Omnichannel Attribution Modelling

OMNICHANNEL
ATTRIBUTIONS
What is attribution modelling?
Why do we need it?
How do we do it?
A t t r i b u t i o n M o d e l l i n g

$$
Pre-Sales Activities Post-Sales ActivitiesConversion
In Store
In App Purchases
Web Shop
Businesses at work

Pre-Sales KPIs
Actions leading to conversion
AWARENESS
FAMILIARITY
CONSIDERATION
INTENT
Web Channel Traffic
Product searches
Store Visits
Login & Registrations
Contact Requests
POS interactions
App Subscriptions
Social Interactions

How Do
User
Decide to
buy?
Web Channel Traffic
Product searches
Store Visits
Login & Registrations
Contact Requests
POS interactions
App Subscriptions
Social Interactions
Actions leading to conversion

2002 2012 2016 -
Touchpoints between User and Business

Touchpoints between User and Business
High
Medium
Low
Campai
gns
Site Site
Search
Product Cart
Product Save
Mailer Social
Media
Media
Television
Radio
POS
Agent,
Dealer,
Live
Store
Mobile
App
Web
Shop/
Dealer
Feedback After
Sales
service
APPS /
Share
Usage /
Repeat
Order
Awareness
Familiarity
Consider-
ation
Intent
Connection
Sale
Relation
After Sales
Service
Evaluation
Contact
Point
Journey
Point

Marketing at work
Paid Search
SEO
Banner Ads
Social
Retargetting
Print and TV
In shop
How you spend
$$
How you actually convert

HALF OF OUR BUDGETS SPENT ON THE
MARKETING CHANNELS GOES TO DUMP,THE
PROBLEM IS WE DON’T KNOW WHICH HALF.
@Marketing team.

Identifying the channels your
user uses to reach you.
In case of ‘multi channel attribution
’ we determine the impact of multipl
e digital marketing channels
(paid search, organic search, email
marketing, direct traffic, referral tra
ffic, display advertising etc) on
conversions. We try to understand
how different digital channels work
together to create conversions and
how the credit for conversions shou
ld be distributed among various ch
annels.
Synchronizing user experience
across devices.
We determine the impact of multiple
devices (Desktop, Tablets, Smart
Phones, Smart TVs etc) on conversi
ons. We try to understand how diffe
rent devices work together to create
conversions and how the credit for
conversions should be distributed a
mong different devices
Taking a complete view of your
user journey online and offline.
We determine the impact of digital
marketing channels on offline
marketing channels and vice versa.
We try to understand how online &
offline campaigns work together to
create conversions and how credit
for conversions should distribute
among different online &
offline marketing channels.
Multi-Channel
Attribution
Cross Device
Attribution
Offline-Online
Attribution
There are three types of Attributions:
Attributions

‘Real World Attribution Model’
Multi-Channel
Attribution
Cross Device
Attribution
Offline-Online
Attribution
Attributions
There are three types of Attributions:
but first let’s implement the above three in order to reach to a real world scenaro

IMPLEMENTATION
How to setup the tracking for ‘Real world attribution’ modelling

Multi-Channel Tracking
for
Marketing Channel Attributions
1

Intent
Consideration
Familiarity
Awareness
Live Store
Connect Apps
Web Shop
Conversion
Marketing at work

14
Key Challenge
Important questions that marketing teams have to answer are:
CURRENT CHANNELS: Which marketing channels are working better than others?
e.g. are the TV ads as effective as the paid search ads on Google?
WHAT IF SCENARIOS: If there is additional money available to spend, where should
we be investing the additional budget? Should we be investing in Facebook mobile ads?
CURRENT SPEND: Is the marketing spend paying off? Is it driving growth for the
company? Should we be investing more or pulling back on marketing spend?
A
B
C

Analytics at work
How you see path reports What you actually want to infer

A customer finds your site by clicking one of your AdWords ads. She returns one week later by
clicking over from a social network. That same day, she comes back a third time via one of
your email campaigns, and a few hours later, she returns again directly and makes a purchase.
Hour
1 week In 1 day
www.letsmakepurchase.comPurchase$$
Ex: user purchase journey through Channels

