Marketing Analytics Machine Learning Eric Peter, CS & MBA Consumer Insight Expert Management Consulting Scott Steinberg, MBA Marketing Growth Strategy Management Consulting Karan Singhal, Undergrad CS Web Development User Interface Design Share&Tell
  2. Share&Tell Yegor Tkachenko, MS Marketing Analytics Machine Learning Eric Peter, CS & MBA Consumer Insight Expert Management Consulting Scott Steinberg, MBA Marketing Growth Strategy Management Consulting Karan Singhal, Undergrad CS Web Development User Interface Design Day 1 (Clarified) We create a way for consumers to make money by actively sharing their behavioral data and opinions. Through this data, we help companies unlock previously unattainable insights. Now We help retailers and CPG companies understand online shopping behavior. We do this by creating a platform for people to donate their Amazon shopping history to raise money for charity. 130 Interviews 3,500+ Survey responses
  3. Cost Structure Fixed - Infrastructure, servers, team of data scientists, corporate sales force, project managers & analysts, product & user experience development team Variable - Payment to consumers for use of their data, profit- sharing model (dividends) with consumers, consumer service reps Revenue Streams 1. Custom research studies 2. Per-feedback fees (surveys, video interviews, focus groups) 3. Sales of raw data / data with automated analytics on top 4. Subscriptions to the platform Pricing based on sample size/type, data type/amount, number of questions, feedback time Key Resources Key ActivitiesKey Partners Value Proposition Customer Relationships Channels Business Canvas - Week 1 Customer Segments Consumers • Millennials/students • Lower income consumers with smartphones • Existing research participants Enterprises • Marketing agencies, consulting • Marketing departments at large companies • Marketing departments at non- large CPG companies • Panel acquisition, retention, incentivization, quality control • Automated seamless insights extraction • Data security • Empowered customer service (for consumer) • Sales force, customer service knowledgable about market research design & execution • Historical granular data • Automated platform for seamless insights extraction • Expertise in market research methodology, execution, statistics Consumers • Profit sharing • Targeted ads in line with customer’s tastes • Sense of empowerment Enterprises • Unique data,analysis • Easy and fast way to do it Consumer • Website • Mobile app Enterprise • Direct web portal • Resold through market research agencies • Custom consulting & research design services Consumers • Getting paid for data that has already been shared, but from which individuals are not profiting • Provide sense of empowerment and control over data • Offers a natural, effortless way to share opinions • Feel heard and that opinion matters Enterprises • Linking real-behavior with opinions (vs. stated behavior) • Ability to follow up with consumer • Faster turnaround • Data API providers • Data aggregators • Marketing agencies • Panel participants blue = consumer black = enterprise
  4. What we thought: Enterprise VP blue = consumer black = enterprise Enterprise Value Proposition: Replace traditional survey providers by: ● Linking real behavior with opinions (vs. stated behavior) ● Ability to follow up with consumer ● Faster turnaround Key Resources • Historical granular data • Automated platform for seamless insights extraction Demographics ● Age? ● Gender? ● ... Behavior ● Where did you buy? ● What? How much? ● ... Emotions / Feelings ● Why did you buy? ● What matters to you? ● ... Survey Surveys are based on SELF REPORTED data
  5. What we did: Talk to companies who use surveys for market research Hypothesis: We can replace existing panel vendors if we have real behavioral data (as opposed to self-reported data) What we did: 12 Customer Discovery interviews with companies that conduct market research using surveys Enterprise Week 1-3
  6. What we found: Not that much pain with self-reported data... “Self-reported data isn’t great, but it’s directionally good enough.” “With real data, we’d get the same insight as we do now, but perhaps we’d be slightly more confident.” “In order to switch vendors, you need to be able to answer a question we can’t answer today” “We have to use [vendor] - we have a long term contract through our HQ." Enterprise Week 1-3
  7. What we found: Not that much pain with self-reported data... “Self-reported data isn’t great, but it’s directionally good enough.” “With real data, we’d get the same insight as we do now, but perhaps we’d be slightly more confident.” “In order to switch vendors, you need to be able to answer a question we can’t answer today” “We have to use [vendor] - we have a long term contract through our HQ." Enterprise Week 1-3 Adding behavioral data alone does not make us 10x better. We need to be able to answer a specific question that marketers can’t answer today
  8. So, we focused on changing the value prop to answer new questions for marketers How should I identify my consumer target (SMB Businesses) How do I better understand my consumer target? What is the path to purchase for online and omnichannel shopping? What are current online shopping trends? Customer Needs Identified through Customer Discovery: Enterprise Week 1-3
