The document summarizes the development of a political engagement platform called Politik Inn over 5 days. On Day 1, it outlined the problem, solution, value propositions, and assumptions. User engagement grew over the first few days but then declined. The platform pivoted to focus on user-generated ratings of politicians and addressing local issues. Mockups of a rating system were created. The opportunity is to connect the 200,000 people in the local area with housing issues to collectively address problems.

1. Politik Inn
-- A platform to connect the masses with the local politicians
Total # of interviews : 52
Initial interviews: 10
Day 1: Users -18
Day2: Users -7 ,Politicians - 1
Day 3: Users - 2 ,Influencers - 3
Day 4: Users - 5 , Politicians - 1
Day 5: Users: 5,Politician (over phone) - 1
Aditya Kariappa
Asli Ehliz
Natalia Pastrana
Mohar Chakrabarty

2. Business Canvas: DAY 1
Problem Solution Key Value Proposition Unfair Advantage Customer Segment/User Types
1) No central repository to
know and connect to our
local politicians.
2) Low interest from
masses in politics.
1) Create a dynamic
repository (updated by
users consistently) of
related content for the
political eco system.
2) Increase engagement
and interactions between
voters and politician.
3) Connect the entire
political eco system.
1) Will increase
transparency
2) Will reduce
corruption
3) Will connect
politicians with the
mass
4) Politicians can in turn
use this for their
campaign and voter
research
1) Blue Ocean: No major
competitors as of now.
1) For the millennial and Gen X
2) Politically active people
3) Two sided market: For the entire political eco system
such as
Politicians at all levels
Voters/Common People
Political Parties
Politicians who contested and lost
Political scientists
Journalist/reporters specialized on politics
public policy makers/decision makers
Macroeconomists
Professors/Experts/Authors related to this field
Key Metrics Channels
1) No. of politicians who
signed up
2) Site traffic
3) No. of users
4) Engagement metrics
(comments/likes, etc)
1) Own WebPages and
mobile apps along with
datacenters.
2) Will be integrated with
all leading social media
channels
and digital newspapers
Cost Structure Revenue Streams
-- IT Costs
-- Labor Costs
-- Floor Space (Office Costs)
-- Advertisement Costs
Advertising
Local (Pay Per Click)
Sponsored Ads (Pay Per Click)
Brand Advertising
Display Ads (Pay Per Click)
Banner Ads (Pay Per Click)
Sponsored Ads (Pay Per Click)
High price for expert, extreme and analogous users (Political Journalist, Public policy
makers, Professors, academicians)
Price for no advertisements
• Resale of data (APIs, Email, mobile ads )
• Retargeted Ads
• Tiered pricing
• Partnerships
• % of donations (Pay for Performance)
• Subscription Model

3. Top 5 Riskiest Assumptions for Day2
• There is a need (pain points) for this kind of a
platform
• Users would like to have this kind of a platform.
Do they actually see some kind of a value
proposition from a platform like this
• The end users will use this product
• When end users will use this product, politicians
will use this product
• Influencers sees some value proposition from this
kind of a platform

4. Business Canvas: DAY 2
Problem Solution Key Value Proposition Unfair Advantage Customer Segment/User Types
1) No central repository to
know and connect to our
local politicians.
2) Low interest from
masses in politics.
1) Create a dynamic
repository (updated by
users consistently) of
related content for the
political eco system.
2) Increase engagement
and interactions between
voters and politician.
3) Connect the entire
political eco system.
-
) Will increase transparency
2) Will reduce corruption
3) Will connect politicians
with the mass
4) Politicians can in turn
use this for their campaign
and voter research
A space where
their voices
could be heard
by local elected
authorities.
1) Blue Ocean: No major
competitors as of now.
Users- CLASSIFIED BY DEMOGRAPHIC ATTRIBUTES
1) Age- 18- 65
2) Living in Brooklyn, Manhattan or NJ
3) Student, working part time or full time
Key Metrics Channels
1) No. of politicians who
signed up
2) Site traffic
3) No. of users
4) Engagement metrics
(comments/likes, etc)
1) Own WebPages and
mobile apps along with
datacenters.
2) Will be integrated with
all leading social media
channels
and digital newspapers
Cost Structure Revenue Streams
-- IT Costs
-- Labor Costs
-- Floor Space (Office Costs)
-- Advertisement Costs
Advertising
Local (Pay Per Click)
Sponsored Ads (Pay Per Click)
Brand Advertising
Display Ads (Pay Per Click)
Banner Ads (Pay Per Click)
Sponsored Ads (Pay Per Click)
High price for expert, extreme and analogous users (Political Journalist, Public policy
makers, Professors, academicians)
Price for no advertisements
• Resale of data (APIs, Email, mobile ads )
• Retargeted Ads
• Tiered pricing
• Partnerships
• % of donations (Pay for Performance)
• Subscription Model

