1.0 Business Drivers for AdForce Service Products
1.1 Corporate
Objectives
AdForce’s corporate objectives
support a clear mission:
To
be the leading service for managing Internet advertising and direct marketing.
The objectives are as follows:
1.
To
maximize market share
2.
To
create multiple recurring streams of revenue
3.
To
achieve excellence in service and reliability
4. To
create the potential for profit
1.2 Business Objectives
AdForce’s business objectives are
designed to achieve the overall corporate objectives, and success in the
identified market segments:
1.
Offer the best ad solution for publishers
2.
Offer the best ad solution for advertisers
3.
Provide marketing and commerce ROI tracking
4.
Build valuable centralized user profile database
5.
Provide the Internet marketing exchange
6.
Be the number #1 brand in the industry
1.3 Customer Priorities
Advertisers have the following priorities:
1.
Reliable ad serving and measurement (counting)
2.
Reports that are accurate, timely and complete
3.
An interface that is intuitive, reliable, fast, and mirrors
their process
4.
Media planning tools with integrated syndicated data
5.
Tools for measuring and analyzing ROI, and effectiveness
6.
Integration with advertiser process - media research,
planning, buying accounting across all media.
7.
Centralized, efficient mechanism for buying and executing
complex campaigns - media brokerage, order stewardship, etc.
8.
Targeting using demographic, lifestyle and behavior
information
9.
Support for rich media formats
Publishers have the following priorities: (they vary by the size of
publisher)
1.
Reliable, 100% ad serving without failures
2.
Accurate counting and reporting
3.
Fast ad serving response time
4.
Powerful and flexible inventory management
5.
Near-site or on-site ad serving (large sites)
6.
A Client that is fast, easy to use and stable
7.
Data center redundancy
8.
Verified user database and targeting capabilities using that
database
9.
Media sales management and order reservations
2.0 Product
Strategy EL/FK/HSR 10-15
Overview Paragraphs…
2.1 AdForce
Hexagon of Service offerings
Performance Metrics – Today, targets for ’99 & ‘00
|
|
Today
|
Q4 ‘99
|
Q4 ‘00
|
|
Ads Delivered
|
160 MM
|
1,000 MM
|
5,000 MM
|
|
Users of
System
|
200
|
2,000
|
5,000
|
|
Active
Campaigns
|
5,000
|
50,000
|
200,000
|
|
New
Campaigns
|
300
|
1,500
|
10,000
|
|
Reports
|
|
|
|
|
Beacons
|
|
|
|
|
|
|
|
|
Using existing numbers the following were estimated…
|
Projections FY99, FY00
|
|
|
|
|
|
|
|
|
|
Q1 '99
|
Q2 '99
|
Q3 '99
|
Q4 '99
|
Q1 '00
|
Q2 '00
|
Q3 '00
|
Q4 '00
|
|
Total Impressions (in Millions)
|
183
|
290
|
492
|
690
|
1,714
|
3,573
|
7,791
|
17,435
|
|
Paid Impressions (in Millions)
|
173
|
272
|
462
|
649
|
1,556
|
3,172
|
6,759
|
14,782
|
|
Beacons
(in Millions)
|
1
|
2
|
4
|
6
|
16
|
38
|
92
|
228
|
|
Campaigns
(in Thousands)
|
5
|
7
|
10
|
12
|
18
|
26
|
39
|
59
|
|
New Insertions (in Hundreds)
|
3
|
4
|
5
|
6
|
10
|
14
|
20
|
30
|
|
Reports
(in Hundreds)
|
7
|
9
|
12
|
14
|
18
|
23
|
29
|
38
|
1.
Subsystems, Frameworks and Added Services
|
Subsystem
|
Framework
|
Current and Added Services
|
|
Media Planning
|
Campaign
Performance
|
1.
ROI Assessment (requires beacon serving)
2.
Demographic profile campaign performance
3.
Behavioral profile campaign performance
4.
Adjust campaigns in real time, offer suggestions, update
schedule (?)
5.
Campaign Decision Support Workstation
|
|
Media
Research Interface to our Campaign Performance subsystem
|
1.
Media Planning using Media Research data
|
|
Banner
Co-op Media Planning
|
1.
Add Co-op inventory to the media planning inventory
|
|
Media
Management
|
Current
Media Management Framework
|
1. Java Client: Campaign Forecasting, Scheduling, Editing
|
|
|
1.
