Post click analysis provides insights into user behavior and revenue generation after users click on ads. It analyzes metrics like location, device used, purchases made, and path to conversion to understand what content and ads perform best. This helps advertisers, publishers, and ad networks optimize campaigns, identify trends, and fine-tune systems. Data is typically presented through tables, charts, funnels and heat maps and should be reviewed on various timescales from daily to yearly to track progress and catch issues.

1. Post Click Analysis
By
The Red Bulls
Harikrishna Natrajan
Rajkunvar Jadhavrao

2. Agenda

What, Why, Who, How, When

What is Post click analysis

Why Post click analysis

Who analyzes

How much to analyze

How to set up analysis

How is data presented

When to analyze

3. What is Post Click Analysis

Most important outcomes of an ad: Response
& Revenue

Get a deeper understanding about the
responsiveness of an ad at various levels &
the revenue thus generated

4. Why Post Click Analysis
Business Benefits

Segment the users & observe user behaviour

Observe market trends

Rank advertisers & publishers
Technical Benefits

Judge the honesty and accuracy of the system

To understand & fine tune the accuracy of the system

Design & implement learning & tuning algorithms for maximizing
future revenue

To build system alerts
− To alert against fraud / discrepancies
− To alert against fatiguing ads

5. Who Analyzes

Publisher
− Find the best performing advertisers
− To profile his users & pitch his inventory to the market

Advertiser
− To gauge the responsiveness of his ads & infer if his campaign message has got through
− To gauge his return on investment
− To find the best publishers
− To plan future campaigns

Ad networks & exchanges
− Operations teams

To fine tune the delivery of ads

To give feedback to the developers about any issues in the system
− Technical teams

To build new algorithms based on the learnings of how the current system functions
in the real world

To remove any discrepancies in the system & put up security & fraud detection
policies

6. How much to analyze

Budget, Requests, Impressions, Fill Rate, Clicks, CTR, eCPM

Geography: Country, Region, City, Locality

Device: Brand, Model, OS & its version

Carrier: Country, Carrier, Circle

Page content: Subject, URL

Event Funnel: For a multiple interaction ad, how many interactions
has a consumer completed

If the following information is available via apps which support user
profile storage / retrieval: Age, Gender, Income / Purchasing power,
Occupation, Likes / dislikes, Hobbies

Custom information which varies from business to business

7. How to setup analysis

Trackers for various events

Cookies, UDID & other device identifiers

Info related to the subject of the consumed
content

User Profile Retrieval from apps

Social Network Integration

8. How is data presented

Tabular & Summarized data

Charts

Event Funnels

Geospatial data

Heat maps

Progress Bar

9. Charts
Share & Domination
Trends
Camparison

10. Funnel
Viewed: 100
Checked
Details: 55
Bought:3

11. Heat Map

12. When to analyze

Real time analysis: Live campaign performance & to check if
campaign budgets are correctly met & capped

Daily review: Daily reports to keep track of progress

Weekly Review: To check weekday & weekend trends & watch out
for discrepancies in the system

Monthly Review: To check performance on regular days & during
occasions

Quarterly Review: To find the best advertisers, publishers & user
segments

Yearly Review: To formulate new plans & strategies