1. Growth & A.I.
Product
A love story
Jan 14th 2020

2. What will you learn ?
● A process to outgrow your competition
● Obtain more from analytics with less hassle
● How to add A.I in your product
● In which part of your product should you
implement AI first for more impact
● When you should not invest in A.I
● And more...

3. Who Am I ?

4. A.I. has inherent
LIMITS
Disclaimer

5. 73
Value Proposition validated
Business Model found
Personas and Segmentation done
Key Performance Indicator defined4
3
1
2
Disclaimer

6. DOABLE
(TECH)
VIABLE
(BUSINESS)
DESIRABLE
(UX)
PRODUCT MANAGEMENT
Disclaimer

7. DOABLE
(TECH)
VIABLE
(BUSINESS)
DESIRABLE
(UX)
PRODUCT MANAGEMENT
SUSTAINABLE
(ALL)
Disclaimer

8. What’s Product Growth?
- A mindset
- A process
- A Tool box
A blend from Marketing and Product and Data in order
to accelerate the increase pf Key Performance Indicators.
— Thiga

9. GROWTH
FOCUS Entire user lifecycle
OBJECTIVE KPIs increase
TEAM
Multidisciplinary Teams (Product, Data,
Design, Technical and Marketing skills)
IMPACT High Impact on Product evolution
EXPERIMENTATIONS High Frequency, Scheduled & Measured
DATA FOCUS Data driven / Data informed
“Ideal” Product Growth organization

10. Tools
Process
Mindset
change
You start here...
Implement an A.I. Growth oriented approach:
1

11. The deep belief that growing happens
through small, incrementals steps, rather
than big overnight victories.
A.L Le Cunff

12. The deep belief that growing happens
through small, incrementals steps, rather
than big overnight victories.
with
Artificial
Intelligence

13. Tools
Process
Mindset
change
Implement an A.I. Growth oriented approach:
2

14. 1 Generate Ideas
Organize and
Prioritize
Test
Analyze
Optimize
Repeat
2
3
4
5
6
Growth process

15. Tools
Process
Mindset
change
And finally...
Implement an A.I. Growth oriented approach:
3

16. Build VS Buy

17. Implementation of AI tools for Growth
MUST HAVES
SHOULD HAVES
NICE TO HAVES
PREDICTIVE ANALYTICS
CLUSTERING /
CUSTOMIZATION
RECOMMENDATION SYSTEM
PSYCHOGRAPHIC PERSONAS
NLP
IMAGE RECOGNITION

18. PREDICTIVE ANALYTICS

19. Asking yourself the right questions:
What is
the expected
Customer Lifetime
Value ?
Who is about to
churn ?
Who are my best,
most valuable
customers ?

20. How does it work ?

21. Predictive Analysis - Build

22. CLUSTERING /
CUSTOMIZATION

23. Clustering/Customization
Review your way of
building personas
Rely on data instead

24. Clustering - Buy example

25. Clustering - Buy example

26. RECOMMENDATION

27. A Recommendation engine is a system that
suggests products, services or information to
users based on analysis of data
Using for instance the history of the user and the
behaviour of similar users.

28. Recommendation - Tool

29. Personalized search - Tool

30. There’s more...

31. Back to the basics
Remember Scrum ?

33. Market & User pains
Product/Solution

34. High(er) Tempo experimentation
AI
+ =

35. Marketing Engineering
Product
Growth
Data
Skills needed

36. COLLECT
qualitative feedback
faster ...

37. NATURAL LANGUAGE
PROCESSING

38. NLP deals with interaction between computers
and humans using the natural language.
The goal is to read, decipher, understand and
make sense of the human languages in a manner
that is valuable

39. NLP - Build with APIs
Amazon Comprehend Google Cloud Native
Language API

40. NLP - Build with Libraries
NLTK

41. Tool

42. NLP - Tool

43. There’s even more...

44. Tool

45. Tool

46. Takeaway

47. Explore your Product and your Process
Find Areas of Improvement
Test and Analyze
Optimize
Grow
REPEAT