Improved website and campaign management
·
Hierarchy of website items (Website, pages, CU’s and other
groupings)
·
Hierarchy of agency items (campaigns, flights, media)
2.
Beacon Scheduling
3.
RAS Scheduling
4.
Media Co-op Scheduling
5.
List based target scheduling
|
|
New
IMS Framework
|
1.
Keyword based campaigns
2.
Campaign Management w/ overlapping inventory
|
|
Three
Tier Client Interface
|
1.
API for Media Management
2.
HTML Client interface
3.
Integration w/ outside systems (including Media Planning
subsystem)
|
|
Media
Delivery
|
Current
Architecture
|
1.
Paid Banners
& Sponsorship ‘buttons’
2.
‘Unpaid’
House Ads
3.
Limited
Secure Ad Serving capacity
4. Limited Rich Media Serving
5.
Beacon Serving
6.
Multiple Ads Per Page (MAPP)
7.
Ads based on viewer’s connection speed
|
|
Rich
Media
|
1. Deliver Rich
Media Ads Faster, more reliably
|
|
List
based targeting
|
1. Serve Ads
based on demographic or behavioral criteria.
|
|
Multiple
Data Centers
|
1.
Added Capacity, faster delivery.
2.
Added Secure Media Serving capacity.
3.
Added Rich Media Capacity (?).
|
|
Media
Co-op Delivery
|
1.
Banner Co-op ad serving, scheduling and management.
|
|
Distributed
Delivery (RAS & RIS)
|
1.
Delivery of Text ads as HTML Text
2.
Delivery of targeted HTML content for ‘advertorials’.
3.
Improved Ad delivery
·
Browser based tag selection
·
Faster delivery of text ads.
·
Faster delivery of Ads
·
Better delivery of Rich Media ads
|
|
API
for Ad Selection plugins
|
1.
Interface to targeting engines (i.e. NetPerceptions,
Engage)
|
|
Reporting
|
Actuate
Reporting Engine
|
1.
Multiple levels of Reporting – Base, Premium, Pay per
Report
2.
Custom Reports – faster to develop, more reliable
3.
Real Time Reports (using data up to the last hr.)
|
|
Beacons
|
1.
ROI Reporting
2.
Click Stream Analysis
|
|
Media Co-op
|
1.
Media Co-op Reporting
|
|
List
based targeting
|
1.
Report on ads served using demographic or behavioral
criteria
|
|
RAS
|
1.
Report on RAS delivered ads – integrated w/ standard
reporting.
|
|
Data
Management & Analysis
|
User
Profiles
|
1.
Match User ID’s w/ Experian Demo data
2.
Match User ID’s w/ beacon Data
|
|
Tracking
|
1.
Track viewers behavior w/in media’s space as well as
outside website (via beacons)
|
|
Targeting
|
1.
Manage lists of targetable user id’s/profiles
|
|
ROI
Calculations
|
1.
Using campaign spent $’s, tracking info, user profiles –
provide campaign ROI data
|
|
Query
Interface
Statistical
Analysis
Collaborative
Filters
Neural
Engine
Rule
Based Engine
|
1.
Beacon Data Management
2.
Profiling
3.
Tracking
4.
Statistical Analysis
5.
Query Interface
|
|
Data Streams
|
Data
Publish
|
1.
Data Export (CD ROM, FTP, e-mail)
2.
Publish & Subscribe
3.
Ad Delivery Data ‘ticker’
|
Deployment Timeline (Frameworks)
|
|
Media Planning
|
Media Management
|
Media Delivery
|
Reporting
|
Data Mangement& Analysis
|
Data Streams
|
System Mgmt
|
|
R0
Q1’99
|
|
New Client
UI
|
200 MM ads
Multiple
Data Centers
Rich Media
|
Actuate
|
User ID
Matching
|
|
|
|
R1
Q2’99
|
Banner
Co-op
|
Beacons
RAS &
RIS (Beta)
Banner
Co-op (Beta)
New Agency
Client UI
IMS (Keywds)
Site
Branding
|
Beacons
RAS &
RIS (Beta)
Banner
Co-op
?? MM ads
|
Beacons
RAS &
RIS (Beta)
Banner
Co-op
|
Beacons
|
|
|
|
R2
Q3’99
|
Campaign
Performance
|
List based
targeting
New Media
Mgmt
New IMS
Three Tier
Client I/F
|
List based
targeting
?? MM ads
|
List based
targeting
|
List based
targeting
|
|
|
|
R3
Q4’99
|
Media
Research I/F
|
|
?? MM ads
|
|
|
|
|
|
R4
Q2’00
|
|
Media
Trading (?)
