Dados e Al - A galinha dos ovos de ouro no E-Commerce. Philipp Povel - CEO e CO-Fundador, Dafiti Group Malte Huffmann - CO-Fundador e MD, Dafiti Group

1. Dados e AI
A Galinha dos Ovos no e-
Commerce
Fórum E-Commerce Brasil
São Paulo, Julho 2020

2. Why are we here?
Dafiti’s essence is Art & Science - today, we would like to talk
about the Science in our business!
How does data and AI in particular transform our world and our
business?

3. By now, we all know it...
“Data is the new Oil “
Clive Humby (UK Mathematician)is credited to be the first
who coined the term in 2006
“AI is the new electricity”
Andrew Ng at re:MARS 2019
“From mobile first to AI first”
Google’s CEO Sundar Pichai announced at Google I/O 2017
“Software Is Eating the World, but AI Is
Going to Eat Software”
Nvidia CEO Jensen Huang, May 12, 2017. Nvidia Developer
Conference

4. ...or don’t we?
MIT Sloan report:
Many AI initiatives fail. 7 out of 10 companies surveyed
report minimal or no impact from AI so far.
Among the 90% of companies that have made some
investment in AI, fewer than 2 out of 5 report business
gains from AI in the past three years. This number
improves to 3 out of 5 when we include companies that
have made significant investments in AI.

5. The amount of data and connected devices is increasing exponentially
Source(s): https://www.statista.com/statistics/871513/worldwide-data-created/ © Statista, https://leftronic.com/internet-of-things-statistics/ |
https://www.statista.com/statistics/371828/worldwide-mobile-connections/ | https://www.bankmycell.com/blog/how-many-phones-are-in-the-world )
What is 1 zetabyte?
4.503.6 Trillion
iPhone 11 Max Pro 256 GB or
8.868.7 trillion
videos of 10 minutes (1080p)
As of August 2019 there were
26.66 billion
of active IoT devices and
3.4 billion
internet users and creating around
9 billion
mobile connections to the internet.

6. Moore's law is the observation
that the number of transistors in a
dense integrated circuit doubles
about every two years
As a result computing power is growing
exponentially and is expected to reach
human levels by 2029
Driven by Moore’s law

7. ● AWS has 125 different services available. Of these, 18 are related to AI / ML and 55 to data
● In 2018, AWS had 200 different ML related launches
● ~10,000 customers are currently using ML services
And by significantly lower cost of storage and the emergence of cloud
computing that offer “AI as a service”
Source(s): https://mkomo.com/cost-per-gigabyte
Hard drive cost per Gigabyte?
>250.000 USD
cost of GB before 1980
<0.10 USD
cost of GB after 2010

8. As a consequence, the world as we know it is changing
The way we commute..
Self-driving cars
The way we buy..
Amazon Go
The way we style...
Stitch Fix
The way we are
watched...
China surveillance
The way news is
created...
Fake News

9. AI has been a significant catalyst for this change as investments into AI are
growing at a rate of 48% p.a. and reached more than USD 40bn in 2018.
Private Investment in AI (in bn USD) Number of funded companies
Source(s): AI Index 2019 Report

10. AI is a General-Purpose Technology and as a result Global GDP could be up to
+14% higher by 2030 - the equivalent of an additional USD 15.7 trillion.
Source(s): PWC AI Analysis - Sizing the Price Report, 1) General-purpose technologies (GPTs) are technologies that can affect an entire economy (usually at a national or global
level). GPTs have the potential to drastically alter societies through their impact on pre-existing economic and social structures
Where will the value gains com from with AI - Global GDP impact by effect of AI
USD 15.7 trillion is more than the
current output of China and India
combined!
Productivity Gains will account for
approx. 40% of all GDP gains and
involve automation of routine tasks
and augmenting employees’
capabilities.
Increased Consumer demand will
deliver 60% of additional GDP.
Consumers will be attracted to
higher quality and more
personalised products/services, but
will also have the chance to make
better use of their time.

