Intro Deck to Frakture: Math Eats Marketing

1. Smart Data NewSQL Predictive Analysis Data Moneyball Flow Import
Marketing Consultants Node.js Touch Mobile Cloud Marketing Math
Regression Analyze Testing Message Production Actionable Insight Analytics 2.0
Data Scientists Customer Cohorts Multiple Channels ROI Quants CMO
Segments BI Competitive Advantage Strategy Simplify Ease of Use Speed
Insight & Action: Math Eats Marketing
NewSQL Predictive Analysis Data Moneyball Flow Import
Smart Data
Marketing Consultants Node.js Touch Mobile Cloud Marketing Math
Regression Analyze Testing Message Production Actionable Insight Analytics 2.0
Data Scientists Customer Cohorts Multiple Channels ROI Quants CMO
Segments BI Competitive Advantage Strategy Simplify Ease of Use Speed

2. The Problem >
#1
Data Sources:
Marketing is being transformed due to the
flood of data. Harnessing that power is still
a problem. Aggregating data ACROSS
channels and technologies is hard.
65% of Organizations say that integrating
multiple data sources is a challenge
DATA
TOO many channels, too
many data sources
Source: http://blog.neolane.com/conversational-marketing/big-data/

3. The Problem >
#2 Good Analytics are difficult to get
> Lack of Human Resources 2018 Data Analyst Shortage
> 140,000-190,000: Shortage by 2018 of people with
deep analytical skills among US Companies
> Benefits are tangible, but not always obvious
> Lack of good, easy cross-channel modeling tools
= 190,000
#3 Turning Insight into Action: = 1500
Once you HAVE good analytics, implementing
and getting to real engagement is hard
> Turn data into something: Relevant, Timely, Contextual, Personal –
A fancy dashboard is insufficient
> Being an expert in each of these channels is impossible
Tools that do all three of these things well and make it simple do not exist
Source: http://blog.neolane.com/conversational-marketing/big-data/

4. Why it’s solvable NOW >
Digital Advertising and Social
Media have moved beyond hype
Public acceptance of Analytics
and Big Data
Professional data analysis
techniques and controlled
experimentation have matured

5. Who’s Trying >
Automation Optimization
Automation companies are focused
Optimization companies improve
on making work easier for
the impact of marketing, generally
marketers. This includes
in a small number of channels.
dashboards, process automation,
action triggers, integration with Analysis Speeding up web page delivery,
targeting ads, testing
CRM, etc. Analysis companies make marketers infrastructures, etc. all fall under
better by delivering new or better Optimization.
statistics for them to make decisions on.
Predictive analytics, cross-channel
metrics, numbers, numbers, numbers.

6. Why we're the ones to solve it >
Chris Lundberg April Pedersen
Co-Founder, CEO Co-Founder
Geek with People Skills. I build Social Entrepreneur addicted to
highly scalable technology that helping people figure out how to
people actually need to do their use technology for meaningful
jobs better and scalable engagement. Leader, organizer,
companies to support them. marketer, rabble rouser.
We are : Experienced Tech & Social Entrepreneurs who enjoy major
disruption in industries & helping groups grow and better engage with their
audiences.
We're all about the Action.
Together we have :
Founded and ran $9M SaaS CRM and Founded and ran nonprofit SaaS to
Communications Platform with 2000 make technology accessible to
clients and 70 staff. small and mid-sized charities.

7. The Technology We're Building >
Our working prototype includes :
1) Data, Data, Data: We've built a number of wicked fast Extract/Transform/
Load libraries to ingest millions of records from a number of different sources, identify
them to the person, and pull out transaction details. In seconds.
2) Segment and Prediction engine: Using combinations of column store
DB's(Redshift), object stores (MongoDB), and modeling (custom), we can slice and dice
the data in thousands of ways, run prediction models, and expose them via an API.
3) Interface: The interface layer
delivers results from the engine API via
Node.js to desktops, tablets, and
touchscreens, producing interactive
timelines and charts, as well as
producing and managing full
campaigns across a number of different
channels.

8. The Tech Stack >
API
Channels
Amazon Redshift
Warehouse
3rd
Party Prediction
DATA Statistics
Modeling

9. The Company We're Building >
Focus over the next 6-12 months:
Build out team of 5-7 and working with our "Gamma" cohort of
clients to test & build on our prototype
Target Market:
CMO's, consultants, agencies serving companies with:
> $1M marketing budget
> Marketing across min 4 channels
> Smart Analytics/Data folks w /ability to recognize ROI
Build Brand:
Geeks solving Marketing/Engagement problems
with a simple, elegant solutions

10. The Investors We Want >
Goal:
Raise just enough seed money ($750K) to build an elite
team for 6-12 months of work with a small cohort of
clients to build the product and ensure relevance
We want investors who:
Are founder-centric
Believe in the importance of a tech CEO
Interested in helping us build a strong network
Believes in iterative development of product & company
Can provide industry advice when necessary
Believes the product is only as good as the clients it has

11. Insight & Action: Math Eats Marketing
www.frakture.com info@frakture.com
angel.co/frakture twitter.com/fraktureinc