|
?? MM ads
|
|
Query Interface
Statistical Analysis
|
Data Publish
|
|
|
R5
Q4’00
|
|
|
?? MM ads
|
|
Collaborative Filters
Neural Engine
Rule Based Engine
|
|
|
|
|
|
|
|
|
|
|
|
2.2 Value
Chain Assessment
In ’98 about $2 Billion was spent on Online Advertising.
The cost of serving those ads was $31 MM. AdForce served 14% of the ads, we collected $4.2 MM in ’98.
The following are estimates based on Media Metrix numbers for Oct.’98.
|
Total Page Views in Oct '98 (000) – Top 20
sites
|
6 Billion
|
|
|
Total Ad Views in Oct '98 (000) – Top 20
sites
|
18 Billion
|
|
|
Total Ad Views in '98 (000) – All sites
|
69
Billion
|
|
|
Total Spent Online Adv
|
|
$2 Billion
|
|
|
Average CPM
|
|
$ 29
|
|
|
Average cost of ad serving
|
|
$ 0.45
|
|
|
Total Spent on Ad Serving
|
|
$ 31 MM
|
100%
|
|
Total Spent on Ad Serving at ADFC
|
|
$ 4.2 MM
|
14%
|
AdForce currently is only doing Ad Serving, areas for growth are:
·
More Ad serving – sites are growing and we can capture
more of the share of the market.
·
More expensive/valuable ad serving – targetable ads
·
Added services – more sophisticated reporting. ROI
reporting. Data Analysis
·
Ad Co-op revenues
AdForce can add value to most of the items that are key to Websites,
Rep Firms, Advertisers and Agencies:
AdServing
·
Forecasting, scheduling, managing and reporting on
space and inventory.
·
Delivering ads fast and reliably
·
Counting the highest number of possible ads -> more
revenues to website customers
·
Effectively handling click-throughs and becons
Reporting
·
Reports for websites, rep firms, advertisers and
Agencies – each report is different.
·
Custom reports
·
ROI reports
Targetable Ads
·
Added value ads based on behavior, demographic or other
profile criteria
Ad Co-op
·
Serving ads for a co-op organization where ad space is
bartered. AdForce would do the ad serving and management of the co-op barter
system. Paid ads are also managed by AdForce.
Estimated
AdForce Revenues by Product Category
|
|
Year
Ended December 31,
|
|
|
|
Net Revenues:
|
1997A
|
1998A
|
1999F
|
2000F
|
2001F
|
|
Adserving
|
$ 320
|
$ 4,286
|
$ 13,738
|
$ 32,482
|
$ 54,758
|
|
Targeting
|
|
|
873
|
2,063
|
3,478
|
|
Reporting
|
|
|
160
|
378
|
638
|
|
Prof Svcs
|
|
|
106
|
251
|
422
|
|
Ad Co-op
|
|
|
|
|
|
|
Total Net Revenues
|
$ 320
|
$ 4,286
|
$ 14,877
|
$ 35,174
|
$ 59,296
|
Website – Organization, where AdForce fits, what issues do
we address
For Websites, the Online Ad $$’s flow from:
·
Advertiser buying
space on pages, known as sponsorships ~ 50% of current large site
revenues. A large portion of this is e-commerce related, and dependent on being
able to track transactions at the advertiser/merchant site.
·
Advertiser buying banner, keyword or other ‘standard’
inventory, known as advertisements – 40% of current large site revenues
·
Agencies buying banner, keyword or other ‘standard’
inventory - < 10% of current large site revenues.
·
There are also ‘house ads’ or non-paid and barter ads
which are run by Websites on ‘unsold’ inventory. The Websites tend to use
site-side or homegrown servers for these ads since they don’t need to have as
accurate reporting or scheduling as needed for paid ads. The % of inventory
that is ‘house ads’ could be as much as the sold ads, depending on the season
and the Website.
For large websites, the organization looks like the following:
Sales:
·
Strategic business development team – focusing on large
sponsorship partnerships (i.e. Amazon sponsoring the books section of Netscape,
ATT sponsoring the “Communications’ channel at Infoseek, etc.) – these deals
tend to be from $500 K to $ 5 MM.
