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Facebook
Case
Study:

An
Integrated
Analytics

platform
for
Digital
Ads
Target Audience for the Case Study:
Digital Marketing and Analytics
professionals 1
Analysing
Facebook

Campaigns:
Current
Situation
•  Facebook - a powerful platform. Highly competitive
and (now) expensive.
•  Facebook and Google Analytics offer limited,
standardized metrics for analysis
•  To push efficiencies, deeper and more actionable
analytics needed
•  Deeper analysis is time consuming, as it involves
considerable back and forth between Google
Analytics, Facebook Analytics and Custom
Parameters
2
The
Solution:
An
Integrated

Analytics
platform
•  A custom analytics system that integrates FB
Analytics, Google Analytics, and Custom-defined
metrics with the ability to slice and dice the data in
multiple ways
3
How
It
Works?
•  All metrics in one, customizable pivot table
•  Set date ranges, & custom ranges such as weekdays/
holidays
•  Create custom metrics on-the-fly (For example -
Revenue per 1000 impressions)
•  Custom properties such as Price ranges, Ad themes,
Headlines, Ad copy, Visual elements, etc. available
within the table
•  Organize & track A/B tests with Custom A/B Test
Dimensions
•  10+ Dimensions in a flat table (vs. 2 for Google Analytics)
•  15+ Drilldowns for Dimensions (vs. 5 for Google Analytics)
4
Facebook
Analytics
Google
Analytics
Integrated Analytics Platform
Dimensions Campaign, Ad,
Ad Set,
Audience, Age,
City
Landing Page,
Source, Medium,
Campaign, Ad
Content, Date,
Week, Month,
Devices
All FB & Google dimensions +
custom dimensions such as
Headlines, Adunit Types, Price
Ranges, Product Names,
Campaign Themes, Duration,
Acquisition
Metrics
CPM, CTR,
Reach, Freq,
Spend
Visits, Pageviews,
Unique Visitors
All FB & Google metrics in one
place
Behaviour
Metrics
n/a Bounce Rates,
Pages per visit,
Visit Duration
All FB & Google metrics +
Custom metrics such as:
%Dropoffs, %Interested
Visitors, %Product Page Views
Conversio
n Metrics
Conversions,
CPAs, Revenue,
based on 1, 7,
30 day
attribution
Conversions,
Revenue, CPAs,
Product View%,
Cart View% and
other Custom
Goals
All FB & Google + custom
metrics such as Revenue per
1000 impressions, %Click to
Transaction, %Spillover to
‘Direct’
5
Results
•  Analysis time reduced by up to 90% with no back
and forth between different platforms and custom
parameters
•  Test Campaign Budgets decreased by 75%
•  Minimum Sample sizes decreased by 75%
•  Conversion Rates increased by 100%
•  Avg. Campaign pausing time decreased from 4
days to 1 day
6
Next
Steps
(In
Progress)
•  By observing patterns based on Behavioural metrics for Ad
Campaigns, we can predict which Ad Campaigns are likely to
perform even before any Conversions are observed. For
example:
o  Facebook Newsfeed campaigns having Bounce Rate below X%, ProductView
% above Y% and Product-Page-Drop-Off% less than Z% are likely to perform
well
o  Facebook Right Column Ad Campaigns landing on Product Pages, having
Pages per visit lesser than ‘X’ and Product Page Dropoff% more than Y% should
be discontinued as they are not likely to perform
•  Create Daily Dashboards that show current status and predict
which campaigns are likely to do well
•  Automate and Create mini-algorithms for Pausing Ads,
thereby increasing efficiencies
7
Appendix
A:

Screenshots
8
Unlimited
Dimensions
in
a
flat
table

(vs.
2
for
Google
Analytics)
9
Acquisition,
Conversion
and
Custom

Behavioural
Metrics
‑
All
in
one
place
10
Unlimited
Drilldowns
for
Dimensions

(vs.
5
for
Google
Analytics)
11
Thank
you
For more details, contact me at:
harshilad@gmail.com
+91 9582211952
Harshil Adesara
12

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