The document discusses 7 deadly sins of programmatic advertising:
1. Viewability is a problematic metric with varying standards across platforms like YouTube, Facebook, and Snapchat.
2. Ad fraud primarily impacts proxy metrics like impressions, but optimizing for goals beyond impressions mitigates the impact.
3. Time-based campaigns disrupt optimization by creating gaps in analysis and allowing false blame when campaigns end. An always-on baseline approach is better.
4. Not disclosing attribution models used in reports can be misleading and deceptive about where conversions are coming from.
5. Using selective timeframes, graphs without data, or blocking access to raw data are red flags that indicate a lack of transparency.
6.
4. Viewability
• Viewability is a unstandardised and
problematic metric
• Google defines viewability as 50% of
the pixels of an ad loading within your
browser for a continuous 1 second
• Video standards are dependent on the
publishers
• Youtube = 30secs
• FB = 3secs
• Snapchat = 1sec
7. If an ad loads in a browser and no one is
there to notice it, does it really matter?
8. Fear of Ad Fraud + scary sites
• Ad fraud primarily effect proxy
metrics such as impressions
• Optimising to goals beyond
impressions mitigates the impact
of ad fraud
• Default features also reduce the
risk of ad fraud
• Whitelisting
• Blacklisting
• 3rd Party Tools
9. 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00%
Aviva.co.uk (Zenith Optimedia)
Vodafone.co.uk (OMD)
Cathaypacific.com (UM)
Tiffany.com (WPP)
Display Traffic Share
Advertiser
Traffic Contribution of GDN
Others GDN
*Data sourced from Similarweb on 17/5/16
• GDN scored lowest in brand safety
based on factors around whitelisting,
black listing, site blocking, custom
targeting and negative news adjacency.
• Yet, it is the most commonly used RTB
source for the Agency Trading Desks
• Main way to mitigate this is to utilise
multiple sources and verify which yields
the most brand safe placements/traffic
10. Time based campaigns only
Time-based programmatic
• Marketing campaigns are
traditionally based on time
intervals and seasonality
• Stopping a campaign
disrupts optimisation
• It results in gaps in
analysis and false blame
11. 2.5
2.7
2.9
3.1
3.3
3.5
3.7
3.9
4.1
4.3
4.5
Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
CPA
Time-based Performance
Campaign 1
Campaign 2
Campaign 3
?
• Time
between
campaigns
results in loss
of learnings
• Results can
be blamed on
unknown
factors
• Limits
accountability
• Staying in market
improves
performance
• Key is to establish
an Always-on
baseline and run
time-based
campaigns over
that baseline
14. 0
100
200
300
400
500
600
700
800
900
1000
PC 1 PC 7 PC 30 PV 1 PV 7 PV 30
Sales vs Attribution Windows
Sales
The Mystery of Attribution
• Too many marketers
don’t know the attribution
model used in their
reports
• Graph shows real data
from a national e-
commerce advertiser
• Important to understand
the proportion of
conversion coming
through via a click-thru
window versus a view-
thru window
• Not disclosing the
attribution model and
window is misleading
and deceptive
15. Error Magnitude
The further you get from the buyers true goal,
the greater the error (and it’s cost)
Click
ROMI
View
Error
Acquisition
17. CPM CPC Clicks Conversions
$3.20 $3.84 1570 62
$1.80 $2.16 1874 54
$2.40 $2.88 1953 71
$1.20 $1.44 2044 97
$3.90 $4.68 1453 57
$4.10 $4.92 1653 48
$3.20 $3.84 1754 66
$2.40 $2.88 1955 74
RED FLAGS
• Totals only (missing
columns)
• Method used to
hide the
‘performance’ of the
campaign and
eliminate the
possibility for
benchmarking
against industry
standards
18. 0
20
40
60
80
100
120
1 2 3 4 5 6 7 8
Conversions
Conversions
RED FLAGS
• Graphs only (no
trends) makes it
difficult to develop
findings if no
analysis is given for
the peaks and
troughs throughout
the campaigns
19. 0
20
40
60
80
100
120
1 2 3 4 5 6 7 8
Conversions
Conversions
RED FLAGS
• Selective
timeframes and
hiding negatives
• Results always
looking great is
also a sign that lack
of transparency and
obfuscation of data
could be occurring
• Blocking the ability
to see raw data or
edit excel reports is
another big red flag
✔
20. Mandates and conflict of interest
• Many agency groups
have a mandate to only
use their in-house
trading desk
• This creates a conflict of
interest and agencies fail
to act within the best
interests of the
advertiser
• Advertisers have the
right to know and control
where their ad dollars
are spent
21. Setting the bar
Low
• Major problem in the
industry around agencies
intentionally limiting
expectations
• Advertisers should avoid
proxy metrics and focus
on the goals that matter
• Programmatic
advertising can be
accountable to true
performance goals such
as engagement, leads,
sales and revenue.
22. Seller vs Buyer
• Seller
• Cost per Thousand
Impressions(CPM/RPM)
• Revenue per Page
• Revenue per Visitor
• Cost per Click (CPC)
• Buyer
• Cost per Click (CPC)
• Cost per Action (CPA)
• Lifetime Value (LTV)
• Return on Marketing
Investment (ROMI)
CPM CPC CPA
25. Strategy
• Do your business goals align with your campaign
goals?
• Is your strategy talking to customers at different
mindsets and not just awareness or acquisition
only?
• Is your media plan adaptive or static? How does it
change based on interactions and performance?
26. Technology
• What technology is enabling the campaign to
succeed?
• Is the tech proprietary to the vendor/agency or is it
leased?
• What is the cost of ownership?
• What was the decision in choosing this
technology?
• How does it add value to the success of the
campaign?
27. Operations
• Do you know the structure of the team delivering
the programmatic solution?
• Do you deal with an account manager only or do
you have interactions with other roles such as
strategist, campaign manager and digital/tag
manager?
• How long have they been in this space?
• What other solutions do they manage as this will
highlight whether they are a generalist or
specialist?
28. Media
• What channels are you utilising in your media
strategy? Are these channels the most beneficial to
achieving your business goals?
• What sources are chosen to deliver these
channels? Why were they chosen? Are they agile
and adaptive based on performance?
• What are the triggers for why new sources are
used? How often does this happen?
29. Price
• What pricing model is the media based on? Is it
dynamic or flat? Are their limits to the budget and
bidding price?
• What goals is the price optimising towards?
• How much are you paying your provider? What is
this based on, hours or %?
• What value are you getting in return?