1. Good Odds Slots
Cohort 4, Team 18
David Reiss-Mello, Pranav Shrestha, Owen Long
Interviews since last class: 14
Total interview count: 54
2. Business Model Canvas - Day 1
Partnering with businesses
to spend lottery winnings
(e.g. Starbucks).
Online Transaction service
(e.g. Stripe)
Ad Agencies to earn
gambling credits by
watching ads
Product Development
Marketing
Entertainment/Newness
Risk reduction: Better form
of gambling
Gambling Transparency
Brand: Funny
Legal council
Software Engineers
Online Marketing
TV + Radio
Social Media
Influencers + college FB
pages
Self-Service
2/3 customers win 1st time
they play
Generally: Mass Market
People who gamble online
People who make in-app
purchases
Potentially non-gamblers
Variable Costs: Transaction costs
Fixed Costs: Legal fees, Online advertising
Advertising
Potentially freemium
Potentially taking a cut/brokerage fees
3. What we thought about customer segments...
Results
- People were suspicious,
even when ad-only
business model was
explained
- Funny = suspicious →
Preferred transparency
- Very few cared the
expected value is 0
Hypothesis
- Mass market like
QuizUp
- Funny advertising
campaign
- Everyone would play a
lottery with 0 expected
value
Experiment
- Ask customers if they
would play
- Ask customers what
type of campaign they
were most likely to
respond to
- Ask if expected value
being 0 mattered
4. Business Model Canvas - Day 2
Partnering with businesses
to spend lottery winnings
(e.g. Starbucks).
Online Transaction service
(e.g. Stripe)
Ad Agencies to earn
gambling credits by
watching ads
Product Development
Marketing
Entertainment/Newness
Gambling Transparency
Social Gambling
Better form of gambling
Brand: Self-aware / Funny
Legal council
Software Engineers
Online Marketing
TV + Radio
Social Media
Influencers + college FB
pages
Social gaming
Gamification - Visual impact
Streaks
Self-service
Generally: Mass Market
- Males
- Focus on college
students
People who gamble online
People who make in-app
purchases
Potentially non-gamblers
Variable Costs: Transaction costs
Fixed Costs: Legal fees, Online advertising
Advertising
Potentially freemium
Potentially taking a cut/brokerage fees
5. Current Customer Segmentation
$100 Gamblers $10 Gamblers $1 Gamblers
Bio:
- Already Gamble
- High income or very risk-
seeking
- Don’t care about expected
value
- Aren’t suspicious about
gambling ads
Bio:
- Don’t gamble, but would if
gambling apps were more
transparent
- Comfortable with math to
realize not a scam
- Semi-suspicious of gambling
apps, but would still download
Bio:
- Risk averse: never gamble
- Extremely suspicious of getting
scammed.
- Don’t calculate expected value
Value Proposition:
- Newness: odds above 50%
- Profit > fun
- Like betting large sums of
money without large risk
Value Proposition:
- Entertainment
- Chance to make money
- Playing with friends
Value Proposition:
- Being part of the fad
- Would not bet more than $5
6. Business Model Canvas - Day 3
Partnering with businesses
to spend lottery winnings
(e.g. Starbucks). Offer
exclusive discounts
Online Transaction service
(e.g. Stripe)
Ad Agencies to earn
gambling credits by
watching ads
Product Development
Legal Research
Marketing
$100 Gambler: Newness
(odds are above 50%), profit
> fun
$10 Gambler: Risk
Reduction + Transparency,
Social, fun > profit, wants to
play against friends
Brand: Transparent
Social Gambling
Brand: Self-aware / FunnyLegal council
Software Engineers
Online Marketing
$100 Gambler: Gambling
apps, Instagram, TV
$10 Gambler: Youtube,
Reddit, Instagram
TV + Radio
Influencers + college FB pages
Social gaming
Gamification - Visual impact
Streaks
Self-service
*For the purposes of the class,
the prime focus was college
students
The $100 gambler
- Already Gambles
The $10 gambler
- Hasn’t gambled before.
Plays because risk is low,
fun, and social
- Somewhat interested in math
(engineers). Confident isn’t
getting cheated
- Seem to be men
The 1$ Gambler:
- Plays for the Fad
Mass Market
Variable Costs: Transaction costs
Fixed Costs: Legal fees, Online advertising
Advertising
Entry fees on large bets
Small transaction fees
Freemium
7. What we thought of revenue model
Initial Hypothesis:
Simple.