Last Interaction attribution model: the last touchpoint—in this case, the Direct channel—would receive 100% of the credit for the
sale.
Last Non-Direct Click attribution model: all direct traffic is ignored, and 100% of the credit for the sale goes to the last channel that
the customer clicked through from before converting—in this case, the Email channel
Last AdWords Click attribution model: the last AdWords click—in this case, the first and only click to the Paid Search channel —
would receive 100% of the credit for the sale
First Interaction attribution model: the first touchpoint—in this case, the Paid Search channel—would receive 100% of the credit for
the sale.
Linear attribution model, each touchpoint in the conversion path—in this case the Paid Search, Social Network, Email,
and Direct channels—would share equal credit (25% each) for the sale.
Time Decay attribution model: the touchpoints closest in time to the sale or conversion get most of the credit. In this particular sale,
the Direct and Email channels would receive the most credit because the customer interacted with them within a few hours of
conversion. The Social Network channel would receive less credit than either the Direct or Email channels. Since the Paid
Search interaction occurred one week earlier, this channel would receive significantly less credit.
Position Based attribution model: 40% credit is assigned to each the first and last interaction, and the remaining 20% credit is
distributed evenly to the middle interactions. In this example, the Paid Search and Direct channels would each receive 40% credit,
while the Social Network and Email channels would each receive 10% credit.
Standard attribution models as you know

WHEN HAS STANDARD BEEN ENOUGH?
@Executive team.

19
Define Marketing Channels01

20
Define Order of Channel Overrides02
Order of Processing
/ SEM - Branded (Paid Search Branded)
/ SEM - UnBranded (Paid Search UnBranded)
/ SEM - Remarketing
/ SEO - Branded
/ SEO - UnBranded
/ SOCIAL - Paid
/ SOCIAL – Organic
/ SOCIAL - Earned
/ GDN - Remarketing
/ GDN
/ Email
/ DISPLAY - Remarketing
/ DISPLAY
/ VIDEO
/ PROGRAMMATIC Buying
/ OFFLINE - TV
/ OFFLINE – In Shop
/ AFFILIATES
/ REFERRAL
/ DIRECT
/ REFRESH Session
/ INCORRECT Tagging

21
Setup Channels in GA03
Analytics, by default, applied these rules to
create channels and store sessions into the
channels:
https://support.google.com/analytics/answer
/3297892?hl=en
Analytics recognize Organic, Direct and
Referral traffic by default. For campaigns, you
need to send the medium and the source
through UTM parameters included in the
landing URL.

22
Create your defined channels04
Adwords and DoubleClick Campaigns can be tagged automatically,
but for any other campaign you need to add URL parameters:
UTM_source
UTM_medium
UTM_campaign
Ex: http://www.metriplica.com/?utm_source=newsletter&utm_medium=email&utm
_campaign=Courses-2017
If you work with other sources and mediums, or you have made a
mistake with parameters, you can customize the channel
grouping:
a) You can create new channels
b) You can modify rules to send some traffic to the proper channel
(for example, you have tagged your email campaigns with "MAIL"
in the UTM_Medium, and you want to store these sessions inside
"Email" Channel.

23
Create your defined channels05
In the first option (Channel Settings --> Channel Grouping), you will find the panel to modify and
create channels groupings.
It is a very good practice don't touch the Default Channel Grouping. Duplicate it, and make changes
in the new one. In GA you will have the option to select the Channel Grouping that you need.

24
Set your defined order06
Points to remember:
When you define a new channel, you must
give a name, define the rules, and select a
color for the channel.
Order of processing is important for
attributions in case of conflicting or
overlapping rules.
For edition, you have the same options, but
you start from a default rule already applied.

25
Build Custom Attribution Model & Reports07
You may create up to 10 custom attribution models per view. To create a custom attribution
model, decide what attribution model we need:
Then 
1. Create new custom model and enter a name for your model.
2. Use the Baseline Model drop-down menu to select the default model you want to use as a
starting point for your custom model. We recommend starting with Time Decay or Position
Based as baseline models and build upon.
3. (Optional) Lookback Window to On to specify any of 1-90 days.
4. (Optional) Adjust credit for impressions to On
5. (Optional) Set Adjust credit based on user engagement to On to distribute credit
proportionally based on engagement metrics.
6. (Optional) Set Apply custom credit rules to On to define conditions that identify
touchpoints in the conversion path according to characteristics such as position (first, last,
middle, assist) and campaign or traffic source type (Campaign, Keyword, and other
dimensions). After defining, specify how these touchpoints will be distributed conversion
credit, relative to others.
7. Click the Save and Apply

