How to leverage machine learning with paid social

1. How to leverage
machine learning
with paid social
Karl Sykes-Tobin iticy
www.linkedin.com/in/karlsykest/

2. Social media platforms
are taking more and more
control away from
marketing managers…

3. We used to have Audience Insights,
precise KW matching,
and full control.

4. Control is dropping
despite platform
technical capabilities
rising.

5. PLATFORM
CAPABILITY
MARKETER
CONTROL

6. From no control to full
control to no control…

7. the fight against
the machines
was inevitable

8. The resistance
was strong
but there was
no match…

10. Ad platform’s
smart options and
broad targeting
started to actually work!

11. Ad platforms are
powered by the most
powerful machine
learning technology ever.

12. But without Humans
the machines
don’t know what to learn

13. With great
power
comes great
responsibility

14. You have to
tell the platforms
what you want
to achieve

15. You need to
tell them
over and
over again…

16. Does the system
understand
what you want to achieve?

18. How many data points
can you give to the system
in a week?

19. QUANTITY
QUALITY

20. Purchase
Viewed
content
Added to
cart
When choosing an optimisation
goal, there is a standoff between
volume and depth of the funnel...
20

21. Visited the
web
Still not enough volume
further down the funnel?
Added to
cart
Purchase
Viewed
content

22. How can i give more
high quality data
by cluster intent actions?

23. Spent X minutes
on Key page
Scrolled down
X% of Key page
Visited high
intent page.
(e.g Prices)
Added to cart
Viewed content
Used the search
HIGH INTENT
Strength in Numbers

24. Optimising
for this
would give
more data points
at higher quality
Used the search
Spent X minutes on Key
page
Scrolled down X% of Key
page
Navigated to high intent
page. (e.g Prices)
Clicked category

25. Used the search
25
Spent X minutes on Key
page
Scrolled down X% of Key
page
Navigated to high intent
page. (e.g Prices)
Clicked category
Added to
cart
Purchase
Viewed
content
Visited
the
web

26. Giving value
to different steps
in the funnel…

27. Viewed content Added to cart Purchase
Vol CR CPA
1000 1% 1
Conversion value = 1
Vol CR CPA
100 10% 10
Conversion value = 10
Vol CR CPA
10 100% 100
Conversion value = 100

28. Does the system
understand the goal?
Do you have enough data
for effective ML?
Are all Sales /Leads Equal?
?

29. To optimise for
complex business goals
you need to give
more data.

30. Marketers may want to
optimise for low CPA’s
OV $10
CPA $5 CPA $5 CPA $10
OV $20 OV $15
POPULAR
BRAND
NORMAL
OWN
BRAND
SPECIAL
OWN
BRAND

31. OV $10
CPA $5 CPA $5 CPA $10
OV $20 OV $15
POPULAR
BRAND
NORMAL
OWN
BRAND
SPECIAL
OWN
BRAND
In this case the platform
would favour these products

32. OV $10
CPA $5 CPA $5 CPA $10
ROAS 200% ROAS 400% ROAS 150%
OV $20 OV $15
POPULAR
BRAND
NORMAL
OWN
BRAND
SPECIAL
OWN
BRAND
Optimising for ROAS could
give a different outcome

33. OV $10
CPA $5 CPA $5 CPA $10
ROAS 200% ROAS 400% ROAS 150%
OV $20 OV $15
-$2 -$13 -$4
POPULAR
BRAND
NORMAL
OWN
BRAND
SPECIAL
OWN
BRAND
What happens if we consider
the cost of the product?

34. OV $10
CPA $5 CPA $5 CPA $10
ROAS 200% ROAS 400% ROAS 150%
OV $20 OV $15
Profit $3 Profit $2 Profit $1
-$2 -$13 -$4
POPULAR
BRAND
NORMAL
OWN
BRAND
SPECIAL
OWN
BRAND
Now our own Brand is the
winning products

35. OV $12
CPA $5 CPA $5 CPA $10
ROAS 200% ROAS 400% ROAS 150%
OV $20 OV $22.50
Profit $4.80 Profit $2 Profit $6.50
-$2.20 -$13 -$6
+20%
LTV
+0%
LTV
+50%
LTV
POPULAR
BRAND
NORMAL
OWN
BRAND
SPECIAL
OWN
BRAND
Considering LTV offers a
different perspective!

36. Without computing
these goals,
we would optimise
for the wrong product

37. OV $10
CPA $5 CPA $5 CPA $10
ROAS 200% ROAS 400% ROAS 150%
OV $20 OV $15
POPULAR
BRAND
NORMAL
OWN
BRAND
SPECIAL
OWN
BRAND
Optimising for ROAS could
give a different outcome

38. More Data = More $

39. The systems
need good
feedback
in order to
improve

40. You have
been a very
good boy!

41. The path to
success
Has changed
drastically

42. Now, success
depends on the
quality and quantity
of the data you give
the machines to learn

43. 5 steps to leverage
machine learning

44. 1. Make sure you
feed the machines
enough data

45. 2. Create custom
goals based on
intent actions

46. 3. Give values to
different steps in the
funnel

47. 4. Upload offline
data to give
additional feedback

48. 5. Give tailored data
to hit more complex
business goals