  9. So, we focused on changing the value prop to answer new questions for marketers How should I identify my consumer target (SMB Businesses) How do I better understand my consumer target? What is the path to purchase for online and omnichannel shopping? What are current online shopping trends? Customer Needs Identified through Customer Discovery: Enterprise Week 1-3 Value Proposition Enterprises • Linking real- behavior with opinions (vs. stated behavior) • Ability to follow up with consumer • Faster turnaround Value Proposition Enterprises • Identify target consumers to increase marketing ROI • Deeper and more accurate behavioral understanding of consumer segments • Understand online/omnichannel path to purchase • Understand online market trends at consumer level Week 1 Week 3 ✘
  10. What about the consumer?
  11. Cost Structure Fixed - Infrastructure, servers, team of data scientists, corporate sales force, project managers & analysts, product & user experience development team Variable - Payment to consumers for use of their data, profit- sharing model (dividends) with consumers, consumer service reps Revenue Streams 1. Custom research studies 2. Per-feedback fees (surveys, video interviews, focus groups) 3. Sales of raw data / data with automated analytics on top 4. Subscriptions to the platform Pricing based on sample size/type, data type/amount, number of questions, feedback time Key Resources Key ActivitiesKey Partners Value Proposition Customer Relationships Channels What we thought: Consumer VP Customer Segments Consumers • Millennials/students • Lower income consumers with smartphones • Existing research participants Enterprises • Marketing agencies, consulting • Marketing departments at large companies • Marketing departments at non- large CPG companies • Panel acquisition, retention, incentivization, quality control • Automated seamless insights extraction • Data security • Empowered customer service (for consumer) • Sales force, customer service knowledgable about market research design & execution • Historical granular data • Automated platform for seamless insights extraction • Expertise in market research methodology, execution, statistics Consumers • Profit sharing • Targeted ads in line with customer’s tastes • Sense of empowerment Enterprises • Unique data,analysis • Easy and fast way to do it Consumer • Website • Mobile app Enterprise • Direct web portal • Resold through market research agencies • Custom consulting & research design services Consumers • Getting paid for data that has already been shared, but from which individuals are not profiting • Provide sense of empowerment and control over data • Offers a natural, effortless way to share opinions • Feel heard and that opinion matters Enterprises • Linking real-behavior with opinions • Ability to follow up with consumer - Faster turnaround • Give additional context in traditional surveys • Data API providers • Data aggregators • Marketing agencies • Panel participants blue = consumer black = enterprise Consumer Value Proposition Hypothesis: Get paid for your data Feel in control of your data Feel heard and that opinions matter ...and, that consumers are willing to provide all these data types: • Social media likes & posts • Email purchase receipts • Credit card purchase history • Amazon.com purchase history • GPS location history • Web and search history
  12. First consumer test Hypothesis: People will provide their data and opinions for money Tested through: ~25 Customer Discovery focused consumer interviews Consumer Week 1-3
  13. Experiment: Take an MVP on an iPad to the mall Consumer Week 1-3
  14. What we learned Hypothesis: People will provide their data and opinions for money Consumer Week 1-3 Findings: People will provide data and opinions for money, BUT Only younger and poorer consumers were interested Cash-based model had other problems too: ● Doesn’t support retention and engagement ● Misaligned incentives ● Not scalable to get to large # of consumers Tested through: ~25 Customer Discovery focused consumer interviews
  15. As a result: What if we offered equity instead of cash? Solves all business needs! ● panel retention and engagement ● identity verification ● quality of data Consumer Week 4 Google Consumer Survey: n = 500
  16. Oh Wait… Need to Isolate Variables Always be skeptical of your data! Consumers aren’t interested in concept of being a partial owner - they cared about the extra cash! Designing a good experiment just saved us 49% of our equity...phew! Consumer Week 4
  17. Value Proposition Consumer: • Getting paid for data that has already been shared, but from which individuals are not profiting • Provide sense of empowerment and control over data • Offers a natural, effortless way to share opinions • Feel heard and that opinion matters By Week 4, We Had No Idea What Consumer Value Prop Should Be Value Proposition Consumer: • Getting compensated for data that has already been shared • Provide sense of empowerment, control over data • Partial ownership of company Week 1-4 Consumer Week 1-4 Consumer: • Control over data • ??? Value Proposition Week 1 Week 3 Week 4