26
Attribution Setup and reporting08
Channel definitions will be available in Multi-Channels and Attribution Reports, and Acquisition Reports:
Acquisition Overview

27
Assisted Conversions

28
Model Comparison Tool

29
You can select the Custom Channel Groping that you have created previously

30
Test and iterate09
Through continuous testing you can determine the acquisition channels which deserve maximum
credit for conversions in a particular point in time/product life cycle

Cross Device Tracking
for
Multi Device Attributions
2

32
User journey mapping cross devices01
User interacts with your digital assets from
multiple devices and in multiple ways:
1. Same asset different devices ex:
Interacting with website via Mobile and
Desktop
2. Multiple assets Multiple Devices ex:
Interacting with website as well as mobile
app

33
Switching to User ID (vs Client ID)02
Through ‘user-id’, you can create and assign your own ids to track unique users instead of
using the client ids generated by the Google Analytics tracking coding.
User id is simply a unique set of alphanumeric characters (like UD23ddd3432)
assigned to a user so that he/she can be identified across devices/ browsers and over
the course of multiple sessions.
Client id represents a unique device/browser. Whereas a user id represents a unique
user that may interact with your website using multiple devices/browsers.
NOTE: Implementation instructions change if you are using GTM.

34
Implementing User ID03
To implement the User ID, you must be able to
generate your own unique IDs, consistently
assign IDs to users, and include these IDs
wherever you send data to Analytics.
The User ID lets you associate engagement
data from multiple devices and ... Connect
multiple devices, sessions, and engagement
data to the same visitors. ...
Each unique User ID is considered to be
aunique user in Analytics
In simple terms, Mobile SDK needs to be
tweaked, web app tracking code needs change
and Web calls (HITs) need to be tweaked to
send additional ‘User ID’ with each hit as an
identifier.
User ID

35
Setting tracking in GA04
User ID data can only appear in a
dedicated User ID view. To see and analyze
the data collected via User ID in your
tracking code, create User ID views.
User ID view – GA view which collects only
the data related to user ID sessions. In the
case of user ID views, GA calculates unique
users by counting the number of unique
users IDs assigned instead of counting the
number of unique clients IDs assigned.
Non-user ID view – the view which collects
data related to standard sessions. It does
not recognize user ID hits. In case of non-
user ID views (regular views), GA calculates
unique users by counting the number of
unique client IDs assigned to users.
1
2
3
4

36
Setting up tracking in web and app05
Once the user id feature is implemented, GA
combine and report all the hits with same user
id, regardless of the device, the hits come
from. This makes cross device measurement
possible in GA.
You can send user id to Google Analytics by
creating a new custom dimension (with user
scope):
ga(‘set’, ‘dimension2’,userId);
A standard session turns into a user ID session
when a user ID is assigned to a user. This can
happen when a user login in the middle of a
standard web session.
User ID property –
turn on user ID setting in GA property

37
Setting up Session Unification06
In Google analytics, by default collected hits can
be associated with a user ID only in a user ID
session and that too before and during user’s log
in but not after the user has logout.
Session Unification
Session unification allows hits collected before
the User-ID is assigned to be associated with the
ID, so long as the hits are from the session in
which an ID value is assigned for the first time.
When OFF, only data with User-ID explicitly
assigned can be associated.
Add the uid parameter in each hit. So a hit
might look something like this:
http://www.google-
analytics.com/collect?v=1&_v=j16&a=164718749&t=pageview&
_s=1&dl=https%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fcutroni.com%2F&ul=en-
us&uid=hsjfy4782jduyth6k4
User ID HITS Non- User ID HITS
User ID Sessions Non- User ID Sessions
User ID hits are processed separately from non-
user ID hits.
By default collected hits can be associated with a use
r ID only in a user ID session and but only before and
during user’s login but not after the user has logged
out.

38
Understanding the difference in reports07
User ID data can only appear in a dedicated User ID view. To see and analyze the data
you collect via the User ID in your tracking code, create User ID views in your account and
then understand the difference.
User ID session – It is the session in which a user ID is assigned to a user. User ID
session is a collection of user ID hits but may also include non-user ID hits if the session
unification setting has been turned ON.
Non-user ID session – it is a collection of non-user ID hits. If you are not using the user
ID feature then the non-user ID sessions are simply known as sessions.
Example differences:
1. User ID views only report on the users which triggered the user ID sessions. So,
the number of unique users reported by nonuser ID views are usually more than the
number of unique users reported by user ID views.
2. Revenue in a user ID view is based on users and not sessions.