1. Set the odds of winning at exactly ⅔
2. Set the payout at 1.5x, making the expected value and our cut zero
3. Collect revenue purely through ads
8. Our revenue model journey
Day 1
Ads only
Unsustainable
eCPM between $1.03 - $9.26
Ads + Transaction Fees
Experiment: Ask if prefer 3%
transaction fee when buying
ticket or when receiving payout
Result: People hated both options
Day 2
Ads + Freemium
Experiment: Ask people if they
would pay for ads free, ability to
play more rounds, and place
higher bets
Result: People were unwilling to
pay
Day 3
Ads + Odds
Experiment: Coded Monte-Carlo
Simulation in Python
95% Confidence Interval:
[$8.568-$8.949]
Day 4
9. Business Model Canvas - Day 4
Partnering with businesses
to spend lottery winnings
(e.g. Starbucks). Offer
exclusive discounts
Online Transaction service
(e.g. Stripe)
Ad Agencies to earn
gambling credits by
watching ads
Product Development
Legal Research
Marketing
$100 Gambler: Newness
(odds are above 50%), profit
> fun
$10 Gambler: Risk
Reduction + Transparency,
Social, fun > profit, wants to
play against friends
Brand: Transparent
Social Gambling
Brand: Self-aware / FunnyLegal council
Software Engineers
Online Marketing
$100 Gambler: Gambling
apps, Instagram, TV
$10 Gambler: Youtube,
Reddit, Instagram
TV + Radio
Influencers + college FB pages
Social gaming
Gamification - Visual impact
Streaks
Self-service
*For the purposes of the class,
the prime focus was college
students
The $100 gambler
- Already Gambles
The $10 gambler
- Hasn’t gambled before.
Plays because risk is low,
fun, and social
- Somewhat interested in math
(engineers). Confident isn’t
getting cheated
- Seem to be men
The 1$ Gambler:
- Plays for the Fad
Mass Market
Variable Costs: Transaction costs
Fixed Costs: Legal fees, Online advertising
Reduction of odds - from ⅔ to 66%
Advertisements - Gambling Advertising Network
Entry fees on large bets
Small transaction fees
Freemium
10. Final Business Model Canvas
Partnering with businesses
to spend lottery winnings
(e.g. Starbucks). Offer
exclusive discounts
Online Transaction service
(e.g. Stripe)
Ad Agencies to earn
gambling credits by
watching ads
Product Development
Legal Research
Marketing
Web Design
Licenses
$100 Gambler: Newness
(odds are above 50%), profit
> fun
$10 Gambler: Risk
Reduction + Transparency,
Social, fun > profit, wants to
play against friends
Brand: Transparent
Social Gambling
Brand: Self-aware / Funny
Legal council
Software Engineers
- Web developers
- UI/UX Design team
- Cyber-security
Online Marketing
$100 Gambler: Gambling
apps, Instagram, TV
$10 Gambler: Youtube,
Reddit, Instagram
TV + Radio
Influencers + college FB pages
Mostly positive first
experiences => Viral loop
Social gaming
Gamification - Visual impact
Streaks
Self-service
*For the purposes of the class,
the prime focus was college
students
The $100 gambler
- Already Gambles
The $10 gambler
- Hasn’t gambled before.
Plays because risk is low,
fun, and social
- Somewhat interested in math
(engineers). Confident isn’t
getting cheated
- Seem to be men
The 1$ Gambler:
- Plays for the Fad
Mass Market
Variable Costs: Transaction costs (Stripe 3.5% )
Fixed Costs: Legal fees, Online advertising, Software Developers
Reduction of odds - from ⅔ to 66%
Advertisements - Gambling Advertising Network
Entry fees on large bets
Small transaction fees
Freemium
12. Next steps
Customer Validation
- Generate a sample marketing campaign and measure interaction rates
Revenue Streams
- Research 60% vs 66%
- Put demo in front of people and record behavior to model revenue
Product Design
- Spice up MVP: add slot machine
- Release game without financial transactions
Hinweis der Redaktion
Big Idea is to test whether customers actually like the transparency and/or the better odds