  18. Let’s first focus on narrowing down enterprise value prop to see what data we need.
  19. What we did: Customer Validation! How should I identify my consumer target (SMB Businesses) How do I better understand my consumer target? What is the path to purchase for online and omnichannel shopping? What are current online shopping trends? ✘ ✘ Enterprise Week 4 14 more enterprise interviews to (in)validate our hypothesized value props and identify the most acute needs
  20. “Great value prop guys, but I challenge you - if you had to do something tomorrow as an MVP, what would it be? This is a LOT to do!” Note: Quote paraphrased, concept of “Big Idea” was likely referenced Key learning: A startup can’t do everything. It needs to do one thing well! Enterprise Week 4
  21. Well, why not focus on data that’s easiest to get? Most Sensitive Least Sensitive Google Survey Consumer Week 5
  22. And heard from companies that Amazon data is big pain point Enterprise Week 5
  23. As a result: An aha moment... Share & Tell… ...helps better understand your target's online & omnichannel shopping & purchasing behavior • What is purchased on Amazon.com? • What is my online/omni market share? Why? • Where else does my target shop? Why? • What does my target do before they buy? What is their shopping path? Why? • What products does my customer buy / not buy? What do they buy with my product? Why? ...helps better understand your target's persona / where to reach them • What online behaviors (sites, apps, etc…)? • What media consumption habits? • What do they search for online? • What activities, interests, hobbies? • What demographics? ...provides ability to more directly and narrowly communicate with your target • Direct messaging / promos on S&T platform • Better targeting on existing ad networks Enterprise Week 5-6
  24. Cost Structure Fixed - Infrastructure, servers, team of data scientists, corporate sales force, project managers & analysts, product & user experience development team Variable - Payment/donations for use of their data, consumer service reps Revenue Streams 1. Subscriptions to insights / platform 2. Per-survey fees 3. Custom research studies 4. Linking data to client databases Pricing based on sample size/type, data type/amount, number of questions, feedback time Key Resources Key ActivitiesKey Partners Value Proposition Customer Segments Customer Relationships Channels Resulting Business Canvas Consumers • Smartphone using consumers who shop online • Millennials • Existing research participants • People who currently give to charity Enterprises • Retail (traditional) • Retail (e-commerce) • CPG with online sales • Panel acquisition, retention, incentivization, quality control • Automated seamless insights extraction • Data security • Empowered customer service (for consumer) • Sales force, customer service knowledgable about market research design & execution • Historical granular data • Automated platform for seamless insights extraction • Expertise in market research methodology, execution, statistics Consumer • Website • Mobile app Enterprise • Direct web portal supported by research- experience B2B sales force • Projects sold through market research & strategy firms Consumers • Get: Charities send invitations • Get/Keep: Shopping discovery + targeted discounts app • Keep: Reports / comparisons of your data Enterprises • Get:partnership,telesales,PR • Keep: Unique data, analysis • Easy and fast way to do it Consumers • Feel good by donating data to charity • (potentially) Service to discover, get discounts on, and buy stuff online Enterprises • Understand purchasing trends on Amazon by demographic group • Data API providers • Data aggregators • Marketing agencies • Panel participants • Charities/non-profits Enterprise Week 5-6 blue = consumer black = enterprise • Understand purchasing trends on Amazon by demographic group • Retail (traditional) • Retail (e-commerce) • CPG with online sales
  25. As a result: Develop low-fi MVP Enterprise Week 5-6
  26. Now, how do we incentivize consumers to provide Amazon data? Consumer Week 5