11. North America & China will be the winners accounting for USD 10.7 trillion and
70% respectively of the global economic impact
Source(s): PWC AI Analysis - Sizing the Price Report
Which regions will gain the most from AI
North America & China stand to see
the biggest economic gains with AI
enhancing GDP by 26% in China and
14.5% in North America. I.e. 70% of
the global economic impact!
Europe and Developed Asia will also
experience significant economic gains
from AI enhancing GDP by 9.9% in
Northern Europe, 11.5% in Southern
Europe and 10.4% in Developed Asia.
Developing countries (incl. Brazil)
will experience more modest increases
due to the much lower rates of
adoption of AI technologies expected.

12. The USA and China are dominating AI on average, however, the reality is much
more nuanced as local centers of AI excellence are emerging across the globe
USA China Next Best or leader
While the US and China dominate AI, there are strong centers of excellence in Europe, Japan and
India as well that lead in some aspects of AI
Source(s): AI Index 2019 Report
Private Investments per country No. 1 ‘
No. 2 UK -> No. 3
Private Investment per capita No. 3
No. 13 Israel -> No. 1
No. of AI startups funded No. 2
No. 1 UK -> No. 3
No. of AI Patents No. 1
No. 6 Japan -> No. 2
No. of Deep Learning Papers No. 1
No. 2 UK -> No. 3
No. of AI Journal Papers No. 2
No. 1 India -> No. 3
Relative Skill Penetration No. 2

13. Brazil ranks last based on private investments into AI and has not yet
defined a national AI strategy
Private Investment in AI (bn USD)
Source(s): AI Index 2019 Report
● Brazil has not yet published a
dedicated artificial
intelligence strategy, but has
only partly addressed AI
through related initiatives
(2017 Internet of Things (IoT)
National Action Plan, 2018 E-
Digital strategy).
● To date, Brazil has most
notably implemented AI in
facial recognition systems
(mainly in criminal
establishment and airports).
Brazil’s National Strategy

14. But is witnessing the second fastest growth in AI hiring in the world
Source(s): AI Index 2019 Report
AI Hiring Index by Country

15. Retail has the highest adoption maturity already - AI & automation has become a
requirement due to winner-takes-all economics and continued margin pressure
Source(s): PWC AI Analysis - Sizing the Price Report, Business of Fashion McKinsey 2020, IBM Institute for Business
Areas with the biggest AI potential
(1) Personalised design and production,
(2) Anticipating customer demand,
(3) Inventory and delivery management.
(4) Intelligent automation
Key Insights:
(1) Margin pressure is mounting due to more competition: Top 20 fashion
players by profit, account for more than the combined profit of the entire industry.
(2) AI is already a reality - over 80% of retail industry expect to be using intelligent
automation by 2021. 40% is already engaged in some form of intelligent automation
(3) AI has winner-takes-all economics
● Margin pressure has made intelligent automation a
requirement, not a choice.
● If you are not using AI, you are falling behind as AI is a reality
with winner-takes-all economics that might kill you business.

16. Through our ideation process, we have identified hundreds of use cases for AI at
Dafiti that could have a game changing impact on our business.
Source(s): company information
● sales forecast
(by SKU,
region, yearly,
monthly etc.)
● catalog
enrichment
● high frequency
pricing
● Vendor
scorecard
creation
● supplier risk
management
● Intelligent
picking
automation
● Anti-Fraud
Control
● Automation of
Payment
Acquirer choice
● shared basket
analysis
● Auto e-mail
response
● sentiment
analysis /
chatbot
● nps clustering
detractors
pred.
● LTV Prediction
● customer
segmentation
● search, recos,
catalog sorting
● churn
prediction,
similar brands
● clustering onboarding, offboarding, eNPS
● talent sourcing, profile match
● legal case predictor
Value
Stream
● event correlation in e-commerce system
● A/B testing of new digital services
● security threat detection
Support
Function
Sourcing &
Planning
Operations &
Logistics
Payment &
Order
Marketing &
Discovery
Customer
Service
HR, Legal, Infrastructure