5. Risky Assumptions for Day3
• People who are tech savvy, 18-25 year old will
be interested in connecting politicians online
• People would like to express their thoughts
irrespective of whether they like or dislike
politicians
• People in NYC are interested in politics and
they like to address issues for the community
• Politicians care about the issues of the
common masses

6. Business Canvas: DAY 3
Problem Solution Key Value Proposition Unfair Advantage Customer Segment/User Types
1) No central repository to
know and connect to our
local politicians.
2) Low interest from
masses in politics.
1) Create a dynamic
repository (updated by
users consistently) of
related content for the
political eco system.
2) Increase engagement
and interactions between
voters and politician.
3) Connect the entire
political eco system.
1) Will increase
transparency
2) Will reduce corruption
3) Will connect politicians
with the masses
4) Politicians can in turn
use this for their campaign
and voter research
1) Blue Ocean: No major
competitors as of now.
Consumers
Male
Age 45+
Live in NYC
Registered voter but stopped voting
Interest in politics
Concern about safety (crime), cleaning and housing
issues
Key Metrics Channels
1) No. of politicians who
signed up
2) Site traffic
3) No. of users
4) Engagement metrics
(comments/likes, etc)
1) Own WebPages and
mobile apps along with
datacenters.
2) Will be integrated with
all leading social media
channels
and digital newspapers
Cost Structure Revenue Streams
-- IT Costs
-- Labor Costs
-- Floor Space (Office Costs)
-- Advertisement Costs
Advertising
Local (Pay Per Click)
Sponsored Ads (Pay Per Click)
Brand Advertising
Display Ads (Pay Per Click)
Banner Ads (Pay Per Click)
Sponsored Ads (Pay Per Click)
High price for expert, extreme and analogous users (Political Journalist, Public policy
makers, Professors, academicians)
Price for no advertisements
• Resale of data (APIs, Email, mobile ads )
• Retargeted Ads
• Tiered pricing
• Partnerships
• % of donations (Pay for Performance)
• Subscription Model

7. Work Flow for Community Issues
Mayor
Town Clerk
Committees
Community
Service Team
Constituent
Representative
Chief Of Staff
Mayor
Secretary

8. Risky Assumptions for Day 4
• Target customer profile will be interested in
communicating with politicians if there is a
platform that they can address the housing
issues
• This platform will reduce the time to delegate
those issues to Councils
• The Chief of Staff is the person who is in
charge to solve the citizens main concerns

9. District Council
email
Letter
twitter
Response Time Test
+1 day, No response
Facebook
1 day, No response
Webpage- format
1 day, No Response
1day,No posting unless he is connected
1 day, Same Day NYC District Council but still waiting for response from authority
No Response Yet

10. Business Canvas: DAY 4Key Partners Key Activities Key Value Proposition Customer
Relationships
Customer Segment/User Types
• Political Journalist
• Early Adopters
• Mayors
• Chief of Staff
• Director of
Community Services
•. Development of
the platform
• Marketing and
Advertising
•Gathering the data
the mayors and
chief of staff and
related the
authorities
regarding the
housing issues
• Enable the users to
communicate their pain
point about housing issues
directly to the politicians
with a quicker response
time
• Empower the users, so
their collective voices will
be heard by the related
authorities
• Trust the platform
• Community
Manager
• Retentive
Consumer
Male
Age 45+
Live in New York Metro Area
Registered voter but stopped
voting
Interest in politics
Continuous struggle with
housing issues
Key Resources Channels
• IT people
• Marketing people
• Contact
information of the
mayors and chief of
the staff and related
authorities
• iOS App
Cost Structure Revenue Streams
•IT Costs
•Labor Costs
•Floor Space (Office Costs)
•Advertisement Costs
• Freemium

11. Target Customer Profile
• Male
• Age 45+
• Low Income
• Live in New York Metro Area
• Registered voter but stopped voting
• Interest in politics
• Continuous struggle with housing issues
“We don’t trust politicians”. “It doesn’t matter
what we think”!!!!