  27. We identified a few possible alternatives to cash... Pay cash Provide a valuable service $5 / $10 cash Donate your data (to benefit a charity) Receive targeted promotions Personalized product recommenda tions ✘ Had learned previously consumers more willing to share data if they get some intrinsic value Consumer Week 5
  28. What we did: 10+ Customer Discovery interviews...and 2,000+ survey responses Consumer Week 5
  29. What we found: “Donate your data” best meets the business’s needs Gets Amazon data? Retention / engagement? Quality? Large #? Outcome $5 / $10 cash ✔ Cash is king! ✘ May be transactional / one-shot deal ✘ Limits to low income ✔ ~>50% interested Kill for now or use in combo w/ donations Donate your data ✔ Interest in ‘doing good’ ✔ Donation implies opp to ask for future donation ✔ Consumer leads verified through charities ✔ ~27% interested Focus for class; need to understand impact of bias Targeted promos ✘ Does not solve major pain, already available ✔ Creates clear gain w. reason to come back ✔ Can verify respondent behavior ✘ Quant test running, qualitatively poor reaction Test for “keep / grow” insteadProduct recs ✘ Limited interest - does not solve pain, not 10X better than others ✔ Creates clear gain w. reason to come back -- Unclear if able to verify respondent • Need 0.75% of TAM to register (1M / 150M) • Of those interested, ~3% will register • Implies >25% interested Consumer Week 5
  30. What we found: Consumers skeptical of donation scams “I’d donate my Amazon data to raise money for charity X, but only if that charity asked me too” “I probably would not donate to a random startup unless I knew for sure that they were legit” Nonprofits should send out communication asking people to donate their data Nonprofits are a customer acquisition channel and a new customer segment Consumer Week 5
  31. As a result: 3-sided market Consumer Week 6
  32. Value Proposition Consumer: • Control over data • ??? Consumer: • Feel good by donating data to charity • Doesn’t cost money to donate Value Proposition Week 3 Week 5 Resulting BMC changes (I) Consumer: • Millennials & students • Lower income consumers with smartphones • Existing research participants Segment Consumer: • Millennials • People who donate to charity Segment Consumer Week 6 ✘ ✘
  33. Value Proposition Non-Profit: • A new revenue stream • A new way to engage with donor base • A way to get donations without pushback Value Proposition Week 3 Week 5 Resulting BMC changes (II) Segment Non-Profit: • All non-profits Segment Consumer Week 6
  34. Resulting BMC changes (III) Consumer Week 6 Consumer: • Targeted ads in line with customer’s tastes • Sense of empowerment Cust. Relationship Consumer: • Get: Charities send invitations Cust. Relationship Need to test this ✘
  35. eCommerce Data & Insight Companies Data aggregators Online Donation Tools and Platforms Slice, Clavis, Profiteero, One Click Retail, Profiteero, Return Path, Paribus? Data Wallet, Datacoup, Infoscout, Axciom, Experian, LiveRamp, SuperFly Razoo, CrowdRise, Causes, Survey Monkey, One Big Tweet, GoodSearch, AmazonSmile Marketing research agencies TNS Qualitative, , Conifer Research, Horowitz Research, Nielsen, Kantar, IPsos, dunnhumby Our Competitive Set Has Evolved too Removed through pivots Online Survey Tools Traditional survey panels Online qualitative research Behavioral Consumer Panels (w/ or w/o surveys) Nielsen, NPD, IRI, LuthResearch, VertoAnalytics, RealityMine, comScore SHARE & TELL Consumer Week 6
  36. Nonprofits might not be the right route What we did: Interviewed 10+ nonprofits Tested email campaign to 60 nonprofits to gauge interest What we learned: ● Only nonprofits who value smaller donations (<$100) from larger base of people were interested in the model ● Nonprofits are slow to make decisions and risk- averse So what? Focus more efforts on testing viability of direct to consumer route. Key hypothesis to test: Can we build enough trust through social media and website? Nonprofits Week 7-9 Non-profits may not be most efficient consumer acquisition path.
