This is the public version from various client work reviewing the digital advertising ecosystem and the seismic changes occurring in the advertising industry. This looks at marketer metrics, ad exchanges, economics and issues around privacy (very short) and use of data and targeting. Greg Stuart +1 631 702 0682

1. review of the digital
advertising ecosystem
by greg stuart
www.gregstuart.com
january 6th, 2010
Prepared by Greg Stuart
greg@gregstuart.com 1
Confidential

2. purpose & agenda
Purpose: Provide background for a discussion on
the ever changing Advertising Ecosystem.
Topics as follows:
1. Marketers‘ Metrics discussion
2. Digital Media Ecosystem review
3. Data & Targeting discussion
4. Three Screen discussion
5. Privacy principles Author‘s Background: Greg Stuart
Decade as NYC Ad Agency Media Strategist
6. Appendix Decade+ as Sr Exec in Digital Media
CMO, VP Biz Dev, Ad Sales, CEO
o Terms & difinitions Digital Media since 1993 (iTV & Web)
o Advertising Spending review CEO of IAB – Interactive Advertising Bureau
Co-Author What Sticks
Advisor to VC‘s & 15+ Net/Mobile Businesses
Consultant to Alcatel, AT&T, etc (see appendix)
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3. main themes
1. Change is everywhere & constant
2. Advertising has never been so complicated…and yet
so ill prepared for the future (tech, data, automation)
3. Exchanges are likely to tremendously transform the
digital advertising & media world
4. Data is the talk of the digital town; but the value of
data is still quite unclear
5. Marketer‘s metrics were indeterminate before and
will be murky for awhile
6. Privacy at a regulatory level is anyone‘s call at this
point (but can be managed)
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4. confused?...not surprised
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5. internet is a still evolving as a medium
„New to Net‟ Commun-
Services Retail Contributor
User ications
• First activities • Email • Online • CDs/Books • Blogs
• ISP & ease • IM banking • Complex • Comments &
• Info. search • Photo sharing • Simple Travel travel posting
• LOTS of time • Early social guys • eBay Motors • Customer
surfing networks • Auto info • Groceries reviews
• Ratings
Web 1.0 Web 2.0 Web 3.0
Source: Nielsen/NetRatings
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6. all media under assault – from consumers
o Lot‘s of multitasking + DVR‘s promote ad skipping television
o The net result is that each ad is less effective as consumers mentally and
physically tune them out
How often do you surf the internet at the same time Do you use your Tivo or DVR to skip
as watching TV? television ads? Skip
Some sds
36%
Seldom 16%
Never 26%
Watch
Sometimes Most Ads
26% 6%
Never Skip
Ads 6%
Always 17%
Skips All
Ads 52%
Usually 15%
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7. digital advertising more complex than ever and
the options more diverse
Outbound
IM communication iPhone apps
Email SMS/MMS
Streaming Display
marketing marketing
Podcasting Online Microsite
advertising development
Website
Development Influentials
Viral
INTERACTIVE AD Seeding
CHANNEL
Online WOM Blogs
Branded
entertainment Microblogging
Search App CRM
Video - YouTube engine mktg Development RSS
application
SEO Widgets
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8. …and yet ads, ads, ads - everywhere
Estimated 4,500,000,000,000
(4.5 trillion) online ads served annually
= 2,000 ads per person per month
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9. marketers‟ metrics
discussion
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10. metrics summary
Online is often more cost effective than other media. Have
seen 10x in cost per value versus TV.
• In part because TV is SO overspent
Internet is not a single medium (it‘s really a platform of mediums)
Click has been everything. But it is the bain of the internet
medium. Soon to mean nothing (or at least little)
Only 8% of consumers click regularly (only 16% ever click)
Publishers like CPM, as it‘s easy to measure, control, etc.
Marketers metrics are CPA, CPL, CPT, engagement, etc. -
Confused yet? Should be!
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11. 35% of marketers use clicks; but click is such a
small percent of activity
Source: DoubleClick DART for Advertisers: 2008
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12. however; there is a MASSIVE decline in display-
ad click through rates
In 2008,
comScore
measured click
rates as less
than 0.1%
Sources: DoubleClick, eMarketer, Eyeblaster, ABI Research estimates
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13. and virtually no one clicks anymore
There are Fewer Clickers and Fewer Heavy Clickers
o There are fewer heavy clickers today: down from 6% to 4% of Internet users
o Only 8% of all Internet users account for 85% of all clicks
Source: comScore, Inc. custom analysis, Total US Online Population, persons, July 2007 and March 2009 data periods
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14. but there is no question online ads work