·
Direct sales team, focusing on smaller sponsorships and
large advertising deals - $10 K to $500 K
·
Indirect sales team, focusing on <$10 K advertising
deals, usually a rep firm.
Marketing:
·
The overall organization has similarities w/ the media
business. There are ‘Producers’ and ‘Directors’. The ‘Producers’ are Program Managers, the ‘Directors’ are Art
Directors.
·
‘Program Managers’ which tend to be business managers
and handle a channel or two of the website (i.e. finance, news, health). They
handle the ‘brand’ of the channel. There is a look and feel that is defined by
the ‘Art Director’
·
The Program Managers tend to be in a negotiation w/ the
sales team re: what and how much space to use for advertising/sponsorships. The
sales team or business development team will sometimes do a deal and then the
program manager has to manage w/in the contract constraints.
·
The Program manager is essentially a constraint and
controls how the $$’s are spent on his program. They are also interested in
fast delivery of advertising since their program is directly affected
Operations:
·
They are the final gatekeepers of what and how ads will
be served on the site. They tend to prefer site-side serving over outsourced ad
serving since it gives them more control as well as more to do.
·
AdForce needs to ensure we make these people reasonably
happy, they could prevent some of our programs from executing, like RAS or
TrackForce beacons.
For Websites, the issues are, effectively:
·
Managing & reporting the sponsorship space sold.
·
Forecasting, scheduling, managing & reporting on
campaigns of advertisement.
·
Counting revenues from the above revenue sources.
·
Scheduling house ads and barter inventory.
·
Ensuring speed of ad delivery and no disruption of
their own pages being served.
For Rep Firms, the issues are similar to Websites, with the added
requirements:
·
Managing, scheduling and reporting on several websites
that are not in their direct control
·
Managing the revenue split among several websites whose
inventory is being sold by the Rep Firm.
For Advertisers, the $$’s flow from and to:
·
Florian to fill in…
For Advertisers, the issues are:
·
Florian to fill in…
For Agencies, the $$’s flow from and to:
·
Florian to fill in…
For Agencies, the issues are:
·
Florian to fill in…
2.3 Market Window
Websites
·
About 71% of the ads
served by the top 20 sites are going through a homegrown system or a site-side
server solution. Both are not meeting the needs of the websites.
·
AdForce has the
opportunity to capture 15% of
the ads served by homegrown / site side systems in the next 12 months and
another 20% the year after.
·
For this year we could
make this number if we served ½ of the ads for Microsoft, AOL, Snap, Time
Warner and Lycos. We have had early conversations w/ all of them.
·
In Oct. ’98 the top 20
sites served 6 Billion pageviews, if you assume an average of 3 ads per page,
the ad impressions for Oct. ’98 were 18 Billion. The breakdown of ads served by
each ad server follows:
Homegrown 49
% - 8.9 B
Accipiter 15% - 2.8 B
AdForce 13% - 2.4 B
DoubleClick 11%
- 1.9 B
NetGravity 7%
- 1.2 B
·
Currently most of the top 20 Websites are looking for
new solutions. 71% of the ads are either served using home grown (49%) systems,
or Accipiter / NetGravity (22%) site-side systems which, we understand (based
on Netscape, Infoseek and CNN) are not meeting their needs.
·
DejaNews, LookSmart and others have used AdForce and
DART and are currently un-committed due to lack of a solution that meets their
needs.
·
We are using the Media Metrix Oct. ’98 numbers (the
absolute numbers may be off, but the relative ranking of companies and the % of
total page views allocated to each website should be reasonably accurate).
