The document proposes a business model for a marketplace that connects buyers and sellers of data to address the lack of market data available to companies. It would allow companies to upload their own data to sell, as well as make custom data requests, and generate revenue through commissions on transactions ranging from $3,000 to over $50,000. The founders believe this marketplace could unlock value by providing a niche platform for small and medium companies to access valuable data.

1. SmrtData
Group 3
Nov. 27, 2018
Clarke Gallie, Kyle Hope, Kerianne Ndimubandi, Sijie Wang, Spencer Farmer

2. The problem
- Not enough variety of market data for C level executives, managers, or data
scientists of a company to make decisions based on accurate numeric
information
- Companies need data, insights, and research to stay ahead, but only million or
billion dollar companies often have the privilege of having the right network or
resources to acquire the data and information to solve specific questions

3. Focus on serving a niche segment of data enthusiasts, managers, AI
and ML developers, and small - medium sized companies looking for
new market research
● Allow buyers of data
○ Variety of vendors to compare offers and quality
○ Custom data service requests, or pre made packages
○ Ensures data is safe and secure with strict regulations
● Allows sellers of data
○ Sell their knowledge and expertise
○ Make an income or side revenue stream
○ Data policy and updated regulations training
The Solution

4. Freelancing Website Example

5. Business Model
Value Proposition
1) Allow companies to upload data or make requests
2) Run through privacy rights, normalize data and make sure the legality of the deal
3) B2B marketplace model for data
Revenue Model
1) Make money on each transaction, 8-12% (tiered commission structure)
2) Sales are typically anywhere from $3,000-50,000+
3) Costs are website, lawyers, marketing and sales
Customer Segments
1) Data scientists, AI and ML developers
2) Managers and C-level executives of companies looking to get ahead

6. Underlying Magic
Secret Sauce
1) Two sided marketplace for buyers and sellers for data
2) Niche strategy, with a first to market advantage
3) Starting in a country with relaxed data regulations
How do we present it?
1) Completely open and informative of our policies, regulations
2) Self starter can make an income and build a “lifestyle business”
3) Companies looking for an advantage
4) “Not the big guys”
How do we sell it (revenue)
1) Sales are typically $3,000-50,000+
2) 8-12% off of a seller's commission for the first $5,000 in sales
3) 7-8% off of seller's commission for $5,000 - $100,000
4) 4-5% from $100,000+

7. Marketing and Sales
Start Local
1) Find current developers and companies selling data and show them how to get on our site
2) Focus on Machine Learning and Artificial Intelligence, show them specific datasets we have, and help them find what they
need to increase usage.
3) Attend conferences to reach all potential markets
Expand Nationally
1) Advertise appropriately, focus on large cities where large data usage corporations are located (Toronto to start)
2) Reach out to consulting groups and companies that need a competitive advantage
3) Be a market leader in safe, open, informative, and secure data transfers

8. Industry
1) Data marketplace will unlock more than 3.6 trillion in value by 2030
2) Insights as a service are expected to be valued at 3.3 billion by 2020
3) Data science jobs have risen by 650% since 2012
Companies
1) A startup HR AI company in Toronto needed data to test their models.
Being a startup, they didn’t know where to go, they spent 3 weeks
finding 1 online scraping company and spent $3,500 for 2,000
LinkedIn profiles in a csv.
2) Stock traders and hedge fund managers buy satellite image processing
of oil farms and land
3) Linamar spends $60,000 on car sales reports in China a year
Market Research
“Every company has big data in its future and every
company will eventually be in the data business.”
Thomas Davenport, American academic and
author specializing in analytics, business process
innovation and knowledge management

9. Competitive Landscape

10. Competitive Landscape
Large company owned
data selling business model

11. Competitive Landscape
Multiple different vendor
freelancing business model
Large company owned
data selling business model

12. Competitive Landscape
Multiple different vendor
freelancing business model
Large company owned
data selling business model

13. Sales Forecast

14. Profit and Loss

15. Cash-Flow

16. Timeline
● Finished Website
● Advertising
● Acquire Local Users
● Selling 15-30
Datasets
● 5-10 Purchases
YEAR 1
● Ramp Up Advertising
● Expand Through
Ontario
● Selling 70-100
Datasets
● 20-50 Purchases
YEAR 2
● Expand Nationwide
● Focus on Customer
Retention
● Selling 150+ Datasets
● 100+ Purchases
YEAR 3TODAY
● Develop Business Model
● Market Research
● Legal
Work/Requirements
● Start Website
Development

17. Management Team
Clarke Gallie
Computer Science, Finance
Kyle Hope
Strategy and
Entrepreneurship
Kerianne Ndimubandi
Business, Marketing
Sijie Wang
Business , General
Spencer Farmer
Human Resources