  37. What we did: Tested ‘direct to consumer’ using a high fidelity MVP... https://www.datadoesgood.com Consumer Week 7-9
  38. What we learned: ‘Direct to consumer’ might be a viable route Arrived to the landing page Clicked ‘donate now’ Logged in with Facebook Shared Amazon data Filled out demographics 100% ~18% ~6% ~6% ~5% ~80% ~95% ~55% Choose a charity ~11% ~60% 25% Consumer Week 9
  39. Cost Structure Fixed - Infrastructure, servers, team of data scientists, corporate sales force, project managers & analysts, product & user experience development team Variable - Payment/donations for use of their data, consumer service reps Revenue Streams 1. Subscriptions to insights / platform 2. Per-survey fees 3. Custom research studies 4. Linking data to client databases Pricing based on sample size/type, data type/amount, number of questions, feedback time Key Resources Key ActivitiesKey Partners Value Proposition Customer Segments Customer Relationships Channels Consumers • Online shoppers • Current charity givers • Millennials • Existing research participants Enterprises • Buyers at e-commerce retailers • Marketers at CPG with online sales Nonprofits?? • Hungry for donations and values small donations from large # of donors • Private donations are main revenue stream • Donor acquisition?? • Donor retention and engagement?? • Data quality control • Data security and storage • Automated analytics • Custom analytics • Sales force • Legal • Physical - workspace, servers • Additional human (short-term) - Full- stack software engineer, Database architect, Security consultant, Legal Consultant, Advisors/Industry Movers (long-term) - Sales team, Analytics team, Security team, Engineering team, Advisors • Intellectual - Trademarks, Contracts with clients, Proprietary analytic tools, Software copyright • Financial - angel/venture funding Consumers • Website • Mobile app Enterprises • Web portal supported by B2B sales force • Projects through market research & strategy firms Nonprofits?? • Web portal Consumers • Get: Social media campaigns & charities send invitations • Keep: Reports / comparisons of your data Enterprises • Get:partnership,telesales,PR • Keep: Unique data, analysis • Easy and fast way to do it Nonprofits?? • Get: telesales, PR Consumers • Feel good by donating data to charity • Donating is free & easy Enterprises • Understand purchasing trends on Amazon by demographic group. brand preference Nonprofits?? • A new revenue stream • A new way to engage with donor base • A way to get donations without pushback Short Term: • Charities/non-profits • Nonprofit hubs/associations • Legal • Other collectors of online purchase history Long Term • Data API providers • Data aggregators • E-commerce retailers • Ad networks and programmatic ad buyers? Final Business Model Canvas Week 10
  40. So...what’s next... We are going to continue working on this after the class. Can we gain traction with consumers? Several additional experiments we want to run incorporating feedback from our MVP. ● Facebook “nominations” ● Linking more directly to causes ● Many improvements to the MVP Can we get a letter of intent from any businesses? We continue to hear companies say they are interested and that this data is valuable. Is one willing to sign a non- binding letter of intent First Priority Second Priority
  41. Thank you, George!
  42. Appendix
  43. What we learned: Refined value proposition for enterprise... Share & Tell… ...helps better understand your target's online & omnichannel shopping & purchasing behavior • What is purchased on Amazon.com? • What is my online/omni market share? Why? • Where else does my target shop? Why? • What does my target do before they buy? What is their shopping path? Why? • What products does my customer buy / not buy? What do they buy with my product? Why? ...helps better understand your target's persona / where to reach them • What online behaviors (sites, apps, etc…)? • What media consumption habits? • What do they search for online? • What activities, interests, hobbies? • What demographics? ...provides ability to more directly and narrowly communicate with your target • Direct messaging / promos on S&T platform • Better targeting on existing ad networks Enterprise Week 4
  44. ...for 3 generic enterprise segments Enterprise Week 4 Retailers Traditional E-Commerce 1 2 CPG With online sales Without online sales 3
  45. What is market research? Comes in many forms... 1. Surveys to understand consumer opinions / emotions 2. Data to understand market trends Initial hypothesis: “disrupt” survey-based market research
  46. A quick primer: How do surveys work? What features do my customers care about? 1 Business asks a question about their customer What does my most valuable customer look like? What drives customer loyalty?