Advertiser Site Visitation Among US Internet Online Advertising‟s Effect on Brand Metrics
Users Exposed to Online Display Ads, 2008 in the US, Q4 2008* (% of Resp impacted)
7.0% 65.0% 70.0%
Control Test Lift
6.6%
6.0% 53.8% 60.0%
(Δ 2.4)
5.8%
5.0% 50.0%
49.1% 45.7%
4.8%
4.5%
4.0% 40.0%
3.9% (Δ 1.6)
3.5%
(Δ 1.3)
3.0% 30.0%
3.1% (Δ 4.9)
2.0% 20.0%
2.1% (Δ 2.6)
1.0% 10.0%
0.0% 0.0%
Week following Weeks Weeks Weeks
1st ad exposure 1-2 after 1st 1-3 after 1st 1-4 after 1st
exposure exposure exposure
Note: home, work and university locations Note: n=2,380 campaigns and 3,889,602 respondents;
Source: comScore Brand Metrix, “How Online Advertising *includes three years through Q4 2008; **delta (Δ ) defined
Works: Whither the Click,” December 5, 2008 as point difference in exposed vs. control groups
Source: Dynamic Logic provided to eMarketer, April 27,
Prepared by Greg Stuart 2009
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15. publishers may have better effectiveness
Ads on content sites have greatest impact
o Ads on content sites raise Awareness, Message Association, Brand Favorability and
Purchase Intent more than Portals and Networks
o Ad Networks provide advertisers with the smallest change — including no change in
Purchase Intent (i.e., 0.2 delta is statistically insignificant)
Ad Effectiveness Deltas by Site Category
Aided Brand Online Ad Message Brand Purchase
Awareness Awareness Association Favorability Intent
OPA BCD 3.2 5.7 3.4 2.4 1.8
MarketNorms 2.3 4.7 2.5 1.5 1.2
Portals 2.5 4.7 2.1 1.3 1.1
Ad Networks 1.2 3.8 2.0 0.6 0.2
Notes: Ad effectiveness deltas in red are statistically insignificant (i.e., there is no change)
A/B/C/D indicate statistically significant difference between deltas at .90 CL
Source: Dynamic Logic’s MarketNorms campaigns over last 3 years through Q1 2009
OPA N=1,540 campaigns; MN = 2,255; Portals = 1,224; Ad Networks = 399
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16. But ad networks provide lots of brand lift also
Ad Network Sites Publisher Sites
Control Exposed Impact Control Exposed Impact
Unaided Message Recall: XXXX 0% 13% +12.9 15% 16% +1.3
Message Association: XXXX 3% 8% +4.9 7% 7% +0.9
Message Association: XXXX 4% 8% +4.1 9% 9% 0.0
Online advertising recall 21% 31% +9.7 34% 39% +4.7
Purchase Intent 42% 53% +10.8 39% 45% +5.8
Recommendation Intent 8% 21% +13.6 13% 15% +1.4
Actions Taken
Consider purchase 12% 24% +11.4 15% 15% +0.3
Download free trial 10% 20% +9.9 11% 12% +0.9
Visit website 11% 25% +14.2 19% 21% +2.0
Gather more info 15% 22% +7.1 17% 19% +1.7
T2 Box: Overall Opinion of Brand 48% 56% +7.8 43% 50% +6.9
Brand Opinions (Top Box)
Is high quality 26% 29% +2.7 19% 24% +4.9
Always up-to-date 24% 29% +4.2 22% 25% +3.1
Is best in the category 16% 18% +2.3 10% 14% +3.9
Has improved their product 15% 17% +1.6 8% 11% +3.4
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17. best campaigns for sure work on ad networks
Best / Worst Performers on Ad Networks
Market Norns Avg Top 20% Ad Networks Avg Ad Networks
16.00%
14.00%
12.00%
Percent Impacted
10.00%
8.00%
6.00%
4.00%
2.00%
0.00%
Aided Brand Online Ad Messsage Brand Purchase
Awareness Awareness Allocation Favorability Intent
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Source: Dynamic Logic Market Norms database

18. online is best able to measure but the
hardest to measure
More than half of interactive marketers —
51% — interviewed by Forrester say that
measuring ROI is their key challenge with
display ads…
…with 38% saying developing good creative is a problem
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19. metrics simplified – there 3 elements
Promote + Found
o Media Questions a marketer should be
o Search (natural & paid) able to answer:
o PR o How many visitors, leads and
o Social Media + Blogging customers am I getting?
o What is driving those visitors,
leads and customers?
Convert o What are my best and worst
o Landing page optimization sources of leads and sales?
o Lead tracking
o Lead management
How can I grow sales?
Analysis How can I lower marketing
o Marketing Analytics costs?
o Lead Scoring
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20. different marketers have different needs
Advertiser Orientation
Direct Response
Brand Marketers Call to Action Marketers
Marketers
Goal is to increase brand awareness, Spending to accomplish a near- Advertisers primarily focused
imagery, and purchase intent term action (traffic, order, etc) on capturing the immediate
Mixes brand spend, but with a action, order, etc
mechanism to drive action too
National 64.0 76.4 8.9
Brand
1.3 3.3 9.1
Customer base
Local affiliate
of a national Revenue, 2007
$ billions
chain 30.2
advertiser 1.3
CAGR, 2003-07
Local percent
“mom & pop” 53.2
Retailers 1.3
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21. metrics for measuring success
Most important metrics for measuring online marketing campaign success according to US*
Senior-Level Marketing Executives by budget size, Feb-Mar 2009 (% of respondents)
$1 million All resp.