Top 20 Websites, October 1998. Source:
Media Metrix
|
|
Web Sites
|
Total
Pages (000)
|
Estimate of Ad Impressions
|
Adserving
Technology
|
|
1
|
Yahoo Sites
|
1,273,942
|
3,821,826
|
Homegrown
|
|
2
|
Microsoft Sites
|
871,455
|
2,614,366
|
Homegrown
Accipiter
|
|
3
|
NETSCAPE.COM
|
505,175
|
1,515,525
|
AdForce
NetGravity
|
|
4
|
AOL Websites
|
455,301
|
1,365,902
|
Homegrown
Looking at Adforce
|
|
5
|
eBay
|
447,844
|
1,343,532
|
DoubleClick
|
|
6
|
Excite Network, The
|
400,376
|
1,201,128
|
Homegrown
MatchLogic
|
|
7
|
Lycos
|
353,416
|
1,060,247
|
Accipiter
NetGravity (Wired)
|
|
8
|
GEOCITIES.COM
|
298,282
|
894,846
|
AdForce
|
|
9
|
The Disney Company sites
|
269,910
|
809,729
|
Starwave (Homegrown)
|
|
10
|
Time Warner Online
|
140,820
|
422,460
|
NetGravity
|
|
11
|
Infoseek
|
139,544
|
418,633
|
Starwave (Homegrown)
|
|
12
|
ZDNet Sites
|
136,773
|
410,320
|
Accipiter
|
|
13
|
ALTAVISTA SEARCH SERVICES
|
131,836
|
395,507
|
DoubleClick
|
|
14
|
AMAZON.COM
|
108,589
|
325,767
|
Outbound campaigns
|
|
15
|
CNET
|
98,894
|
296,681
|
Accipiter
|
|
16
|
Switchboard Network
|
98,673
|
296,019
|
NetGravity
|
|
17
|
BLUEMOUNTAINARTS.COM
|
96,465
|
289,395
|
No ads
|
|
18
|
SNAP.COM SEARCH & SERVICES
|
76,005
|
228,014
|
Accipiter
|
|
19
|
USATODAY.COM
|
56,246
|
168,739
|
Real Media
|
|
20
|
TRAVELOCITY.COM
|
54,568
|
163,704
|
DoubleClick
|
Window of Opportunity for Websites
– When Products need to be done in
order to meet target market share numbers
|
|
1H ‘99
|
2H ‘99
|
1H ‘00
|
2H ‘00
|
|
Media Planning
|
|
·
Media Planning 1.0
|
·
Media Exchange 1.0
|
|
|
Campaign
Management
|
·
Keyword IMS & Mgmt
·
Site Branding 1.0 (for directory & community
sites)
|
·
IMS Overlapping
·
Hierarchical Website Representation & Campaign
Scheduling
|
·
Back Office Integration
|
|
|
Media
Delivery
|
·
RAS & RIS
·
Faster more accurate delivery
|
·
Banner Co-op
·
Rich Media
|
·
|
·
|
|
Reporting
|
·
Premium / Custom Reports
|
·
Near Real Time Reporting
|
|
·
|
|
Data Streams
|
·
Data Export
|
·
RegForce 1.0
|
·
Publish / Subscribe
|
|
|
Data
Analysis
|
|
·
TrackForce for E-Commerce sites
|
·
TargetForce Behavioral
|
·
TargetForce Demographic
|
Rep Firms
·
They need to have centralized ad serving, and DCLK is a
key competitor. Few other options other than AdForce
Advertisers
·
Florian…
Agencies
·
Florian…
2.4 Product
Architecture
Overview Paragraphs…
2.4.1
Media Planning Subsystem
Overview Paragraphs…
Goal:
·
Characterizing website pages and ad/media space using
content, behavioral, demographic and other profiles.
·
Interfacing w/ IMS engine to get Forecasts of inventory
over on media space over a variety of websites.
·
Defining a media plan or a campaign which consists of:
Media Inventory distributed over a time period on space that is available from
the websites.
·
Include API for interfacing to:
·
Media Space manager (both query and define media space)
·
Forecasting engine (IMS, both to query and provide
data)
·
Extracting data on space definitions.
2.4.1.1
Campaign Performance FW
2.4.1.2
Media Research I/F
2.4.1.3
Banner Co-op Media Planning FW
2.4.2
Media Management Subsystem
Goal:
·
Reserving space on websites over a period of time.
·
Scheduling ad/media over the website space during a
time period (campaign)
·
Schedule beacons (?)
·
Editing the campaign within the bounds defined in the
scheduling process
·
Include API for interfacing to:
·
Reserving space
·
Scheduling ad/media, including beacons
·
Editing campaigns
·
Extracting data on scheduled campaigns
2.4.2.1
Current Media Management FW
2.4.2.2
New Media Mgmt FW
2.4.2.3
IMS FW
Overview Paragraphs…
Goal:
·
Forecasting availability of inventory over on media
space over a variety of websites.
·
Forecasting based on:
·
Space & Time – content definition vs. query
·
(i.e. what 468 x 60, JavaScript enabled inventory do I
have on Yahoo Finance, from 3/15/99 to 4/15/99 ?)
