Guha Athreya, Sr. Manager, Customer Analytics - AbsolutData, discussed various approaches to maximize ROI and generate incremental business in a multi device, multi channel environment. He also discussed this topic by sharing some cases and experiences in Travel & Hospitality sectors. AbsolutData is a global leader in applying analytics to drive sales and increase profits for its customers. AbsolutData has built strong expertise and traction with Fortune 1000 companies across 40 countries. We specialize in big data, high end business analytics, predictive modeling, research, reporting, social media analytics and data management services. AbsolutData delivers world class analytics solutions by combining their expertise in industry domains, analytical techniques and sophisticated tools.

1. © Absolutdata 2014 Proprietary and Confidential
Chicago New York London Dubai New Delhi Bangalore SingaporeSan Francisco
www.absolutdata.com
April 29, 2014
Driving Marketing ROI across On-Line
and Off-Line Channels
An approach to maximize ROI and generate incremental
business in a multi device, multi channel environment

2. © Absolutdata 2014 Proprietary and Confidential 2
Absolutdata snapshot
Company Overview
 Founded in 2001, Absolutdata is a pioneer in delivering
consulting-oriented advanced analytics services to a global
client base
 It helps clients understand their customers better by
statistical data analysis and delivering key analytics that help
enhance their own value
 Senior management from
McKinsey, Kraft, Pfizer, Mitsubishi, Nielsen, GE, and HSBC
 400+ employees across San Francisco, Los Angeles, New
York, Dubai, Singapore, London and Delhi
Mission
To empower forward-looking
organizations to reach new heights
of business performance through
the optimal use of data
Services Provided
CRM ME
Data Visualization
& Reporting
Market Research Big Data
Corporate Philosophy

3. © Absolutdata 2014 Proprietary and Confidential 3
In a Multi Channel, Multi Device Ecosystem, adding the reported impact of all on-line and off-line channels gives
a number higher than company’s revenue
Find the True Value
30% 45% 60% 20%
100% ???
The attribution problem

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Prediction
Media
 On-line
 Offline
External
 Competition
 Technology
 Demographic shits
 Macro economics
Revenue
History
The root causes….
Revenue is impacted by many drivers beyond just
Media Investments
Media channels work together, but each channel
reports all of the synergies
Other Marketing
 CRM
 Direct Marketing
 Pricing
 Distribution
Operations
 Supply
 CSAT
Sometimes Modeling efforts result in over-fitting History and don’t focus on Prediction Accuracy

5. © Absolutdata 2014 Proprietary and Confidential 5
Absolutdata’s Approach to revenue attribution
Phase 1- Holistic Base Model, Market Mix
Holistic approach incorporates all drivers
Appropriate level of modelling sophistication - OLS, HB etc
)) ((Daily
Signups
Baseline
sales
Regression
Coefficients
Level of Media
Effort
Regression
Coefficients
Other Factors
Phase 2- Refinements, e.g. Structural Equation
Models
Assess Synergies, Refine Attribution
Phase 3 – Triangulation e.g. Cookie
Data, Discrete Choice Models
Search
Clicks
TV Impacts
Display
Impressions
TV GI
Search
Clicks
Email
Campaign
Print Affiliates Display
Over all
Signups+ + + + +
TV
Impacts
TV Impacts
Secondary Relationships
Attribution’s % impact of
each media channel drives
daily proportions
Cookie data captures Unique ID
activity and measure recency
and frequency

6. © Absolutdata 2014 Proprietary and Confidential 6
Russia Ukraine Brazil China Philippines
Poland Serbia Argentina Australia Malaysia
Turkey Spain USA India UAE
Romania Puerto Rico UK Indonesia Saudi Arabia
South Africa Denmark Germany France Thailand
Egypt Belgium Mexico Japan Vietnam
…Consumer Durables…Telecom…Electronics….Retail…CPG…Banking…Online Services…
Building A global knowledge base across verticals

7. © Absolutdata 2014 Proprietary and Confidential 7
Model built on Historical DataDATA TYPES DESCRIPTION
Bookings Individual, Group, Corporate
Media
Online & Offline Spends
Competition
Emails
Delivered, Clicked
Competition
Promotions
Loyalty Promotions
Rate Sales
Competition
Other Drivers
Pricing, Inventory, Locations,
Guest Satisfaction
Competition
Macro Economics
GDP, CPI, Sentiment,
Unemployment etc
Case study in hospitality – Phase 1 results
Bringing disparate data sources together Building a Master Model
Model robustness checked by predicting Recent Past

8. © Absolutdata 2014 Proprietary and Confidential 8
Case study in hospitality – Phase 2 results, phase 3 in progress
Media Impact
7%
Impact of Other
Drivers
12%
Competition
Impact
-1%
Base Line
82%
Cumulative
Effect of All
Past
Marketing
Efforts
Incremental
18%
53.1%
20.5%
14.1%
6.0%
4.1% 2.9%
0%
23%
45.6%
12.3%
8.8%
5.5%
4.5%
0.1%
0%
10%
20%
30%
40%
50%
60%
Search TV Affiliates Display PR E-mail Print
Primary Attribution
After Secondary Attribution
(Actual Contribution from
Model)
Impact of Secondary
Relationship
on Search= - 30%
Impact of Secondary
Relationship
on TV= +25%
Phase 2: Model used to understand Historical Impact
Phase 3: Insights inform planning and ROI
Optimization

9. © Absolutdata 2014 Proprietary and Confidential 9
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For Media related queries -media.relations@absolutdata.com
For all other queries -info@absolutdata.com
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