Empirical Analysis of Search
Advertising Strategies
BHANU C. VATTIKONDA, VACHA DAVE,
SAIKAT GUHA, ALEX C. SNOEREN
Query
Sponsored
results
Organic
results
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Huge and growing industry
Search Revenues ($ billions)
30
25
20
15
10
5
0
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
Source: IAB/PwC Internet Ad Revenue reports
3
Sponsored
Organic
Brand Ad
Competitor Ad
Are common advertising
strategies profitable?
Metrics for campaign analysis
 Click-through-rate (CTR)
 Measures ability to attract users but not quality of users
 Cost per acquisition (CPA) or cost per conversion:
 Does not capture profitability (e.g., in case of organic results)
 Profit-per-impression
 Requires access to sensitive financial information from advertisers
User Flow
Search impression
Conversion
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Search engine data
 User click information
 Cost of a particular advertising strategy
 Number of conversions that an advertiser receives
How much is a conversion
worth to the advertiser?
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Value of a conversion
 Advertisers specify bid value for an ad
 Indicates how much they are willing to spend
 We assume that advertisers are rational and want overall advertising to
be profitable
money advertiser is wiling to spend
 Value of a converison, 𝜆 =
number of conversions
total bid value
=
number of conversions
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Net acquisition benefit (NAB)
 We introduce a new metric--NAB--captures profitability of a particular strategy
 Advertiser spends 𝑐𝑜𝑠𝑡 on a particular strategy 𝑥
 Leads to 𝜋 conversions
 𝜆 is value of a conversion
 Profitability(𝑥) = 𝜋 ∗ 𝜆 − 𝑐𝑜𝑠𝑡
 𝑁𝐴𝐵 𝑥 = 𝜋 −
𝑐𝑜𝑠𝑡
,
𝜆
normalized for impressions
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Computing NAB
 𝑁𝐴𝐵 𝑥 = 𝜋 −
𝑐𝑜𝑠𝑡
𝜆
 Computing NAB for a strategy requires:
1. Conversions
2. Cost of the ad strategy
3. Value of a conversion (𝜆)
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Comparing ad strategies
 Compute NAB for each advertising strategy
 Compare NAB to see which ad strategy is more profitable
 If 𝑁𝐴𝐵 𝑥 > 𝑁𝐴𝐵 𝑦 then strategy 𝑥 is better than 𝑦
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Common ad strategies we analyze
 Cannibalization
 Advertising for own brand name
 Poaching
 Advertising for a competitors brand name
 Mobile ad extensions
 Using ad extensions (e.g., call extension) on mobile devices
Sponsored
Organic
Search engine dataset
 Month long click log data from a search engine
 Billions of clicks
 Millions of ads
 Conversions for both ad and organic clicks
 Several million dollars of ad spend
 Bid that the advertiser placed for each ad click
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Advertising for own brand name
 Advertise for brand name
 NAB is computed over search impressions where user searches for brand
name and ad is shown
 Do not advertise for brand name
 NAB is computed over search impressions where user searches for brand
name and ad is NOT shown
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Advertising for own brand name
Yes, advertise
Impressions
Conversions
Cost
Target cost
No, do not advertise
• Users search for brand • Users search for brand
and advertiser ad is
shown
• Total number of
conversions through
ads and organic results
and advertiser ad is
not shown
• Number of conversions
through organic results
• Cost of campaign
•0
•𝜆
•𝜆 --- but irrelevant
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NAB(ad)
Advertising on own brand name
NAB(noad)
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Incremental benefit is limited
32% advertisers
net loss
Why do advertisers advertise
− NAB(noad)
for NAB
theirad
brand
name?
NAB(noad)
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Click-through-rate is misleading
CTR
 Click-through-rate not correlated to campaign performance
NAB ad − NAB(noad)
NAB(noad)
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Summary
 We introduce NAB which can be used measure profitability of an ad
campaign without access to profit information from advertisers
 Advertisers often target the wrong users
 Common strategy of targeting own brand name can be a net loss
 Commonly used metrics can be misleading
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Thank you
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