+ (n=49) (n=112)
Conversions or sales 82% 70%
Registrations/Subscriptions via organization‘s Website 55% 52%
Click-throughs 51% 49%
Unique views to Website or page where ad or content was placed 51% 37%
Boost in search rank 39% 34%
Downloads of data or information 33% 37%
Change in target audience awareness/perception of brand 31% 25%
Customer feedback on Website 16% 26%
Number of target audience members reached 14% 13%
Streams of video or audio content 8% 6%
Other 6% 3%
Note: 8respondents were primarily based in the US
Source: Forbes, “2009 Ad Effectiveness Survey,” June 1, 2009
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22. advertising metrics - relationships
Measurement
CPM CPC CPA CPI RPT LR
Metric
Customer &
Profit
Potential Cost Per Cost per Cost per Cost per Revenue per Lifetime
Customer by Thousand Click Acquisition Inquiry Transaction Revenue =
Source
Guesstimated
Relationship
$ 1.00 $ 0.25 $ 0.75 $ 0.95 $ 1.50 $ 4.25 = $ 3.30
Allowable: $ 1.65
Allowable = What would company pay to acquire customers
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23. Impressions
Clicks
Conversions
Revenue
Unique Impressions
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Unique Clicks
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Unique Conversions
Click through rate
Click to conversion rate
Impression to conversion rate
Ad Exposure Time
View Through
Ad Interaction Rate
Interaction Time
Ad Component Interactions
Video Play Rate
Average Video View Time
Video Completions
Replay Rate
Reach
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Frequency
Frequency vs. Response
Frequency vs. Conversion
Time Lag to Conversion
Ad Delivery Rate
Attrition Rate
Lead Generation
Revenue per Sale
Revenue per User
Revenue per Impression
There are a number of possible metrics or points of
Revenue per Click
Revenue per Visit
Repeat Purchase Rate
Lifetime Revenue
expanded list of possible metrics
measurement for marketers in digital media, 30 or more.
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24. alt: msn‟s engagement measurement
msn has popularized and development tech to support ―engagement
measurement‖.
It recognizes that other advertising, might have played a role (delivered value)
to the final click.
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25. alt: cross media analysis
Like MSN‘s engagement mapping, some
work has been done to isolate a medium‘s
value, and in combination.
Research behind What Stick‘s found that
Internet was most Cost Effective Medium
in 75% of campaigns
Optimized media plans delivered
+30% lift in media
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26. is there a blurring of search & display?
Traditionally:
o Search=performance (clicks, action, etc)
o Relevance, technology, ease
o Display=branding (attitude change)
o Graphical, context, rich media
However, their objectives can be blurred:
o Search been proven to provide brand value
o Display can provide performance
But they are different:
o Ease of text – alteration, speed, pervasive
o Technology and scale
o Commensurate advertiser base (really important)
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27. final thoughts on metrics
Clicks have ruled (counterproductively so)
Alternatives: Analytics systems permit reaching deeper
o View thru (30 days post the activity)
o Brand or performance later in process
Better tools coming: Factor TG, Market Share Partners
But as a result of it‘s inherent advantages, digital media
wins (ROI, immediacy, integration, optimization, more)
o Mobile is just not ready, but is heading in the right direction.
o iTV is likely a long ways off.
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28. digital media
ecosystem review
peeling the layers of an increasingly
complicated ad ecosystem in the
increasingly digital-networked
advertising industry
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29. summary ad ecosystem
More disruption than ever & at nearly every level &
category - publishers, local, agencies, media...
Exchanges potentially change everything
Critical to Exchanges is application of data
What could happen:
o Shift away from networks to exchanges
o Exchanges follow Direct Mail & Search going direct to
Advertiser
o Agency media department becomes less important
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30. the times, they are a-changin‟
bob dylan
Traditional definitions range from the
broad to the specific…
“Intermediaries that enable advertisers to …But the landscape is evolving as new types
reach audiences across the web, and allow of players emerge
publishers to better monetize inventory.”
CIBC analyst report Ad Exchanges eliminate the typical ―broker‖
role by linking publishers directly with
advertisers via a managed transaction
“Aggregates advertising inventory from a platform (e.g., Right Media)
number of websites and sells this inventory
to advertisers or agencies.” Rep firms market inventory from select
publishers to advertisers, functioning more
Piper Jaffray Investment Research as an outsourced sales force than a reseller
(e.g., Glam)
“Brokers of online inventory. Ad networks will
buy inventory from a publisher, then resell to Specialist providers of sophisticated value-
an advertiser, pocketing the spread” add services such as targeting and ad-
serving (e.g., Revenue Science) serve both
CIBC analyst report publishers and advertisers without brokering
any inventory
“Appliers of sophisticated targeting analytics
to serve advertising for third parties”
CIBC analyst report
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31. the digital value chain
Advertisers Agencies Inventory Programmer/ Distribution Measurement
(creative/strategy) Influencers publishers platforms
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32. expansion of the value chain
Advertisers Agencies Inventory Programmer/ Distribution Measurement
(creative/strategy) Influencers publishers platforms
Ad- Agencies Agency Data Exchanges Networks Pub. Prog./
vertisers Support/ Clearing- Support Publishers
Buyers houses
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33. players in expanded value chain
Ad- Pub. Prog./
Agencies Agency Data Exchanges Networks
vertisers Support Publishers
Support/ Clearing-
Buyers houses
• SEM • Technology
• Digital media platforms that
buying agency enable the • Yield optimization
• Single-source bid- companies that
buying and
management tool enable publishers to
selling across
• Automated system that maximize the value
multiple ad
• Ecommerce manages and optimizes of their inventory
networks and
site on bidwords for advertisers across multiple ad
publishers real
AdWords based on conversion rates networks and
time
• Local • Algorithm-based platforms exchanges real time
storefront in that maximize ROI on ad
Yellow Pages network and exchange
• Major brand inventory buys on behalf of
brands • Search engine
advertiser
aggregators
focused on
• Centralized ad selling
specific
demographic • Not directly involved in the buying and entity that sells • Search engine
selling of advertising, but either facilitate typically remnant ad • Website
the transfer of data between parties in inventory across owner and
the value chain, or aggregate data from multiple websites, operator
several parties and make it available to either blindly or
Prepared byby Greg Stuart players in the value chain Confidential
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34. representative players in value chain
Search Intent Driven Media
Advertiser Agency Agency Support / Buyer Ad Networks Publisher/ Content
Advertisers Agencies Inventory Programmer/ Distribution Measurement
(creative/strategy) Aggregators publishers platforms
Broad Scale Media
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Advertiser Agency Agency Support /
Confidential
Data Exchanges Ad Networks Publisher Publisher/
Buyer Clearinghouses Support Content

35. all the details – source gridley & co.
