Find out how to leverage first-party cookies and attribution models to optimize your marketing and better map your customer journey.

1. Understanding first-party cookies
and attribution models
C O M M U N I T Y

2. 15K member. 6 years
C O M M U N I T Y

3. • 5:00-5:20: Attendees intros
• 5:20 – 5:35: A guide to the post-cookie world
• 5:35-5:55: Open mic
• 5:55-6:00: QA
Agenda

4. CODE: COURSEFRIEND2020 Academy access

5. Understanding
first-party
cookies and
attribution
models
A guide to the post-
cookie world

6. Intro
• With the death of third-party cookies and the
evolvement of data privacy and legislations
such as GDPR and CCPA, companies need to be
aware of these in order to future-proof their
technology.
• First-party identity resolution or the ability to
stitch all customer data into accurate profiles
is key to improve marketing insights, optimize
ad spend and deliver flawless customer
experience.

7. Difference between first-party and third-party
cookies
• For first-party cookies, the cookies are created and stored
by the website the user visits directly. They enable
website owners to collect analytics data, remember
language settings, and perform functions that help create
a good user experience.
• For first part-cookies, engagement is happening with the
same website, app or endpoint.
• Third-party cookies are created by any domain other than
the website. It can be cross-site tracking, retargeting (ads)
and ad-serving (display ads).

8. Source: us.epsilon.com
Difference between first-party and third-party
cookies

9. Why third-party cookies are dying
• As the emphasis on user privacy is growing, third-party cookies are
becoming a general threat to targeted advertising and marketing.
• A growing number of consumers are not comfortable with the way
their data is shared. They want transparency, choice and control
over how their data is used.
• Safari and Mozilla Firefox no longer support third-party cookies.
• These cookies will be also blocked in Chrome by 2022.

10. Third-party cookies death concerns
• Advertisers are confused about the future of
advertising along with the death of third-party
cookie.
• Ad tech companies like Facebook, Google and
Amazon collaborate on a collective cookie
replacement.
• In light of these, companies started to recognize the
importance of having high quality identity graph of
their own customers.

11. What’s next?
Without Chrome-based third-party cookies
data, you’ll still be able to make use of
Google Ads targeting, which will be
powered by Chrome’s first-party cookies
and the Privacy Sandbox tools.

12. What are your company’s/main client’s tactics
for addressing identity resolution in the
future?

13. • Deterministic: ID resolution uses what you know to be true. It merges identifiers like phone
numbers, emails, device IDs and user IDs that you have collected from the user.
• It’s a high-confidence approach that users first-party data where you definitely know with
certainty the user’s behavior and data points.
• Probabilistic: ID resolution uses what you assume to be true. Using predictive algorithms and/or
third-party databases, it attempts to merge different identifiers to piece together a single view of
the customer.
Deterministic Vs Probabilistic Methodology

14. Source: Segment
Deterministic Vs Probabilistic

15. • Intelligent tracking prevention is a featured offered with Safari and iOS 11 by default.
• It changes the way Apple handles first-party cookies unlike most other browsers.
• Its newest version, ITP 2.0, detects cross-site tracking, which makes it impossible to use them in
third-party context for tracking or analytics purposes. This is different from their previous versions
(1.0 and 1.1) where first-party cookies could be used in a third-party context.
Apple’s Intelligent Tracking Prevention (ITP)
and cookies

16. Source: Segment
Evolvement of cookies and data privacy
legislations

17. How to drive prospects to opt
in and make use of first-
party data?

18. 1. Browser push notification
• SEO, PPC or organic social media efforts driving prospects to your website where they accept to
receive notifications from you regularly.
• Accepting cookies and getting daily notifications via browser push is a successful practice of using
first-party cookies.

19. • People can visit a landing page or website
via an ad or other marketing initiatives
where they are asked to fill out a form or
subscription bar to receive blog newsletters.
They can be also redirected to an article
where a popup shows.
• Once they agree to the company’s terms of
service and privacy policy or confirm that
they are humans, it means that their info
has been successfully captured via first-
party cookie.
2. Landing page, newsletter forms and popups

20. The 3 use cases an effective
identity resolution helps solve
• Analyze end-to-end customer journeys
• Optimize your marketing efficiency
• Deliver consistent experiences

21. • Some prospects and visitors might be anonymous as they haven’t provided their contact info to the
company yet.
• Therefore, it’s critical to tie the unknown user activity to a user profile once has made herself known.
• Without an accurate system that ties unknown and known users, end-to-end customer journey
mapping becomes impossible because the connection between anonymous and post-sale activity is
broken.
• Therefore, with the right identity resolution, marketers, analysts and product owners can invent new
features, optimize site experience and create powerful retention campaigns.
1. Analyze end-to-end customer journeys

22. Example of marrying an anonymous IP with their
known user profile

23. • A proper identity resolution that stitches together accurate customer profiles in real-time,
enables marketers to create high-performing campaigns that save valuable marketing budget.
• According to Gartner, the average brand spends 14% of its entire marketing budget on
personalization tactics.
• Marketers can initiate powerful omni-channel campaigns when there’s one centralized repository
of customer data from all sources.
• Whether it’s advertising, email or support centers, marketers can deliver the right message, to
the right person at the right time.
2. Optimize your marketing efficiency

24. Tying a new user profile of the same customer to
their existing known profile

25. • Customers no longer use a single touchpoint; they rather engage on mobile apps, mobile
browsers, desktop and more.
• A proper identity resolution allows marketers to create a consistent experience across all their
touchpoints. For example, if a user purchases a product on their phone, they shouldn’t see an ad
while browsing on their desktop afterwards.
• Identity resolution enables companies to unify all their user across devices and channels into one
single view of their customer.
3. Deliver consistent experiences

26. Unifying data across multiple touchpoints into a
single view

27. Achieving a single view of the customer
• Company teams can tap into customer data platform (CDP)
to create a personalized customer experience.
• This is done through identity resolution, which unify all
customer touchpoints across channels, devices, and online
and offline activity.
• Stitching all data leads to create comprehensive profiles that
grow with customers over time.

