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© Google Inc. 2016. All rights reserved.
Attribution with
Google Analytics
Peter Falcone
Analytical Lead EMEA
April 6th, 2017
© Google Inc. 2016. All rights reserved.
● Digital Attribution
● Online to Store Attribution
● TV Attribution
We’ll cover
© Google Inc. 2016. All rights reserved.
● Real life examples
● Results achieved
● How to & implementation details
We’ll focus on
3
4
Source: https://en.wikipedia.org/wiki/Fritz_Heider
5
Attribution
The purpose of attribution is to quantify the influence each advertising
touchpoint has on a consumer’s decision to make a purchase decision, or
convert.
6
”
Aim for better, not for perfect
Improving focus by increasing data quality, extending the scope of channel
measurement and media budget allocation.
It`s a process of technology and service which provides a clearer view on
marketing performance and enables value driven optimization.
Digital
Attribution
8
Founded
2011
4
Products
(but 4.400
recipes)
Countries
9
SEM
manager
1
Bid strategy
Adwords ROAS
1
10
FABB
● is a constant process of media optimization
● assigns fractional contribution at granular and actionable level
● exports fractional contribution into bidding systems
Proprietary + Confidential
Process, products and features
Data driven modeling
(DDA + unified channel grouping)
X-Channel measurement
(auto tagging, utm`s, filters)
Automated bidding
(ROAS bid Strategy)
Data access / export
(unsampled report)
FABB
Import Conversion credits
(Offline Conversion Import)
Proprietary + Confidential
Demo: Data in GA
Proprietary + Confidential
All signals per click are stored here
value
click IDs)
Unique ID
used by bid managers to track
ads and refer back in the
system
per ad / user / time / auctionURL?gclid=value
Proprietary + Confidential
Signals used in autom. bidding stored in a Click ID
+/-
XX%
Smartphone
Noon EST
Location
BrowserOS
Remarketing
list
Ad creative App
Language
Actual
query
Search
partner
Bid adjustment based on prioritized
combinations of signals
Click ID
Google
Stores auction
signals/info
Impact on ROAS performance
Pre Post
ROAS - SEA all
(Adwords All campaigns)
145%
(proportional increase)
77%
(proportional increase)
ROAS Top 10 generics
(Adwords Top 10 Generic campaigns)
Case study: https://goo.gl/r6RHgb
Online to Offline
Attribution
17
Context
153 stores in France
36 days of store data loaded in
Google Analytics
In-store buyers
with loyalty cards
A high % of transactions’ volumes
are made through the loyalty card
program
In-store buyers with loyalty
cards that log-in on the
website
Logged-in users represent a high % of
online traffic that can be matched
with offline transactions made with
loyalty cards
Online to Offline - Context & Methodology
1 2 3
18
19
UserID
tracking
20
2 different Users
(cookie-based)
Cookie (clientID)
123456.429834
Cookie (clientID)
432234.3423424
21
Login
Login
1 User
(persistent ID based)
› User-Centric Measurement
› Works on Web, mWeb & Apps and other devices
User ID: 4Q321
Cookie (clientID)
512955.2424231
Cookie (clientID)
123456.429834
Cookie (clientID)
123456.429834
User ID: 4Q321
22
UserID Tracking in Analytics
user login
UserID (UID)
assigned
<UID
>
<UID
>
<UID
>
<UID
>
User ID
User ID
23
Implementation guide: http://goo.gl/cMkBv7
1
2
4
3
UserID Tracking - Implementation
24
Implementation guide: http://goo.gl/cMkBv7
UserID Tracking - Session Unification
PAGE 1 PAGE 2 PAGE 3
LOGGED INNOT LOGGED IN
1 SESSION
Login
With Session Unification enabled, all
login and pre-login hits in the same
session (only) are reported in the User
ID View
4
25
Implementation guide: https://goo.gl/pMB4aT
UserID Tracking - Tag Manager
4
26
Online to Offline Tracking in Analytics
Loyalty Card
purchase
Measurement Protocol
user login
UserID (UID)
assigned
<UID
>
<UID
>
<UID
>
<UID
>
User ID
User ID
27
Measurement Protocol for Online to Offline
Measurement Protocol
allows you to send data to Google
Analytics from anything with
an Internet connection.