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36. exchanges-likely biggest change ever
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37. exchanges - new kids on the block
Question Answer
Publishers provide a slice of their inventory to exchanges so that
What do Exchanges permit? advertisers can select just the inventory they want, sometimes
calculating value from upwards of 50 data elements
What makes them so interesting Real Time Bidding technologies that can both cherry pick inventory
to the industry and provide immediate feedback
In addition to RTB, the integration of data and access to data on that
What make exchanges work?
user or individual impression
No straightforward answer to this question, because exchange
What are typical exchange
inventory falls into buckets. That said, most inventory is acquired for
CPMs?
$0.10 – $2.00 CPM
Exchanges typically receive (only) 5% to 10% of revenue on
What are typical exchange impressions they serve. (Networks, the current middle man, are 25%
margins? to 50%). Too early to tell but likely will scale; it takes very little to run
an exchange
How much exchange inventory
Hard to quantify, but generally reported to be tens of billions
is available?
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38. how exchanges use data
Advertisers are able to sort through dozens of impression attributes (and cherry-pick
billions of impressions) to choose impressions to buy. Data are used to select and
optimize exchange impression attributes and bring high value than just context or time
of day
There appear to be two current data pricing models:
o Cost per Cookie by BlueKai with is a simple auction model: Cookies with series of data about
users are auctioned for around $2-3 per thousand and buying can buy that cookie for as long
as cookie lives.
o Percent of Spend by eXcelate / % of value model: The data provider receives a percentage of
the media value (currently 20%)
Other Internet data players:
o Next Action (SKU level data)
o Acerno (eCommerce data owned by Akamai)
o Revenue Science (BT)
o Media6º (Social Media – Birds of a Feather)
o Lotame (Social Media)
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39. will there be a network shakeout?
Yes, Likely.
Supposedly 300+ networks. Some are generating
~$100 million in revenue.
They do the work that agencies are too lazy, or
economically unable, to do
Key elements: Tech, Marketing/Positionings, Ad
Sales (Relationships), Publishers (Content)
Exchanges make the publisher segment
unnecessary. Tech is critical.
Positioning is really necessary for a network to
survive. Possible positionings: Brand,
Optimization, Category/sector, Metric, etc
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40. economics' of the ecosystem
$1.5M-$3M
per Sales
Person
Ad Serving (DART, Atlas)
Ad Serving (DART, Atlas)
CPM
$1-5
2.00 CPM
$0.10 CPM
$0.50-
$1.00
$0.01
5¢- 5¢-50*¢ 7¢-
* Short term 5¢-10¢ 25¢-50¢
12¢ arbitrage gain 15¢
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41. underpinning data & targeting are cookies
Cookies, or the tracking of users from one session
to the next and one site to another, is critical to
using data & targeting.
Cookie deletion by users is rampant. Upwards of
nearly 50% of users delete cookies a month.
Private study conducted amongst trusted sites
showed a real variation in deletion rates.
Current industry thinking is that cookies are at
great risk due to regulatory
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42. overall, 36% users delete cookies monthly
“Multi-user computer”
Rejecters 16%
Selective 20% “Periodic”
Users
“Bipolar”
Acceptors 64%
This data is proprietary & confidential – do not forward.
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43. …and some sites saw nearly 50% cookie deletion
Cross Site User Breakdown
100%
18% 20% 17% 13% 13% 14%
90%
20%
80%
17% 13% 18%
19% 14% 26%
Percentage of Users
70%
29%
60%
50%
74%
40%
63% 66% 69% 68%
30%
57% 51%
20%
10%
Rejectors
Inconsistent
0%
Acceptors
Site A (8-27-05 Site B (11-17- Site C (9-1-05 Site D (2-14-06 Site E (2-22-06 Site F (2-01-06 Site G (2-01-06
thru 4-20-06) 05 thru 4-19-06) thru 1-31-06) thru 4-20-06) thru 4-01-06) thru 4-20-06) thru 4-20-06)
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44. measuring cookie deletion – how it was done
1.) Large population of web
users who regularly log into a
2.) A tracking pixel associates the
registration oriented site.
user’s persistent ID with the 3rd
party cookie each time they login
3.) If users return with different 3rd party cookies,
we know they must have deleted their cookie.
P u b lis h e r ID 3 rd P a rty C o o k ie D a te
ABC 123 5 /1 /2 0 0 5
ABC 123 5 /2 /2 0 0 5
ABC 123 5 /9 /2 0 0 5 Person who did not delete their cookies
ABC 123 6 /5 /2 0 0 5
DEF 456 5 /8 /2 0 0 5
DEF 456 5 /1 6 /2 0 0 5 Person who deleted their cookies sometime between 5/16 and 5/20
DEF 789 5 /2 0 /2 0 0 5
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45. the buy/sell process - today
1 Buyer decides
1.
what web sites to
buy
3 5
2
2. Buyer and Seller Publisher Side Sales Planner
negotiate deal
3
3. Hand off to Sales Executive Pub Ad Operations Account Manager
internal teams for
workflow Inventory
4
4. Buyer ad ops Campaign
sends ads to
avails &
mgmnt Reporting Billing
publisher reservations
5
5. Seller ad ops
workflow
(sales tools)
inputs ads
6
6. Buyer reviews 4 7
results, compares
reports, compiles 2 Media Campaign
7
7. Seller sends bill Billing &
planning & Mgmnt & Reporting &
Agency Side
to buyer recon-
8
8. Buyer reconciles buying trafficking analytics
ciliation
the bill and pays workflow workflow
Pre Buy Media
Research Tools 6
3 8
1 Media Buyer
Associate
Media Buyer
Agency Ad
Operations
Associate
Media Buyer
Billing
Coordinator
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46. What‟s moving where / when
Exchanges are the most significant change to advertising
since Google.