28. • The importance of marketing attribution is to
study how customer touchpoints drive
conversions.
• It measures each channel effectiveness and
assigns credits to the touchpoints that lead the
customer to convert.
• This allows marketers to better map their
customer journey and optimize their marketing
campaigns.
Marketing attribution

29. 1. First touch attribution
2. Lead creation touch attribution
3. Last touch attribution (Opportunity creation touch)
4. Last non-direct touch attribution
5. Last [Insert Marketing Channel] Touch Attribution
6. Linear Attribution
7. The time decay conversion
8. U-Shaped (Position-Based) Attribution
9. W-Shaped Attribution
10. Full-Path (Z-Shaped) Attribution
Marketing attribution models

30. 1. First Touch Attribution
• This model gives credit to all the marketing efforts that
pushed the prospect to interact with the first page.
• It gives emphasis on the top of the funnel where
awareness is created.
• Its drawback is the inaccuracy between the first touch
and conversion. For example, as the cookie expires
within a 30 to 90-day period, this model is giving
attribution to the first touch within this period and NOT
the true first touch where conversion might take
greater than 90 days. (i.e: If you are using conversion
tracking using Google Analytics).

31. • This model helps you determine the marketing channels
that drive lead conversions.
• However as there’s a lot more than just a lead signup or
creation, this remains a small part in the customer
journey so it’s unrealistic to give 100% credit to lead
creation only.
• Also this model may often be confused with the first
touch model because marketing automation platforms
consider that the first session starts from whenever the
lead is created.
2. Lead Creating Touch Attribution

32. • It’s the simplest model for attribution systems.
• It assigns credit where a sale opportunity is
created and where the end of the marketing
funnel is.
• It also has the smallest time window for an error
to occur as the period is very short, unlike the
first touch model.
3. Last Touch Attribution (Opportunity Creation
Touch)

33. • This is somehow more useful than the simple last
touch model, because it doesn’t take into account the
“Direct Traffic” which may not come from manually
typing the URL but also from any traffic that doesn’t
have a referral source. For instance, any social posts,
social ads, or emails that don’t have a proper UTM
tracking is considered direct traffic.
• As a result, this model helps you avoid the troubles of
“Direct Channel” data which is often deceiving.
4. Last Non-Direct Touch Attribution

34. 5. Last [Insert Marketing Channel] Touch
Attribution
• This is the last Adwords touch model, Facebook or
Twitter touch model.
• This is the last touch before whatever conversion you
configured the analytics to measure such as lead
conversion, or opportunity conversion…
• While each attribution comes standard with their
channel as each insights, either on FB or Adwords, uses
a Last Adwords Touch Model, it’s biased to their own
channel.
• For example, if a visitors clicks on a Facebook ad on
Monday and then a Google ad the next day and then
converts, both channels model credit 100% of the
conversion credit.

35. • This method gives credit to every single touchpoint in
the buyer journey.
• The good thing about this method is that it’s a multi-
touch model.
• Its shortcoming is that it doesn't take into account the
varying impact of each touchpoint and may assign the
highest credit to a channel that impacted the least in
driving conversions.
• For example, a prospect initially clicks on your landing
page via your FB ad, stays on the page for an hour. 1 day
later, they visit your site via direct search and then
convert. Your landing page will get 5% of the credit
while the remaining 95% goes to direct search.
6. Linear Attribution

36. • This model assigns attribution to the channels or
touchpoints closest to conversion. It makes the
assumption that the closer to conversion, the
more influence it has.
• The main problem with this model is that it
ignores top of the funnel as it considers it away
from conversion.
7. Time Decay Attribution

37. • This model focuses on lead generation.
• It’s a multi-touch model that tracks every single
touchpoint but emphasizes the importance of 2 key
touchpoints: the anonymous first touch that brought the
visitor to the door and the lead conversion touch.
• Each of the these touches are given 40% of the credit
and the remaining 20% is split equally across the other
touchpoints.
• The problem is that it ignores marketing efforts beyond
the conversion stage.
8. U-Shaped Attribution (Position-Based)

38. • This model takes takes the U-Shaped model to the
lead opportunity stage, which is considered the
end of the funnel for many organizations.
• The W-Shaped gives emphasis to 3 touchpoints:
First touch, lead conversion and opportunity
creation touch.
• Each of these 3 receives 30% while the remaining
10% is distributed equally among the remaining
touchpoints.
9. W-Shaped Attribution

39. • Taking it one step further, the Full-Path model or
Z-Shaped takes the attribution to include the step
beyond the opportunity stage: the customer
close.
• In this model, each of the four touchpoints gets
22.5% of the credit and the last 10% is split
equally among the remaining touchpoints.
• This model is fair and accurate for organizations
that do marketing to existing sales opportunities.
• Adopting this method requires a close
coordination between marketing and sales.
10. Full-Path Attribution (Z-Shaped)

40. Source: Ruler
Marketing attribution software and comparison

41. Open Mic