How to prosper in the age of extreme customer centricity.

1. The Machine Learning
Company

2. Moves at a lightning pace.
Technology

3. NY, 5
th
Av., 1900 NY, 5
th
Av., 1913

4. Yet human behaviour
does not.
People still have the same hopes, fear,
ambitions as 2.000 years ago.

5. “The faster
technology changes,
the more people
stay the same.”

6. So you thought Selfies are a millennial thing?
So you thought selfies are a Millennial thing?

7. A.D. 1920

8. And you thought scooters are a new hype?
A.D. 1911

9. We adapt.

10. We focus on changing human behaviour, not
on changing technology.

11. Still,
technology moves fast.
Is it really different this time?

12. Technology moves
lightning fast.
Is it really different this time?

13. Lil Miquela
Shudu

18. What is happening?

19. It’s the economy,
stupid.

20. The supply chain.

21. Production
Raw Materials Distribution
Marketing
Customers

22. Production
Raw Materials Distribution
Marketing
Customers
1950 -1970
Choke point
€ € € € €
Big factories
Organised around production

23. Production
Raw Materials Distribution
Marketing
Customers
1980 - 2000
Choke point
€ € € € €
Supermarkets & FMCG’s
Organised around marketing

24. Production
Raw Materials Distribution
Marketing
Customers
2000 - …
Choke point
€ € € € €
Internet happened…
Organised around customer

25. Alibaba, the
most valuable
retailer, has no
inventory.
Uber, the
world’s largest
taxi company,
owns no fleet.
AirBnb, the
largest
accommodation
provider owns no
real estate.
Facebook, the
most popular
media owner,
creates no content.
Platform companies, owning the customer experience.

26. Disrupt the disruptors.

27. “A brand is no longer built by
advertising (alone), but by the sum
of all touch points.”
(Those touch points are increasingly digital.)

28. What to do in the age of the
customer?
Be extremely customer centric.
This depends on data.

29. Digital Transformation =
extreme customer centricity.

30. We’ve organised our supply chain
completely wrong.
ProductionR&D Distribution Marketing Customers
What does the
customer want?

31. ProductionR&D Distribution Marketing Customers
What does the
customer want?
Sales figures
Current solution:

32. ProductionR&D Distribution Marketing Customers
What does the
customer want?
Sales figures
Make this as short
as possible.
Current solution:

34. ProductionR&D Distribution Marketing Customers
What does the
customer want?
Sales figures
Make this as short
as possible.
Current solution:
Problem:
- post factum
- not real time
- sample based

35. What if we turn the cycle around?

36. This is based on data.
ProductionR&D DistributionMarketing Customers
What does the
customer want?
What if we turn the cycle around?

37. First, you make a customer.
Then you find out what he needs.
(And then you make and ship the product.)
(Hyperpersonalised.)

38. Zume Pizza

39. Adidas Speedfactory

40. Metallica + Spotify

44. Winning (digital) companies have a
continuous feedback loop.
•at scale (not sample based)
•real-time (not post-factum)
•every (use of the) product is based on data,
and lets data flow back to improve the next
product.
Building a ‘Machine Learning Company’.

46. But you can make it smaller.

49. And even smaller.

53. Google Store Visits

54. First, you make a customer.
Then you find out what he needs.
(And then you make and ship the product.)
(Hyperpersonalised.)

55. Driven by digital
•every product gets its digital twin
•extreme digital measurability
•increasing link between offline and online

56. Every organisation has to do e-commerce.
(And not just for the sales.)

57. E-commerce is not about the sales.
Distribution
Channel
Company
making
products
Customers
What does the
customer want?

58. E-commerce is not about the sales.
Distribution
Channel
Customers
What does the
customer want?
Problem:
- post factum
- not real time
- sample based
Company
making
products

59. E-commerce is not about the sales.
Distribution
Channel
Customers
What does the
customer want?
Webshop
Company
making
products

60. E-commerce is not about the sales.
Distribution
Channel
Customers
What does the
customer want?
It’s all about the
data flowing back.
Webshop
Company
making
products

61. Build a continuous feedback loop.
•every (use of the) product is based on data
•data continuously flows back to improve the
next product

62. Build a continuous feedback loop.
•every (use of the) product is based on data
•data continuously flows back to improve the
next product
Stop using data that is post-factum, sample
based or not real time!

63. D2C is not just a distribution tactic, it will
be a vital strategy.
Start collecting data now.

64. Gather
data
Spot the
pattern
Adapt the
product
Do
something
Machine Learning.
At speed. At scale.

65. Build a
Machine Learning Company

66. Thank you!

67. Questions?
bart@wijs.be
@netlash

68. Foreestelaan 1
9000 Gent
info@wijs.Be
09 335 22 80