1. Loads of inventory (10‘s of Billions)
2. RTB (technology) drives the efficiency for system
3. Players and technologies are just being established
Networks that are not differentiated or have some unique
attribute likely to be squashed.
DSP=Demand Side Platforms are taking the planning out of
the media plan=affect on agencies
Data here is critical and yet value is still unclear
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47. data & targeting
discussion
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48. summary - why data has an allure
Value of targeting & tech - Google $95 eCPM
o Key is a intent-driven targeting system with 100k‘s of
advertisers & self service
Net, targeting (and the data to support) are very
alluring to advertisers and publishers.
Categories of data: Context, Intent, Identity
o Content; ecommerce, social, non-web, etc.
o Unclear as to where uniqueness might still be
Some question the real value (but not sure yet)
Requires new understanding of metrics, or at least
analytics
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49. theory behind targeting – good for all
Advertiser‘s out Media
Cost per thousand Number of viewers
of pocket spend provider‘s
(CPM)
revenue
1,000 viewers for a
given media property
Current TV $10/1,000 viewers 500 500 $10 $10
(example)
Advertiser A really only wants to
reach half of them but they can‘t be
broken out
. . . lower out of . . . higher total
Increase CPM . . . pocket per revenue to media
advertiser . . . provider
1,000 viewers
$6 For Adv A
Digital
Addressable $12/1,000 viewers 500 500 $12
(example) $6 For Adv B
Sell to Sell to
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50. how does „intent‟ affect pricing
Index to
CPM Implied CTR
Exchanges
High Transactional
Value (e.g. CNET,
~$100 15.0% 15000
WebMD, private jet
websites)
Google Search $95* 12.2% 12000
Cars.com $30-40 4.7% 4700
Forbes $25 3.3% 3300
Branded News
$15 2.0% 2000
(NYT)
Portals $2.80 0.4% 400
Networks $1-2 0.2% 200
Exchanges $0.10-1.50 0.1% 100
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51. ad spending trends-behaviorally-targeted
In millions
Source: eMarketer
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52. sources of data
Web Visiting & Viewing Demographics
• Self-reported and validated
• All web site/page click stream
• Appended segments (e.g. Claritas, Acxiom)
• Content viewed
• Individual & household level
• Search engine queries
• Keyword used
Marketing Stimuli
TV Viewing • Online ads
• Link to digital set • Referral links
top TV data using
name and address
Online Transactions
Offline purchasing • All secure session activity
• Linked using name and address • Purchases and subscriptions
• Client CRM databases • Price paid, shipping & handling, promotions
• Retailer loyalty card data • Applications/configurations
• IRI Scanner panel data
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53. different data is available on platforms
Consumer Info Data Example Mobile Internet TV
GPS Location Store or street location (Main & 1st street)
Context
IP address 127.159.456.37
Concurrent media use Net & TV, Mobile & TV, etc
Content Mazda review
Daypart Lunch Breakfast or weekend shopping
Zip code 11932
Calls placed (to who, frequency) Calls to order lunch from deli daily
Family plans Family of five, etc
Usage patterns (when & where) Uses phone in the car, Internet on the road
Interests - Intent
Type of handset or upgrade Bought an iPhone early, Brand buyer, not price
# of e-mails/texts sent/received Sends ~xx texts/day indicates age/engagement
Coupon activity Uses coupons for consumer package goods
Location patterns Goes to shopping, mall, or restaurant
Apps/downloads Downloaded ―mint‘ app
Purchases Bought TV from Best Buy.com
Shopping cart Considered TV from Amazon.com
Content viewing history Frequent News viewer, Recent Auto Shopper
Ads seen/clicked on Clicked on mortgage ad
YP.com searches Sought: ―‖Plumber in Portland:
Other searches Searched: for ―TV reviews‖, Used Cars, etc
Identity
# of unique people called Frequent callers are influencers
Device owned Android owner
Psychographic segment ―Urban Dweller‖
Registration (address, etc.) Name, address, etc
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54. the ability to drive incremental value from data
and targeting depends on 4 key elements
• Do the insights • Can the data be
from data really used in ways that
help advertisers consumers are ok
meet key goals? with?
Value Privacy
• What unique data • Can the provider
is available for process the data?
use?
Uniqueness Capability
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55. data helps advertisers better meet specific goals
Category of Data Why is it valuable? Specific data types
Provides insight on the setting • Contextual (what content are
in which a consumer views they viewing)
Context an ad (e.g., while reading a • Day Part (when)
• Geographic (where are they)
laptop review). Some think • System (with what device)
context really matters.