17. It is difficult to implement AI. Some best practices to get you started!
Source(s): Dafiti Learnings; McKinsey Global Institute (https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/how-to-make-ai-work-for-your-business,
https://hbr.org/2019/07/building-the-ai-powered-organization, https://www.mckinsey.com/featured-insights/future-of-work/skill-shift-automation-and-the-future-of-the-workforce)
The biggest challenges are people and processes!
Digital capabilities come before AI!
Take a portfolio approach and start small and early!
Don’t put tech. teams solely in charge of AI!
You don’t have to go it alone on AI!
AI’s
Dos & Don’ts

18. Dafiti Example: Start small! ML can be extremely simple as shown by Dafiti’s
Ratings & Reviews solution for an operational problem.
Baseline Code
Library import
Only 12 lines
of code!
● Problem Description: Backlog of more than 50k customer
ratings & reviews had to be approved and uploaded to the
website. Typically, this is a manual process and would
require a lot of time.
● Goal: Automatically approve backlog by applying learning
from previously approved and rejected R&R (approx. 600k)
● Results: small testset of 92 reviews showed 28 approved
(~30%) reviews with ~90% accuracy which translates that in
a backlog where I usually have ⅓ rejected reviews I could
approve ½ of valid reviews automatically - big win in 12 lines
of code
● Next steps: curate date (e.g. AWS mechanical turk), more
data, better algorithms (e.g. word2vec)
Ratings & Reviews approval
Results

19. Dafiti Example: Image recognition (supervised learning)
● Problem Description: User wants to find similar products
of a clothing she sees. Also be able to find similar clothes
of influencer’s dresses (resolve out-of-stock problem).
● Goal: Find similar products of an image or photo.
● Results: Users which used visual search had on average
~10 % higher basket. By using an AI-as-a-service
approach the same API could be used for influencer
pages.
Visual search
Source(s): company information

20. Dafiti Example: Pricing optimization (supervised learning)
● Problem Description: Optimize prices in order to
maximize each SKUs absolute profit contribution over its
lifecycle.
● Goal: Model to predict conversion rate as a function of
price changes, then optimize the price for a metric like
revenue or contribution margin.
● Result: PoC with live test of xxxSKUs in randomized A/B
test.
○ Using our ML Model allowed us to generate a 17%
higher contribution margin
○ Very relevant uplift.
Pricing Recommendation
Source(s): company information

21. Dafiti Example: Picking robots and warehouse automation enabled by AI
Source(s): company information
54k m² new fulfilment center
Automated picking process
by AI-driven robots
Built within a fully
environmental friendly
mindset

23. In order for the world to embrace the potential of AI, 7 key risks need to be
addressed going forward.
Privacy
Security
AI Bias
Explainable AI
AI Monopoly
Jobs
Wealth Inequality
1
2
3
4
5
6
7

24. But: Most organizations are still not taking the necessary steps to mitigate the risks
associated to AI
Organizations taking steps to mitigate risks from AI (2019)
Source(s): AI Index 2019 Report
Percent of respondents

25. Now, let’s remember why we are here….
“Data is the new Oil “
Clive Humby (UK Mathematician)is credited to be the first
who coined the term in 2006
“AI is the new electricity”
Andrew Ng at re:MARS 2019
“From mobile first to AI first”
Google’s CEO Sundar Pichai announced at Google I/O 2017
“Software Is Eating the World, but AI Is
Going to Eat Software”
Nvidia CEO Jensen Huang, May 12, 2017. Nvidia Developer
Conference
To understand how data and AI in particular are transforming our
world and our business.
...and now, you really get it!

26. The transformation
starts with you!
Some books to get
you started

27. Some books that inspire us!