Conversion modeling will be crucial as restrictions increase on the use of cookies and personal data for advertising. As individual identifiers are less available, the industry will rely more on aggregated, anonymized data and conversion modeling. Conversion modeling uses machine learning to quantify the impact of marketing efforts when not all conversions can be tied to ad interactions due to data limitations. It provides benefits like a more representative view of performance and accurate, privacy-safe measurement. Proper measurement foundations like tags and consent modes are important for accurate conversion modeling.

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Conversion modeling
will be crucial in a world
without cookies
Pavel Jašek, Analytical Consultant, Google
Twitter: @paveljasek

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Platform Changes
Browser restrictions on use of cookies
Mobile OS restrictions on use of device identifiers
Regulation
Increase in restrictions on use of personal data
and additional requirements around user consent
User Privacy
Rising user expectations on Privacy
impacting measurement ecosystem

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Known unknowns Unknown (un-)knowns
Tracking gaps
Transactions not tracked
Consent rate
Not able to collect all the data
Missing attribution
Lost connection to interactions
… …
Biases
Skewed observed data

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We expect the availability of individual
level identifiers to continue to degrade
over time
Industry will move to rely on aggregated
and anonymized measurement and data
collection
Your understanding of the customer
journey may still have gaps, even when you
have the right infrastructure in place
The industry’s ability to tie conversions to ads will
continue to decrease

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Reported
conversions
2016
100%
0%
2021 Present
Illustrative Example
As a result, we’ll continue using conversion modeling in
order to maintain a full picture of ads performance
Modeled
Observed
Modeled
Observed

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Conversions power revenue growth for advertisers through
automation and advanced measurement
Smart Bidding
Modeled
Conversions
Observed
Conversions
Targeting &
Creative
Revenue
Growth
Attribution
Incrementality
Conversions Measurement Automation &
Optimization
Tags, APIs or
Uploads

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Benefits of conversion modeling
Representative view of
your performance
More efficient campaign
optimization and bidding
Accurate, privacy-safe
measurement

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What is Conversion Modeling
and Why is it Important?

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Conversion modeling
refers to the use of machine
learning to quantify the
impact of marketing efforts
when a subset of
conversions can’t be tied
to ad interactions
What is conversion modeling?

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2x
as many Marketers prefer to use a
combination of modeled+observed
data (vs. observed data only)
Over 90%
of web + app advertisers will consider
conversion modeling when analyzing
their performance data
Source: 3P Qualitative Research Study on Conversion Modeling, SKIM 2020
Modeling is used widely in the industry today

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What types of
measurement
modeling exist
at Google?
Attribution Modeling
Online to Offline Modeling
Unique Reach Modeling
Conversion Modeling
Behavior Modeling

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Quality conversion data coupled with ML-based
modeling leads to better campaign performance
1P Data, Aggregate Customer
Behaviors & Contextual Signals
Advanced Machine
Learning
Campaign performance boost with
Machine Learning based technology
35%
Source: BCG 2019 Study: The Dividends of Digital Marketing Maturity

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High Bar for Privacy
Unique to each Advertiser
Quality Data
Communicating
significant modeling
changes
Seamless Integration
No Fingerprinting
Addressing Gaps via Unique
Modeling Methodologies
Tailoring Gaps based on the
advertiser
Ongoing Improvement
Ensuring Accuracy
Rigorous Threshold for Reporting
These principles guide our conversion modeling
solutions across products at Google*
1 2 3
*Where the conversion event occurs on an online surface

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Measurement foundations
for a great Conversion Modeling

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App
Invest in a durable foundation essential for all
conversion modeling
Google Tag Manager
Global Site Tag
OR
Web
Google Analytics 4
Firebase SDK

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Only aggregated and anonymized conversions are reported in your account | Supported tags include: Google Ads Conversion Tracking, Floodlight, and Google Analytics
Consent Mode
1 2 3 4
User navigates to your website
or app and indicates consent
status
(for ads and/or analytics
storage)
Consent Mode will tell Google
tags whether they have
permission to use cookies for
ads and analytics
When the user does not
consent, the relevant Google
tags will adjust their behavior
to help observe conversions
without using associated
cookies. When the user
consents, Google will observe
data as normal.
With modelling, Google
surfaces the most accurate
data in your account to enable
better reporting and
optimization

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Consent mode adjusts tag behavior based on the
user’s consent status
Google receives a
consent ping w/ gclid,
dclid, cookie ID, Google ID
Unconsented ping sent to
Google; no ad click
identifier sent unless URL
passthrough enabled
Google
Tags load

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Who should use Consent Mode?
Primarily using Google
Ads for conversion
tracking
Consent Mode will allow modeling for
lost conversions and simplify
compliance if GA is simultaneously
deployed.
Interest in
future-proofing
measurement
Consent Mode will form a durable
part of Google Analytics’ future
privacy capabilities, including new
features around cookieless
measurement.
Coming soon to GA4 properties will
be the ability to model for behavior
impacted by lack of cookie consent.
Primarily using Google Analytics
for conversion tracking
If not requiring consent for Analytics, Consent
Mode will still simplify compliance for optional
GA functions (like remarketing) prior to consent.
If requiring consent for Analytics, Consent Mode
will allow modeling for lost conversions and
pre-enable customer for GA cookieless mode.

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Without
Consent Mode
With Consent Mode,
tags only fired for
users who granted
consent
With Consent Mode,
tags fired for all users
(Consent Mode adjusts the
behaviour of tags based on
user consent)
Illustrative chart only, observability and recovery rates vary by advertiser
Recommended for
most accurate
modeling
Maximize the amount of conversions recovered while
meeting your business requirements
Observed
Conversions
Modeled
Conversions
>70% of ad-click-to-conversion
journeys lost due to user cookie
consent choices

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increase in reported
Search conversions
+5%
Adopt products built on top of the global site tag & Google
Tag Manager for enriched first party data
#
what? where? who?
Enhanced
Conversions
Consent
Mode
Google
Analytics 4
Uses advertiser’s hashed
customer data to fill in
gaps due to browser
changes
Adjust tag behavior and
fill in gaps in conversions
due to consent banners
Provides most complete
picture of behavior and
conversions across Web
and App
Google Ads only
Google Ads,
Google Analytics,
SA360,
CM360/DV360
Google Analytics
only
Web advertisers
in non-sensitive
categories with
customer data
App or web
advertisers in the
European Economic
Area (EEA)
App or web
advertisers using
Google Analytics
increase in reported
YouTube conversions
+12%
lost ad click to
conversion journeys
recovered due to user
consent choices
>70%

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Conversion modeling will be crucial in a world without cookies
Learn as much about
known unknowns
Tracking gaps
Consent rate
Potential biases
in observed data
Educate your team
and customers how to
cope with the changes
Think with Google article
bit.ly/ConversionModeling
Marketing Education Series
bit.ly/ModelingEducation
Adopt products built on top
of the global site tag & GTM
for enriched first party data
Google Analytics 4
Consent Mode
Enhanced Conversions
DATARESTART 2021 SUMMARY

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Thank
You
@paveljasek jasek@google.com