·
Behavior & Time – lists of users vs. query of space
& time
·
(i.e. how much inventory do I have on Yahoo Finance
from 3/15/99 to 4/15/99, for the people who visited beacon 4367 from 9/1/98 to
12/31/98 ?)
·
Demographics & Time – demographic profiles vs.
query of space & time
·
(i.e. how much inventory do I have on Yahoo Finance
from 3/15/99 to 4/15/99, for people who are 35 to 44 yrs. old ?)
·
Include API for interfacing to:
·
IMS engine – queries of space, behavior or demographic
nature over time.
2.4.3
Media Delivery Subsystem
Overview Paragraphs…
Goal:
·
Respond to ad/media requests fast (under 500 ms ?),
accountably (> 90%) and w/out caching
·
Choose and ad/media to ‘deliver’ by ‘deciding’ on what
banner to serve to which viewer on what space at what time.
·
Handle click-throughs – respond fast (under 500 ms ?)
and accountably (>95%), prevent caching of response
·
Handle beacons (? Here ?)
·
Allow for distributed handling of ad/media requests
·
Include API for interface to:
·
Insertion of ad/media schedules
·
Input and output to Targeting engines
·
Output to Data Streams
2.4.3.1
Current Ad Delivery FW
2.4.3.2
Distributed Media Delivery FW
2.4.3.3
List based targeting FW
2.4.3.4
Media Co-op Delivery FW
2.4.3.5
Media Selection Plugin FW
2.4.3.6
Image delivery FW
Overview Paragraphs…
Goal:
·
Deliver ad/media ‘payload’ fast (>80 % of baud rate)
and efficiently, use internet caching
where possible.
·
Deliver a variety of media seamlessly (rich media,
advertorials, etc.)
·
Allow for distributed ad/media payload delivery
·
Include API for interface to:
·
Distribution of ad/media payloads
·
Interface to other ad/media delivery services (i.e.
Rich Media, Audio, Video, etc.)
2.4.4
Reporting Subsystem
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Goal:
·
Report on existing and past campaigns – media scheduled
on website space during a period of time.
·
Report on click-throughs and beacons.
·
Report on ROI & Targeting (?)
·
Report data in a variety of ways – summaries, detailed,
w/ more or less fields, etc.)
·
Reports are delivered in HTML, print and excel formats.
·
Include API for interfacing to:
·
Requesting, scheduling, stopping reports, to be delivered
through standard mediums (i.e. HTML, printed or excel)
·
Getting a report’s data through the API
·
Defining a report (?)
2.4.4.1
Actuate FW
2.4.4.2
Beacon Reporting FW
2.4.4.3
Media Co-op Reporting FW
2.4.4.4
List based Targeting Reporting FW
2.4.4.5
RAS Reporting FW
2.4.5
Data Management and
Analysis
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Goal:
·
Provide Access to the data generated by the ad delivery
sub-system.
·
Provide query interface to gather summary and detail
information
·
Provide filtering mechanisms for data: statistical
filters as well as other filters (?)
·
Include API for interfacing to:
·
Query interface
·
Filtering mechanisms
·
Extracting of Data
2.4.5.1
User Profiles FW
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Goal:
·
Develop profiles of ad/media viewer’s behavior and
demographics.
·
Interface w/ other profiling systems, such as Experian,
to add profiles to an existing user’s record(s).
·
Include API for interfacing to:
·
User’s profile records – to add, edit, delete fields
2.4.5.2
Tracking FW
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Goal:
·
Track ad/media viewer’s behavior w/in the ad/media
space (website) as well as outside the website (usually into
merchant’s/advertiser’s sites)
·
Track visits, click-throughs and additional data
provided by website/merchant/advertiser.
·
Include API for interfacing to:
·
View and extract viewer’s records of visits
2.4.5.3
Targeting FW
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Goal:
·
Define campaigns using behavioral or demographic
profile criteria (i.e. deliver banner A to 18 to 24 yr. Males, or deliver
banner B to viewers that visited a page w/ beacon)
·
Deliver ad/media using behavioral or demographic
profiles as criteria.
·
Include API for interfacing to:
·
Targeting engine definitions, decision tree, counts (?)