  47. A quick primer: How do surveys work? 2 Market research team writes a survey that will inform the answer Demographics ● Age? ● Gender? ● ... Behavior ● Where did you buy? ● What? How much? ● ... Emotions / Feelings ● Why did you buy? ● What matters to you? ● ... Survey 5 - 10 minutes of questions 10 - 15 minutes of questions
  48. A quick primer: How do surveys work? 3 Survey sent to consumers through a ‘panel provider’ Demographics ● Age? ● Gender? ● ... Behavior ● Where did you buy? ● What? How much? ● ... Emotions / Feelings ● Why did you buy? ● What matters to you? ● ... Survey $ / person Panel ProviderMarket Research team
  49. Demographics ● Age? ● Gender? ● ... Behavior ● Where did you buy? ● What? How much? ● ... Emotions / Feelings ● Why did you buy? ● What matters to you? ● ... Survey A quick primer: How do surveys work? 4 Consumers answer survey based on their memory Panel ProviderMarket Research team Self reported data
  50. A quick primer: How do surveys work? 5 Market research team analyzes data to develop an answer Market Research team Insight & recommended business action
  51. Demographics ● Age? ● Gender? ● ... Behavior ● Where did you buy? ● What? How much? ● ... Emotions / Feelings ● Why did you buy? ● What matters to you? ● ... Survey ...Where we thought we fit in 4 Consumers answer survey based on their memory Panel ProviderMarket Research team 3 Survey sent to consumers through a ‘panel provider’ Why can’t this be based on actual (vs. self reported) data?
  52. Demographics ● Age? ● Gender? ● ... Behavior ● Where did you buy? ● What? How much? ● ... Emotions / Feelings ● Why did you buy? ● What matters to you? ● ... Survey ...Where we thought we fit in 4 Consumers answer survey based on their memory Panel ProviderMarket Research team 3 Survey sent to consumers through a ‘panel provider’ ...let’s be a “next gen” panel provider that merges real data with opinions
  53. ...Where we thought we fit in What data? • Social media likes & posts • Email purchase receipts • Credit card purchase history • Amazon.com purchase history • GPS location history • Web and search history Opinions how? • Record short video / audio clips • Take <5 min surveys • Write reviews • 1-1 text chats
  54. Other learnings
  55. Presenting Share the key insights that led to a decision or answer. Don’t just share the answer Example: Equity Idea We learned a, b, & c...therefore we want to do “x” VS. We want to do “x”. Here is some rationale for why. Preempt question the audience might ask and prepare responses. Don’t bullshit if you don’t know the answer. It’s okay to say need time investigate it. 1 2
  56. Group work 1. Set up regular recurring meetings at least twice a week 1. Carefully consider if the task is best performed by a group or by an individual a. Everyone wants to participate in decision making, but it is often more efficient if a single person completes 80% of the task and the group then finishes the rest 1. If there is any tension, discuss it explicitly 1. Don’t take criticism of your ideas personally 1. Humor helps
  57. Launchpad Methodology/Process 1. Applying the scientific method to business model is extremely useful a. treating all ideas as hypotheses prevents attachment to bad ideas i. also encourages rapid iteration to get to better ideas faster b. using MVPs as tests of ideas rather than finished products avoids wasting tons of development time 1. Interviews a. what people initially say is not what they would actually do i. need to push commitment to see what they actually do b. interviews with experts are a quick way to get a lay of an industry c. it’s surprisingly easy to get interviews with experts with a warm intro, student status, and the purpose of learning as much as we can d. need to clarify customer segment as early as possible to interview the right people i. early interviews should focus on figuring out who they are

×