Allows marketers to direct ads • Actions (purchases, click/buy
Behavior to consumers based on history, views)
Interests-Intent actual behavior (e.g., in the • Preferences (affinities, interests,
market for a house) intensions)
Allows identification of • Demographic (who)
Personal demographic & • Psychographic (market segment)
Identity psychographic segments
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56. “Project Canoe” has been formed to bolster MSO advertising
revenue through set top box targeting
What is Project What is the What is the
Canoe? aspiration? status? No single Telco / IPTV
providers manages sufficient
scale of subs to effectively
• Consortium of six • The cable • David Verklin was counter the breadth of Project
Canoe reach
cable providers companies currently named CEO and
(Charter, Cox, Time capture just7% of piloting has begun in
Warner Cable, total TV ad spend select demographics
Cablevision, but hope to increase • Project has garnered
Comcast & Bright ad revenue by 3 $150M in initial
House Networks) to times to nearly $15B funding from the
deliver targeted, consortium partners
interactive ads to
viewers (estimated
60M set top boxes)
• The consortium will
sell data to
networks, who in
turn will sell to
advertisers
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57. who get‟s the value from Data
Currently:
• Marketers should get the value. Perceptually they do. Word on
the street, in reality they are not right now.
• Publishers ultimately should get the value. But they don‘t cause
they can‘t sell that small inventory
• Networks/Exchanges probably get most of the value. They have
the scale and need the differentiation.
Future:
• Ultimately, those that hold and process the data probably get the
most value. If that data is unique and not acquirable elsewhere.
Data turned in insights likely matters most.
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58. three screen discussion
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59. it‟s supposed to be media planning; not medium
planning
Three screen holds allure because:
o Access to a consumer cross-media at their different access points via
different messaging value is intriguing
o Some companies (cable & Telco's) have multiple media/distribution
platforms and want to use them to get more share from advertisers
Facts
o Each consumer has different media habits
o Cross media optimization can improve performance
o Collection of data/insights is better in some channels than others and
communication value is better in some channels than others (and priced
differently)
o There is a large internet ad spend, but not much spend or expertise in
mobile and/or addressable TV
Reality
o Unlikely that three screen will become a big deal anytime soon.
o There is not enough expertise or spend in 2 of the 3 channels and there are few/no tools to
manage/optimize or insure value in 3 screen approach.
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60. significant time is spent on the various screens
Big growth in channels that consumers have more control
over, such as TiVo, Net and Mobile and where
addressability resides
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61. 3 screen ad approach
The value may be in the value exchanged. Internet for
data, TV for communications impact and mobile for
personal & proximity.
o Data richness of data collection o Richness of video
o Contextual advertising o Long form of TV Commercials
o Richness of targeting available o Production values of TV
o Multiple forms
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o Proximity to retail/location

62. who wants things to change & why
Television Industry Advertisers/Agencies
o TV‘s ―virtue‖ is to sell lots of o A/A are not oriented to small
inventory at bulk ($10s of buys either, or to know the
millions) value of targeted media
o $70B category that‘s been o They don‘t have the tools in
doing ―just fine‖ managing, or optimizing, or
o Controlled by networks that measuring to commit large
are not digitally oriented sums
o The ‗pipes‘ might want to o They aren‘t good at cross
solve given the unique value media now
this brings them o They will likely apply test
o Comcast and NBC deal budgets cause they like to be
viewed as ―first‖
Only Nielsen is focused on addressing 3 screen with their A2/M2
(Anywhere Anytime Media Measurement) Initiative
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63. what would need to happen to get TV to change?
Cable and TV would have to be willing to work together
• Lack of standards & consistency is a big issue
• Lack of geographic coverage is an issue
Ability to get cooperation or to go around them (force coop)
• Potentially advertisers can drive the change
• Exchange business commitment of $50 million by Chrysler
Super strong business case or desperation
• Probably still not enough to create change
• Upfront spending falls by significant amount, forcing change
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64. privacy principles
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65. privacy summary
Consumer control is everything in privacy
But that is not a proven science yet
o Focus needs to be on value, trust & control
Various approaches being developed.
o Unclear if self regulation is enough
Government might intervene - soon
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66. effective privacy policy must satisfy 4 elements
Value Consumer permits implicit or explicitly data use in
exchange for a personal benefit – more relevance
or convenience – and some clear value
Consumer trusts the Brand to use permitted data
Trust
only within agreed-upon limits.
Identity kept anonymous or confidential and
Anonymity
assurances and proof of such
Opt-out (partially or wholly) at will must be
Control
employed
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67. EXISTING SUBS NEW SUBS
OPT-IN
Written or mailed consent, sent to ATT Written or mailed consent sent to ATT
Sign-up on xxxx.com
website (un-checked box)
Permission on service order. Checkbox on
service form.
Ad-campaign about opt-in
All-in when subscribing to service.
greg@gregstuart.com
Permission granted on website.
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All-in when subscribing to service.
Recorded on phone.
Part of Service/Account Activation
process. (unchecked checkbox)
Download software/toolbar.
Agree to TOS. Download software/toolbar.
Pop-up box to opt-in and Agree to TOS.
TOS agreement change
Ad-campaign about opt-out Ad-campaign about opt-out
Email notice for opt-out Opt-out when subscribing.