39
Setup and reporting08
Adding the User-ID to website tracking
Adding a User-ID to the JavaScript code is fairly
easy – it’s a single line.
ga('create', 'UA-XXXX-Y', 'auto');
ga('set', '&uid', {{ USER_ID }});
ga('send', 'pageview');
Adding the User-ID to the Android SDK
t.set("&uid", {{ USER_ID }});
Adding the User-ID to the iOS SDK
[tracker set:@"&uid" value:{{ USER_ID }}];

Offline Tracking
for
Offline-Online Attribution
3

Let’s look at a broader perspective of
a purchase.
The complete purchase cycle is one
transaction regardless of the actions
being performed offline or online by
using one associated user
Mapping ALL events as part of one
transaction helps us mimic an
ecommerce portal and assign each
action a value in the whole purchase
process.
Transaction ID
Upload data via
API or FTP
Transaction ID
matched
User data with
Transaction ID
User purchase journey with business

OFFLINE TRACKING
User ids can be set for all of these authentication systems with the help of
measurement protocol but the implementation is not going to be easy.

Building Custom Attribution Model & Reports
For all digital touchpoints covered until now, we
have used ’login’ for the user authentication. Other
users’ authentication systems widely used for offline
tracking are:
1. Biometric identification (like retinal scan,
fingerprint scan, iris recognition, voice
recognition, Digital Signatures or Digital
Signage, etc)
2. Punching cards to record attendance (like atten
dance of employees)
3. Wrist bands (like the one used by Disney)
4. Retail loyalty cards (used by many supermarket
chains)
5. Online and offline Coupons

+ What type of user behavior do you value?
+ Is there an optimal conversion window you are solving for?
+ What does the repeat purchase behavior look like historically?
+ Are there any microConversions defined with engagement type goals, tied to the economic value?
+ Are offline conversions being sent back into GA using Universal Analytics?
Context in making the decisions that will go into a custom attribution model.
The Acquisition channels can be:
1. Digital Marketing Channels (like paid search, organic search, email marketing, direct traffic,
referral traffic, display advertising etc.)
2. Offline Marketing Channels (like radio, TV, Billboard, Magazines, Newspapers etc)
The objective of attribution modelling is to understand the buying behavior of your website visitors:
# Why people buy from your website?
# What happens before they make a purchase?
# What prompted them to make a purchase or complete a predefined goal?
# Which are the most effective acquisition channels for investment.
Building Custom Attribution Model & Reports

Multi-Channel
Tracking
Cross Device
Tracking
Offline-Online
Tracking
Online Conversions
Advertisers See Today
Cross Device
Conversions
Store Visits + Calls
Summary

Identify the channels your user
uses to reach you.
Improving traffic channel tracking
with Marketing channel definitions
and campaign tracking guidelines.
Synchronize user experience
across devices.
Cross device user tracking
capabilities by implementing Visitor
Ids and App Ids
Take a complete view of your
user journey online and offline.
By introducing data mapping
capabilities from various channels
into analytic tool and mapping
important user actions as part of the
user transaction.
Multi-Channel
Tracking
Cross Device
Tracking
Offline-Online
Tracking
Summary

Launch
[2 month foundation]
1. Identify initial personas and segments to target per channel.
2. Establish the content needed to support each group (what do you
want to serve up to each segment and persona and to what degree?)
3. Establish rules for serving content (if User X indicated he or she is Y
in user profile then serve up this content) per channel per user task.
Evolution
[9-12 months post launch]
1. Test existing content by running ongoing metrics and audits to see
how consumers interact with the content experience.
2. Identify additional areas, such as enhanced cross-sell, up-sell.
3. Test assumed customer journeys across channels to verify accuracy
and optimize content performance.
Enrichment
[18+ months post launch]
1. Integrate omnichannel for all channels.
2. Leverage new or emerging technologies and techniques.
3. Optimize per business needs, analytics and consumer trends.
Omnichannel Attribution Roadmap

ATTRIBUTION
MODELS
The readymade attribution models from the google solutions gallery

Are we there yet?
Connect with us for any consultancy and implementation support.

Web: www.metriplica.com
Email: Shivam@metriplica.com
Of.Barcelona: (+34) 93.328.40.54
Watsapp: (+91) 8800104714
Of.Kuwait: (+965) 98080216
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Omnichannel Attribution Modelling

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