Everyone is talking about Big Data, Deep Learning and Artificial Intelligence. But the reality in some companies looks different, especially when developing new products: (the relevant) data is missing. Without predictive models and recommendation systems cannot be trained and the value is consequently low. This so called cold-start problem is especially concerning startups, since without own data treasure the companies are missing a defendable unique value proposition. Successful startups solve this problem with the help of „Data Traps“ and develop products with „Data Network Effects“. What exactly stands behind these terms and how companies design their own successful and data-driven products, will be demonstrated by Martin Szugat based on samples from his occupation as Data Strategy Consultant.
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Using Data Strategy Design to Build Data-Driven Products
1. Using Data Strategy Design to
Build Data-Driven Products
Martin Szugat at Product Tank Munich on 26.06.2017
datentreiber.de
2. Driving your business forward.
Consulting, workshops and seminars on data strategy design.
3. 1996-2008
Software developer, consultant,
trainer and author
Study & research of bioinformatics
(Data Science)
2001-2008
Managing director & shareholder of
SnipClip GmbH
2008-2013
Program director of Predictive
Analytics World conferences in
Germany
2014-dato
Managing director & owner of
Datentreiber GmbH
2014-dato
Founder and director of
Datengipfel academy
2017-dato
4.
5.
6. Drivers for AI spring:
Improved methods & open source tools
Processing power (i.e. GPU) & memory
Availability and quality of data
7. Breakthroughs in AI are mainly driven by data.
Source: http://www.kdnuggets.com/2016/05/datasets-over-algorithms.html
11. What makes data valuable?
Quantity (i.e instances)
Density (i.e. features)
Quality
Completeness
Currentness
Correctness
Reliableness
Representativity
…
12. More data means better predictions (in general).
Source: https://medium.com/mmc-writes/the-fourth-industrial-revolution-a-primer-on-artificial-intelligence-ai-ff5e7fffcae1
16. “Accessing and owning a large, domain-specific dataset to build high
accuracy models can be the single hardest problem that founders need to
solve in the beginning.”
Source: https://medium.com/@muellerfreitag/10-data-acquisition-strategies-for-startups-47166580ee48
17. “Owning a large, domain-specific dataset can therefore become a significant
source of competitive advantage […]”
Source: https://medium.com/@muellerfreitag/10-data-acquisition-strategies-for-startups-47166580ee48
31. Data-driven business is lead by a value-oriented strategy.
Exploitation Refinement Utilization
32. What‘s a „data product“?
Data Algorithm
Infor-
mation
„Data Product“
[2]:
“A data product is a
computer application
that takes data
inputs and generates
outputs, feeding
them back into the
environment.”
„Data Product“
[1]:
“Customers buy the
data 'product' once,
and continue to use
it as is.”
„Data Product“
[3]:
“A data product is
digital information
that can be
purchased.”
33. What‘s a data-driven product?
Data Algorithm
Infor-
mation
It‘s valueable.It‘s unique.
It‘s an unique value proposition. (model)
It‘s a driven-driven product.
It‘s customer needs.
39. Prediction of
percentage of
seats sold
Predictive
Model: Total
Revenue
Predictive
Model: Seats
Sold
Wikipedia
Movie Data Movie Total
Revenue
Figures
Seats Sold
per Movie
43. Prediction of
percentage of
seats sold
Predictive
Model: Total
Revenue
Predictive
Model: Seats
Sold
Wikipedia
Movie Data Movie Total
Revenue
Figures
Seats Sold per
Movie
Movie Name
Mapping Table
Prediction
Game
Data
WarehouseETL Tool Predictive
Modeling Tool
Website
Development
Tools
Data
Engineers
Data
Scientists
Web
Developers
Seller: Movie
Total Revenue
Figures
44. Cinema
Operator
Prediction of
percentage of
seats sold
License cost
reduction
Website
SaaS
Email
Predictive
Modeling
Marketing &
Sales
Seats Sold
per Movie
HR
Software
Marketing
Budget
Monthly Pay per
Cinema Hall
Prediction
Game
Movie Name
Mapping
Table
Prediction
Game
Seller: Movie
Total Revenue
Figures