(with checked box) (Deselect checkbox)
Mailer with TOS change
1. Notice within
Mailer Options:
Pop-up TOS change and
2. Sent to website
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opt-out button
3. Separate insert w/ bill
privacy is not an exact science – range of options
Agree to TOS – highlighted in
Email notice of change in TOS - application documents
explicit (with unchecked box)
NAI notification NAI notification
Explicit opt-out on xxxx.com Explicit opt-out on xxxx.com
In TOS, no explicit notification Buried in TOS agreement
that this can be done
No opt-out option No opt-out option
Low feasibility
High feasibility
Low feasibility
High feasibility
Moderate feasibility
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Moderate feasibility
= Height of bar assesses feasibility
EXISTING SUBS NEW SUBS
OPT-OUT

68. novel approach-Blue Kai registry
Blue Kai gives the consumer access to what
they know about them and the opportunity
to opt out or modify that profile
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69. privacy experts
Jules Polonetsky (WA DC)
o Future of Privacy Forum
Alan Chapell (NYC)
o Chapell & Associates
J. Trevor Hughes (VT)
o IAPP-International Association of Privacy
Professionals
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70. final thoughts
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71. case study context: Google revolutionized on-line advertising by
solving the two-sided value proposition equation
Online ad Online search,
landscape, 1999 2003+
• Complex user experience, often • Elegant user interface, limited clutter,
cluttered user interface integrated into browser toolbar
Consumers
• Intrusive ad formats (pop-up ads, • Increased focus on contextual ads,
banners) and direct marketing relevant to end-users
campaigns (spam e-mail)
• Limited search capabilities (site lists, • Better algorithm – gateway to the web
poor search engines)
• CPM-based advertising • Pay-per-click pricing
• Unclear ROI, limited campaign • Best-in-class measurement for
Advertisers results for advertisers advertisers
• Limited targeting • Highly focused based on customer
browsing / search behavior
• Clutter • Simplicity, site guidelines
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72. Thank You
More questions?
Greg Stuart
greg@gregstuart.com
+1 631 702 0682
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73. appendix
Author‘s (Greg Stuart) Bio
Terms & Definitions
Advertising Spend review
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74. greg stuart bio
Greg Stuart is a recognized leader in digital media & advertising and was selected by Ad Age as one of ―10 Who Made Their
Mark‖ in 2006.
He is the former CEO of the Interactive Advertising Bureau (IAB), the trade group for the interactive advertising & marketing
industry. He grew the IAB‘s revenues with a CAGR of 37% (overall +500%) while leading the industry from $6 billion to $17
billion in ad spending. The IAB customers included AOL, CNET, Google, Disney, NBD, Yahoo! & 400 others.
Greg has more than two decades of hands-on operating experience as a proven business builder in the Digital Media and
Technology arenas since 1993. He has extensive experience as CEO/Director/senior executive roles with Y&R, Sony Online
Ventures, Cars.com, Flycast Ad Network and venture-backed DeltaClick.
In the last two years he has served as Advisor, Director and angel investor to venture-backed companies with a resulting $750
million in exits, each at least at a 10x multiple. He‘s also worked with AT&T, Alcatel Lucent & Meredith in redefining their digital
media opportunities for the future.
Ad Age identified his book, ―What Sticks: Why Most Advertising Fails and How to Guarantee Yours Succeeds,‖ as the ―Number
one of 10 books you should have read‖.
Aside from his industry leading status in advertising and digital media, his operating expertise is in leading cross-functional teams
in product development, go-to-market strategy, company positioning, business development/deal making, marketing, and
scalable revenue generation with a record of success in both rapid growth businesses and turnarounds.
He currently serves on the Board of Zimbio, a next generation webzine with nearly 20 million uniques and backed by Menlo
Ventures and August Capital. He had served on the Board of Rapt (Accel backed), Inc. in SF, sold to Microsoft; and Board of
Allyes (Oak backed) in China, sold to Focus Media. Greg has also served on the Advisory Boards of a dozen venture-backed
companies in Search, Mobile, Video, Research, & Social Media backed by Intel, Greylock, Sierra, Conway, TimeWarner,
USVP, Union Square, Oak VC, DFJ, Canaan, Spark, Intel, First Round Capital and others.
He is a member of the National Speakers Association and speaks around the world on the failings, and thus opportunities, of
advertising - Istanbul, Israel, Germany, Mexico City, Jakarta, Sao Paulo, Switzerland, Zurich, Shanghai, Sydney, Barcelona,
Monaco, Tokyo and others.
Greg has a BA in Economics from the University of Washington and completed Wharton‘s intensive Advanced Management
Program in 2008. He lives happily outside of New York City in Bridgehampton, NY with his wife Pamela, twin daughters and
son.
http://www.linkedin.com/in/gregstuart
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75. Glossary
Term Description
CPM "cost per thousand" ad impressions. the price that is charged to advertisers by ―publishers‖ for 1000 ad
impressions
RPM ―Revenue per thousand" ad impressions. the revenue that is generated for 1000 ad impressions
Impression Web: a measure of how many times an advertisement is displayed.
Mobile: each individual ad unit viewed on a mobile publisher's deck (web site).
TV: how many times ad is played
Inventory the total number of impressions that a Web site has available for sale over a given period of time (usually,
inventory is figured by the month).
Upfront Annual sale of network ad inventory, typically at a slight discount to scatter prices, and guaranteeing
placement in specific show time and position in pod
Scatter Day-to-day market for network ad inventory. Majority of sales occur between 3 and 9 months prior to
airtime, and on similar terms to upfront
Remnant Day-to-day market for ad inventory not sold in upfront or scatter markets. Typically discounted 30-70% on
scatter market rates on a preemptible basis and without specific airing time
Ad Currency Nielsen Rating Points
Unique Visitor Someone with a unique address who is entering a Web site for the first time that day (or some other
specified period).