·
Editing decision tree
2.4.5.4
ROI calculation FW
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Goal:
·
Combine the expenditure on campaigns to the tracking of
viewers visits using the Tracking subsystem, provide Return on Investment
calculations
·
Include API for interfacing to:
·
2.4.5.5
Resource allocation
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Goal:
·
???
2.4.6
Data streams
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Goal:
·
Provide data from subsystems using queries. Usually
little analysis or filtering.
·
Include API for interfacing to:
·
Extracting data from subsystems using ‘simple’ queries.
2.4.7
Media Products
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Goal:
·
Handle existing media types: text, GIF, Animated GIF,
HTML, JavaScript, Java, Audio, Video and other Rich Media types.
·
???
2.4.8
Media Exchange FW
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Goal:
·
Working on it…
2.5 Competitive Assessment
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AdForce areas of strength:
·
Meeting the reporting needs of large sites and
networks: AdForce offers superior reporting capability at the network level
·
Client services: AdForce has many good references that
will rave about the quality of support. Use them. Explain to your prospect that
in the fast-paced world of Internet systems, any feature advantage of any
competitor could be erased tomorrow. What they should base their evaluation on
is reliability and service.
AdForce areas of weakness:
·
Java application: AdForce customers don’t like the Java
application and would prefer to use an HTML interface. Luckily, the Java
application makes for a great demo. If the downside comes up from a reference,
make sure to position it as a trivial issue
·
Deal killers: AdForce has lost customers for not being
able to rotate multiple ads per page and for not being able to set up inventory
for a hierarchical site. Make sure you screen your prospects for these issues.
When competing with any site-side product:
·
Economics: Most (but not all) sites are convinced that
outsourcing is the way to go for ad serving. If your prospect is considering
bringing Accipiter or NetGravity in-house, make sure they consider the ongoing
software license fees, hardware upgrade costs, and staffing implications of
their decision. If they run the numbers, they’ll find that AdForce’s CPM
pricing is a better deal.
·
Agency familiarity: Agencies are experienced with the
3rd party products (AdForce and DART) and know exactly how to schedule and
report on their campaigns. Explain to the site that their advertisers will
prefer it.
·
Audit: As a 3rd party, AdForce functions like an audit
against the site’s numbers. The advertisers will appreciate working with an
unbiased 3rd party.
With Accipiter
·
As of February 1999,
Accipiter does not have geographic targeting. This is under development and
certainly not a proven feature
·
Accipiter can’t track
click-thrus on rich media ads
With DART
·
DoubleClick’s ad sales function creates a conflict of
interest in the minds of many networks and large sites who consider them to be
a competitor. Because DART’s functionality is similar to AdForce’s, you can use
this issue as a tiebreaker.
·
DART gets mixed reviews for client services, so make
sure your prospect hears the bad reviews. RotoMedia is a particularly unhappy
former DART customer.
·
Beware of where DART can beat AdForce:
·
Real-time reports – same day data is available. In
addition, customers can start/stop campaigns with 15 minutes lead time with no
human expediting
·
Pricing – DoubleClick is real aggressive. Find out what
price you have to beat
With NetGravity AdCenter (service bureau)
·
NetGravity will beat you on price. Try to find out what
price you have to beat
·
NetGravity generally has the reputation for the worst
ease-of-use, although not all customers agree with that.
·
NetGravity AdCenter is very new and has low volume
customers. Heap lots of fear, uncertainty, and doubts on AdCenter’s ability to
service clients with volume over 5 million ad impressions/month.
Bottom Line: There are problems with every ad server and you can
find both deliriously happy and violently unhappy customers for each vendor. Explain
to your prospect that AdForce is committed to establishing a long-term
partnership to grow together to meet their needs.
2.6 Packaging
considerations
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AdForce provides a service, as
such we provide to our clients:
·
Client UI for interfacing to our sub-systems/services –
currently this is both Java and HTML (some reporting, and AdForce One)
AdForce will be providing
distributed ad request processing and distributed ad/media delivery as such we
will need:
·
OEM or ‘packaged’ versions of ad request management
subsystem and ad/media delivery subsystem.
2.7 Make versus
buy issues
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The first order of business
before being able to integrate w/ ‘buy’ or ‘partner’ services is creating API’s
for our subsystems. The business deal can be done prior to the API, but the
actual integration will not be effective until the API’s are developed.
Current possibilities for ‘partnering’:
·
Ad Request management and Ad Delivery on proxies