The data is sent via HTTP Requests,
a very common way to transfer
data online, to:
http://www.google-analytics.com/collect
http://ssl.google-analytics.com/collect
Name Parameter Example Description
Protocol
Version
v v=1 Protocol version - the value should be 1
Tracking ID tid tid=UA-123456-1 Google Analytics Property ID
User ID uid uid=123456 Persistent/authenticated user id, unique
to a particular user
Hit Type t t=event The type of interaction collected for a
particular user
28
Demo
time
Return on AdWords spend is multiplied by 6.4
when considering in-store transactions
Online return
on ad spend (€)
Online to in-store return
on ad spend (€)
x6.4
Proprietary + Confidential
More online preparation is done,
when the basket value is high
Low
28%
33%
39%
46%
58% 57%
66%
73%
87% 86%
x3
HighStore average basket value
O2S effect1
by basket size (%)
1
In-store buyers who visited the site before making a purchase (the standard lookback window of this study is 7 days
Proprietary + Confidential
Key Findings
44% x3
of in-store buyers visited
the site before making a
purchase
x6.4
Is where the O2S effect
is maximized
Mobile
O2S1
effect when
average basket value is
high
AdWords ROAS when
in-store sales are
considered
1
In-store buyers who visited the site before making a purchase (the standard lookback window of this study is 7 days)
Case study: https://goo.gl/sKw1Ii
TV
Attribution
How would you like to...
Identify TV Spot performance and optimise towards it?
TV Attribution helps you identify low performing
TV spot activity, and optimise its budget into
higher performing activity
ENGAGEMENT
COSTEFFECTIVENESS
© Google Inc. 2016. All rights reserved.
TV Attribution Analysis Logic
6am 8am 10am 12pm 2pm 4pm 6pm 8pm 10pm 12am
Digital Activity
Baseline
TV
TV
TV
TV
TV
TV
TV
TV
How it Works
• Evaluate
minute-by-minute
and hour-by-hour
activity
• Machine learning
establishes baseline
• Model incremental
impact of airings
© Google Inc. 2016. All rights reserved.
Bear in mind: short-term analysis scope!
© Google Inc. 2016. All rights reserved.
TV SPOT DATA
● Impressions
● Creative
● Network
● Day-part
● Spot
Combine & analyse
data
Incremental searches & visits
attributed to individual TV spots
Bayesian Inference with
Gibbs Sampling
GOOGLE SEARCH DATA
● Volume
● Brand, Generic
● Tablet, Desktop, Mobile
● Baseline, Ad, Other
How Does It Work?
High level process
GOOGLE ANALYTICS DATA
● Paid visits
● Direct visits
● Organic visits
● Baseline, Ad, Other
37
© Google Inc. 2016. All rights reserved.
Thank you!

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GAUC 2017 Workshop Attribution with Google Analytics: Peter Falcone (Google)

  • 1. © Google Inc. 2016. All rights reserved. Attribution with Google Analytics Peter Falcone Analytical Lead EMEA April 6th, 2017
  • 2. © Google Inc. 2016. All rights reserved. ● Digital Attribution ● Online to Store Attribution ● TV Attribution We’ll cover
  • 3. © Google Inc. 2016. All rights reserved. ● Real life examples ● Results achieved ● How to & implementation details We’ll focus on
  • 4. 3
  • 6. 5 Attribution The purpose of attribution is to quantify the influence each advertising touchpoint has on a consumer’s decision to make a purchase decision, or convert.
  • 7. 6 ” Aim for better, not for perfect Improving focus by increasing data quality, extending the scope of channel measurement and media budget allocation. It`s a process of technology and service which provides a clearer view on marketing performance and enables value driven optimization.