12. Two Routes
Politik Inn
Enterprise Software
Internet Based
Test: Interview Town
Clerks, Chief of Staff
Pass: 1 out of 5 say Y
Test: People with
housing and ask if
they would rate
Pass: 1 out of 5 say Y
Target Customer Segment: “We don’t trust politicians”.
“It doesn’t matter what we think”!!!!
Journalist1: “Politicians should consider their voters
like customers”.
Journalist2: “ Politicians have a narcissistic complex.
They want to be liked by all”.

13. Business Canvas DAY 5 : Test1Key Partners Key Activities Key Value Proposition Customer Relationships Customer Segment/User Types
• Town Clerk
• Mayors
• Chief of Staff
• Director of
Community Services
•. Development of
the software
• Marketing and
Advertising
• Enable the users to
communicate their pain
point about housing issues
directly to the politicians
with a quicker response
time
• Empower the users, so
their collective voices will
be heard by the related
authorities
• Prioritizing the housing
issues (affordable housing
and lease problems) for
the chief of staff
•Relationship with
Town Clerk & Chief of
Staff
Consumers
Male
Age 45+
Live in New York Metro Area
Registered voter but stopped
voting
Interest in politics
Continuous struggle with
housing issues
User
Town Clerk
Buyer
Chief of Staff
Key Resources Channels
• IT people
• Marketing people
• Direct Sales of
Software Products
Cost Structure Revenue Streams
•IT Costs
•Labor Costs
•Floor Space (Office Costs)
•Advertisement Costs
• Licensing (up sell on Analytics)

14. Our Initial Idea
Voters/Common People
Elected
Politicians
Non - Elected
Politicians
Entire
political eco
system
Political
Parties
Political ScientistPolitical
Journalist
Public policy
Maker
Macroeconomist
Professors/Expert
s/Authors

15. Do they care? Hell Yeah!!
Day1
Day5

16. So we Pivoted (Politik Inn
Electifi)
•From a multi sided platform to a User Generated /Long Tail Model
•From eBay of politics to Yelp for Politics

17. Business Canvas DAY 5 : Test 2Key Partners Key Activities Key Value Proposition Customer
Relationships
Customer Segment/User Types
• Political Journalist
• Early Adopters
• Mayors
• Chief of Staff
• Director of
Community Services
•. Development of
the platform
• Marketing and
Advertising
•Gathering the data
the mayors and
chief of staff and
related the
authorities
regarding the
housing issues
• Enable the users to
communicate their pain
points about housing
issues collectively
• Empower the users, so
their collective voices will
be heard by the related
authorities
• Collectively address
the issues
• Community
Manager
• Retentive
Consumer
Male
Age 45+
Live in New York Metro Area
Registered voter but stopped
voting
Interest in politics
Continuous struggle with
housing issues
Key Resources Channels
• IT people
• Marketing people
• Contact
information of the
mayors and chief of
the staff and related
authorities
• iOS App
Cost Structure Revenue Streams
•IT Costs
•Labor Costs
•Floor Space (Office Costs)
•Advertisement Costs
• Free for consumers
•Ad based Revenue

18. Proposed Use Case
1000 ppl
Does
not take
action
Automated
Notifications
When politicians do not
respond notifications goes
to rate them
Get
Rated
Politic
al
Journa
lists
picks
it up
Goes
Vocal
Picture
Mayors

20. Mockups (1)

21. Mockups (2)

22. Mockups (3)

23. Petal Diagram Non- Direct Competitors
Closest Competitors
Substitutes
Allies
The local town
website

24. Features
• Functional
Online user friendly platform to dynamically
prioritize the issues of the local masses.
• Emotional
Users feel that their voices are being heard and
their pain points are being addressed
Users feel that they are part of a community
• Social
The power shifts from politicians to users

25. Market Size
Our
Opportunity
200K
Total Potential Market
400K
Total Market Size
10 M
Total Available Market
No of iPhone users in US: 63M
Total population of US: 300 M
Population of tri-state area: 20 M
Ratio: 0.067
iPhone users in the tri-state area = 4.2 M
People with housing issues= 400K
Realistic Market (Users):
200K
Source: http://www.statista.com/statistics/232790/forecast-of-apple-users-in-the-us/; https://www.google.com/webhp?sourceid=chrome-
instant&ion=1&espv=2&ie=UTF-8#q=population+of+us

26. Has an Inbuilt Potential to Scale

27. Back-Up

28. The Math