1. © 2016 Karthik Ethirajan, all rights reserved
Measurement Solution for Smart TV
Karthik Ethirajan
October 2016

2. © 2016 Karthik Ethirajan, all rights reserved
2
Agenda
3. Use Cases
4. Data Flow
5. Market Size
6. Revenue Forecast
7. Go-to-market Approach
Product
Business
Case
Strategy

3. © 2016 Karthik Ethirajan, all rights reserved
TV viewing data can be used to more accurately measure
popular metrics such as RF and ROAS
3
Reach is the number of unique HHs
exposed to an ad. Frequency is the
numbers of times it was exposed.
ROAS is conversion (purchase
amount from incremental sales)
over ad spend
Reach & Frequency
(R/F)
Return on
Advertisement
Spending (ROAS)
Enabled by
TV Viewing
Data
Campaign
Data
Safe Haven Environment
Enabled by
TV Viewing
Data
Campaign
Data
Safe Haven Environment
Purchase
Data
Value
Proposition
Results are based on actual measurement, and not extrapolated
from a small panel

4. © 2016 Karthik Ethirajan, all rights reserved
4
Data flow for the RF and ROAS use cases
Ad
Network
Data
Match
• Mobile ID
• Timestamp
• IP address
Target
File
• Campaign ID
• Creative ID
• Advertiser
• Duration
Campaign
Data
Smart TV
/ STB
• Mobile ID
• Timestamp
• IP address
TV Viewing
Data
Report
Generation
R/F
Exposure
Report
• Age | Experian
• Gender
• HHI
Demographic
Data
Enrichment Partner
Data
Match
Attribution
Partner
• Foot Traffic | Ninth Decimal
• Online | Convertro
• Retail PoS | Datalogix
• Auto | Polk
• Credit Card | Amex
Attribution
Data
Report
Generation
ROI
Attribution
Report
Safe Haven
Partner
• PII
• Timestamp
• SKU
• Purchase amount
Matched IDs
Matched IDs
• Double
Blind Match
| Acxiom /
Liveramp

5. © 2016 Karthik Ethirajan, all rights reserved
Measurement TAM is ~4 billion of which TV is an order of
magnitude bigger than digital
5
$531B $582B
2015 2017
Global Ad
Spend
U.S. Ad Spend
34% 34%
$69B $72B
$183B $197B
CAGR
4.7%
3.8%
0%
14%
38% 36%
Global Ad Spend by Medium
TV Ad
Spend
$58B $75B
32% 38%Digital Ad
Spend
TV
Portion
of TAM
• $72B TV ad spend in US
• 50% Measured ads
• 10% Measurement pricing
--------------------------------------
$3.6 billion TAM
Digital
Portion
of TAM
• $75B Digital ad spend in US
• 5% Cross-screen TV ads
• 10% Measurement pricing
--------------------------------------
$0.38 billion TAM
Source: Zenith Optimedia, eMarketer, BI, Karthik analysis

6. © 2016 Karthik Ethirajan, all rights reserved
Smart TV measurement solution revenue forecast &
product pricing guidelines
6
$24
$48
$72
$-
$10
$20
$30
$40
$50
$60
$70
$80
Year 1 Year 2 Year 3
Annual Revenue Forecast (in millions)Revenue Model Year 1 Year 2 Year 3
Market TAM (in Millions) $ 4,000 $ 4,000 $ 4,000
Market Share 5% 10% 15%
RF Use Case
RF Share 80% 80% 80%
Partner Rev Share 10% 10% 10%
RF Revenue $ 16 $ 32 $ 48
ROI Use Case
ROI Share 20% 20% 20%
Partner Rev Share 20% 20% 20%
RF Revenue $ 8 $ 16 $ 24
Total Revenue
Annual Revenue $ 24 $ 48 $ 72
3 Year PV $ 116
Product Pricing Guidelines
 All numbers are in millions
 Discount rate applied is 10%
 TV dominated TAM expected to stay flat
 Market share assumption is based on
incubating a brand new business
 RF will be the predominant use case
compared to ROI reports
 Partner costs for safe haven and
demographic data will be ~5% each
 Attribution data cost is higher around 10%
Model Assumptions
 Pricing should be based on number of
addressable markets rather than
addressable TV sets
 ROI reports are a higher value product and
has more price elasticity, and hence should
be priced 2X or more than RF reports

7. © 2016 Karthik Ethirajan, all rights reserved
7
Key success factors and go-to-market recommendations
Product
Marketing
• Higher the penetration of Smart TV or addressable TV sets denser
the sample points to chart reach and conversions
• Deployment of precise ACR means better quality of data to work
with
• Measurement platform will require some of the same DMP and data
analytics capabilities as that of audience targeting
• Go to market with a branded product, deal direct with advertisers,
pay data partners on the back end as vendors
• Develop agency/DSP relationships as much of the advertisement
dollars flow through these demand agents
• Clearly articulate product positioning: actual measurements as
opposed to panel used by Nielsen
Partnerships • Closed loop attribution require partnerships with offline and online
data providers to provide a complete view of user journey from
discovery to purchase
• Data partnerships should be paid based on usage, not rev share
• Safe haven partners can help boost confidence with respect to
protection of PII data and user privacy