  • 9. 8
  • 11. 10 FABB ● is a constant process of media optimization ● assigns fractional contribution at granular and actionable level ● exports fractional contribution into bidding systems
  • 12. Proprietary + Confidential Process, products and features Data driven modeling (DDA + unified channel grouping) X-Channel measurement (auto tagging, utm`s, filters) Automated bidding (ROAS bid Strategy) Data access / export (unsampled report) FABB Import Conversion credits (Offline Conversion Import)
  • 14. Proprietary + Confidential All signals per click are stored here value click IDs) Unique ID used by bid managers to track ads and refer back in the system per ad / user / time / auctionURL?gclid=value
  • 15. Proprietary + Confidential Signals used in autom. bidding stored in a Click ID +/- XX% Smartphone Noon EST Location BrowserOS Remarketing list Ad creative App Language Actual query Search partner Bid adjustment based on prioritized combinations of signals Click ID Google Stores auction signals/info
  • 16. Impact on ROAS performance Pre Post ROAS - SEA all (Adwords All campaigns) 145% (proportional increase) 77% (proportional increase) ROAS Top 10 generics (Adwords Top 10 Generic campaigns) Case study: https://goo.gl/r6RHgb
  • 18. 17
  • 19. Context 153 stores in France 36 days of store data loaded in Google Analytics In-store buyers with loyalty cards A high % of transactions’ volumes are made through the loyalty card program In-store buyers with loyalty cards that log-in on the website Logged-in users represent a high % of online traffic that can be matched with offline transactions made with loyalty cards Online to Offline - Context & Methodology 1 2 3 18
  • 21. 20 2 different Users (cookie-based) Cookie (clientID) 123456.429834 Cookie (clientID) 432234.3423424
  • 22. 21 Login Login 1 User (persistent ID based) › User-Centric Measurement › Works on Web, mWeb & Apps and other devices User ID: 4Q321 Cookie (clientID) 512955.2424231 Cookie (clientID) 123456.429834 Cookie (clientID) 123456.429834 User ID: 4Q321
  • 23. 22 UserID Tracking in Analytics user login UserID (UID) assigned <UID > <UID > <UID > <UID > User ID User ID
  • 25. 24 Implementation guide: http://goo.gl/cMkBv7 UserID Tracking - Session Unification PAGE 1 PAGE 2 PAGE 3 LOGGED INNOT LOGGED IN 1 SESSION Login With Session Unification enabled, all login and pre-login hits in the same session (only) are reported in the User ID View 4
  • 27. 26 Online to Offline Tracking in Analytics Loyalty Card purchase Measurement Protocol user login UserID (UID) assigned <UID > <UID > <UID > <UID > User ID User ID
  • 28. 27 Measurement Protocol for Online to Offline Measurement Protocol allows you to send data to Google Analytics from anything with an Internet connection. The data is sent via HTTP Requests, a very common way to transfer data online, to: http://www.google-analytics.com/collect http://ssl.google-analytics.com/collect Name Parameter Example Description Protocol Version v v=1 Protocol version - the value should be 1 Tracking ID tid tid=UA-123456-1 Google Analytics Property ID User ID uid uid=123456 Persistent/authenticated user id, unique to a particular user Hit Type t t=event The type of interaction collected for a particular user
  • 30. Return on AdWords spend is multiplied by 6.4 when considering in-store transactions Online return on ad spend (€) Online to in-store return on ad spend (€) x6.4
  • 31. Proprietary + Confidential More online preparation is done, when the basket value is high Low 28% 33% 39% 46% 58% 57% 66% 73% 87% 86% x3 HighStore average basket value O2S effect1 by basket size (%) 1 In-store buyers who visited the site before making a purchase (the standard lookback window of this study is 7 days
  • 32. Proprietary + Confidential Key Findings 44% x3 of in-store buyers visited the site before making a purchase x6.4 Is where the O2S effect is maximized Mobile O2S1 effect when average basket value is high AdWords ROAS when in-store sales are considered 1 In-store buyers who visited the site before making a purchase (the standard lookback window of this study is 7 days) Case study: https://goo.gl/sKw1Ii
  • 34. How would you like to... Identify TV Spot performance and optimise towards it? TV Attribution helps you identify low performing TV spot activity, and optimise its budget into higher performing activity ENGAGEMENT COSTEFFECTIVENESS
  • 35. © Google Inc. 2016. All rights reserved. TV Attribution Analysis Logic 6am 8am 10am 12pm 2pm 4pm 6pm 8pm 10pm 12am Digital Activity Baseline TV TV TV TV TV TV TV TV How it Works • Evaluate minute-by-minute and hour-by-hour activity • Machine learning establishes baseline • Model incremental impact of airings
  • 36. © Google Inc. 2016. All rights reserved. Bear in mind: short-term analysis scope!
  • 37. © Google Inc. 2016. All rights reserved. TV SPOT DATA ● Impressions ● Creative ● Network ● Day-part ● Spot Combine & analyse data Incremental searches & visits attributed to individual TV spots Bayesian Inference with Gibbs Sampling GOOGLE SEARCH DATA ● Volume ● Brand, Generic ● Tablet, Desktop, Mobile ● Baseline, Ad, Other How Does It Work? High level process GOOGLE ANALYTICS DATA ● Paid visits ● Direct visits ● Organic visits ● Baseline, Ad, Other
  • 38. 37
  • 39. © Google Inc. 2016. All rights reserved. Thank you!