Cost-Per- what an advertiser pays for each visitor that takes some specifically defined action in response to an ad
Action (CPA)
Cost-Per-Click the cost or cost-equivalent paid to a publisher per click-through. The amount paid by the advertiser each
(CPC)
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76. cost per X detailed definitions
CPM (cost per thousand impressions) has been popular since the start of online advertising. CPM remains one of the most popular cost metrics
used, though these days it‘s rarely the only metric employed for a campaign. It allows simple comparisons between campaigns and future
opportunities (many publishers use this on their public rate cards).9 For example, even if marketers pay for a campaign on a cost-per-click basis, they
can get reporting on total impressions and simply divide their total spend by impressions and multiply by 1,000, thereby generating a similar metric
across differing campaigns. Nonmarketers such as CEOs or CTOs can often more easily relate to this type of measure than to online-specific metrics,
such as time spent interacting with an ad, that are less directly related to costs.
CPC is a very popular metric for marketers trying to drive direct action from an advert. More than 65% of database marketers in a recent Forrester
survey say they use response rates as a key metric.10 However, it can also lead to advertisers paying for many clicks that are not from the target
audience, such as clicks by mistake or invalid clicks from Web crawlers, and even expose them to click fraud. As a marketer, using your own ad
serving tool for measuring clicks (and visitors) can help establish a standard measure, rather than trying to compare metrics from a variety of tools for
each campaign.
CPV (cost per visitor) gives insight to Web site owners. CPV is where advertisers pay publishers based on how many viewers of display ads then
actually visit the advertiser‘s Web site. These metrics are most useful for advertisers aiming at driving further interaction from consumers, rather than
general brand awareness or attitude, and of course take no account of what the visitors do when they get to the Web site; they could, for example,
leave immediately once they arrive on the landing page. Some marketers now impose stricter rules on what counts as a ―visit‖ (which is sometimes
still called a ―click‖), such as ―visitors spend at least 3 seconds on the landing page,‖ to get over some of these problems.
CPA (cost per acquisition/conversion) gives a metric comparable across channels. CPA metrics allow marketers to measure success based on
customers acquired through a campaign. Of course, ―acquired‖ may have different meanings for different marketers: For a retailer it may simply mean
a site visitor or someone who puts goods in the shop‘s online basket or perhaps only those who actually buy. For brand marketers, it may be
measuring those who click through to a certain area on a Web site, those who sign up for an email newsletter, or those who take some other type of
direct response activity via the ad landing page like asking for more information on debt management, for example. Google has heavily promoted this
as a metric, with CPA management tools included in its AdWords product and within the affiliate network (previously known as DoubleClick Performics
Affiliate). Introducing some type of ―quality‖ measurement within the definition of acquisition — so, for example, only counting those email subscribers
who remain subscribers for three months — helps marketers assess success on a more valuable scale than simply volume.
CPE (cost per engagement) is emerging as a metric. CPE is a newer ad model whereby advertising is offered free, with advertisers paying only when
viewers actually engage with the ad itself (thus differing from CPA, which looks at consumer activity post exposure). ―Engagement‖ can be defined in a
number of ways, such as completing a survey within the ad, entering a competition, or watching a certain amount of video. Online video ad provider
VideoEgg pioneered this payment system in 2008.11 This method is seen to push back more responsibility for ad performance onto the ad creative
than other methods such as CPC, which were thought to place the bulk of the burden of performance onto the publisher. It is also a way of measuring
interaction with newer types of creative — such as video ads or ads with product comparison tools within them — that may drive significant interaction
but not actually click-throughs. However, as ―engagement‖ means something different for every marketer, such metrics are not comparable across
campaigns even for the same marketer, limiting their value.
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77. verbiage on digital ad metrics
View-based metrics simply look to track exposure. These measures, such as number of
impressions or unique viewers, generally appeal more to advertisers with a branding goal, as
they mirror the basic offline measures for brand exposure of readership in print or viewers
on TV. Even the smallest of advertisers can track this with free analytics packages such as
Google Analytics. However, these metrics reveal very little about the impact of advertising
on consumers, and with almost two-thirds of marketers using these as a metric, it‘s hardly
surprising that half of interactive marketers say extracting ROI is their biggest challenge with
display advertising, and 60% of marketers say that they struggle to build the case for interactive
marketing in their organizations.
Performance-based metrics aim to expose true interactions. Metrics such as number of
click-throughs or video views give an indication of how many consumers actually took some
action upon seeing an ad and appeal to advertisers looking to drive direct action, though are
unlikely to be very insightful for marketers with a branding goal or to indicate real ROI. One of
the reasons for the prevalence of both of these types of basic metrics, despite their lack of real
insight, is the relative ease of benchmarking across your own campaigns and with the industry
as a whole; DoubleClick, for example, supplies some ad click-through rates.
Cost-Based Metrics Generate More Insight
Evaluating display ad campaigns on a cost basis allows marketers to track the efficiency of the
channel and begin some simple comparisons, such as comparing banner ads and search on their
―cost per click‖ (CPC) or even television and banners on ―cost per unique viewer.‖
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78. ad spending review
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79. ad spending by channel summary
Media Channels
~$300 billion dollar industry (U.S.) Television:
60/40 national / local o Broadcast TV
o Cable TV
50/50 brand / direct marketing o Spot TV
o Interactive TV
Online is ~$25 billion, mobile is <$1B Internet:
Online display/brand is only 1/4 o Search
o Display
Growth opportunities online: o Digital Video
o Games
1. Online video is up & growing (+115% in ‗09) Magazines
2. Behavior/Audience targeting still growing Business Press
3. Performance & ROI rules Newspaper
Radio
4. Local online will grow, eventually Out of Home
Digital OOH
Direct Mail
Net, Digital is growth medium Yellow Pages
Mobile
Others declining; & will continue to fall
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