Attribution models sound like a smart way to allocate credit to your different ad campaigns. But, they're inherently built from flawed and incomplete data, meaning that it's impossible to assign credit to the right campaigns. This means that they are almost certainly making you draw the wrong conclusions. Rich is going to explain how you change that, and break down how incrementality models can help you make better decisions with your creative, your strategy and your media buying Key Takeaways: - Attribution and Measurement are different things - Attribution is not sufficient for measuring the impact of your marketing campaigns - Increasing privacy thresholds mean that it will only get worse at this - Incrementality, captured through several methods, is the most powerful method at our disposal to capture and deliver growth

1. April 25, 2024
Headlight x DigiMarCon
Moving Beyond
Multi-Touch
With Rich Ingilby

2. Let’s start with some definitions

3. Attribution
Directly connecting an individual or cohort to the
marketing activities they’ve engaged with.
Incrementality
The actual impact that a marketing activity has
on a KPI, and which would not have happened
without it
Measurement Modeling
Using statistics and machine learning to find
correlations and signals that can describe the
incremental impact of marketing activities.

4. The first responder: The nervous
system of our marketing
campaigns
Attribution:

5. GA4 is a good example of an attribution
channel*
*and there are lots of others

6. …and DDA sounds great, right?
[Data-driven] Attribution uses machine learning
algorithms to evaluate both converting and
non-converting paths. The resulting Data-driven model
learns how different touchpoints impact key event
outcomes. The model incorporates factors such as time
from key event, device type, number of ad interactions,
the order of ad exposure, and the type of creative assets.
Using a counterfactual approach, the model contrasts
what happened with what could have occurred to
determine which touchpoints are most likely to drive key
events. The model attributes credit to these touchpoints
based on this likelihood.”
“
r”

7. But,
there’s a few pretty fundamental issues…

8. Where attribution models fall down
They only
know when
people have
clicked an ad
1

9. Where attribution models fall down
Privacy (e.g.
SKAN)
2

10. Where attribution models fall down
Cookie
banners
3

11. Where attribution models fall down
4
Tracking
across
sessions

12. But wait… THERE’S MORE
Google going
cookieless
sometime1
Apple
blocking all
UTMs on
Safari 2
And
shared
links3
1. https://developers.google.com/privacy-sandbox/blog/cookie-countdown-2023oct
2. Apple WWDC 2023 — June 5 2023
3. https://www.pcmag.com/news/to-improve-privacy-apple-to-strip-tracking-parameters-from-shared-urls
4. https://backlinko.com/duckduckgo-stats
5. https://headerbidding.co/walled-gardens-in-ad-tech/
6. https://hbr.org/2023/08/how-the-pandemic-changed-marketing-channels#:~:text=Nearly%20two%2Dthirds%20(61%25),
The rise of
privacy-centric
browsers4
The rise and
rise of digital
walled
gardens 5
Rise in the
number of
marketing
channels 6
MORE PRIVACY
MORE SKAN

13. What impact does this have?
Take a look at your first and last click attribution report
And… how many people are coming directly to your site?
Well…

14. Attribution is a first
responder. It’s your
campaign’s nervous
system. It’s great for
instrumentation
Attribution is actually
great for some stuff

15. Where attribution models fall down
∞ …But, would they have
converted anyway?
Reason #

16. The solution?
Incrementality
“The actual impact that a marketing activity has on a KPI”1 …
1. https://www.adjust.com/glossary/incrementality/
… and which wouldn’t just have happened anyway 2
2. Rich Ingilby (2024)

17. It doesn’t care about individuals
It looks at cohorts and aggregates. No tracking? No
problem.
What does an
incrementality-first
approach do?
It doesn’t care if someone clicked or viewed
It looks at outcomes, not the journey
It tracks actual impact
It compares what actually happened against a
counterfactual: What was your impact?

18. So how do you measure incrementality?
Source: Towards Data Science - Power Analysis for Data Scientists
https://towardsdatascience.com/power-analysis-17636d3f059b
You run a test
We need two things:
1) We need results with our
marketing present, and results
without our marketing present
2) We have to be confident of
effect size

20. You could also look at alternative data
sources
For example: “How did you hear about us?” surveys

21. Or take this straight to MMM*
(*Media Mix Modelling)

22. MMM aims to reattribute based on
incrementality

23. Response Decomposition
Given current spend levels, and current results,
what proportion of the results is a product of the
constituent channels?
Budget Allocation Optimization
Given a spend X, what is the optimal allocation
of that spend?
Response Optimization
Given prior performance scaling curves, at what
point will increased spend start resulting in
diminishing returns?
What do we use
MMM for?

24. Day to Day performance reporting
The model by definition is built on prior performance, it
won’t tell you anything about current performance. You
cannot optimize to maximize MMM outputs.
Compensation for Lack of/Noisy Signal
The models depend heavily on long term (2y+) trends,
stable performance, strong data points and knowledge
of external factors that impact performance.
Discovering Unexpected External
Performance Impacts
Models by their nature are for projecting forward fixed
assumptions. If those assumptions are wrong, so is the
model.
What don’t we
use MMM for?

25. MMM requires a large number of inputs
You need:
Historic data
+
Building*
+
Know-how*
*We can provide those parts dw

26. Each of these has a part to play
Speed Comparability Accuracy
Attribution
Surveys
Testing
MMM
High Med Low

27. Sweet, so how do I use
Incrementality?

28. Thinking in terms of
incrementality
opens a lot of doors

29. Channel X says it’s doing a lot. Is it?
Or is it just getting in front of people
before they buy?
It shows where you need
to fix bad channels

30. You can’t measure the
impact of brand
awareness with
attribution
You can with
incrementality
Incrementality enables full funnel
marketing
https://www.thinkingunstuck.com/think-pieces/the-two-most-important-charts-in-marke
ting-and-why-they-matter-now-more-than-ever

31. All of your spend is going
to statics, you say? Those
things that are great at
driving clicks, you say?
It lets you measure
creative impact

33. Measuring the actual impact of your marketing…
+
Operating across the funnel
+
Focusing on incremental revenue
Incrementality lets you GROW

34. Key takeaways
1. Attribution and measurement are different things
2. Attribution will only get worse
3. Good attribution enables good instrumentation, good
measurement enables good strategy
4. Incrementality, is the most powerful method at our
disposal to measure impact
5. When you know what is delivering impact, you know how to
grow

35. Questions?
Get in touch!
headlight.co