Optimize Google Shopping with help of Euclid What does a Greek philosopher have to do with PPC and Google Shopping? Well, his theories are a great approach for optimizing your Google Shopping campaign. We open the Open the black box Product Listing Ads 1. Black-Box-Bidding 2. First Dimension (Product Targets) 3. Second Dimension (Devices) 4.Third Dimension (Query Types) 5. Moderate the Google Shopping autopilot

1. #SMX #14A @whoop_app
Optimize Google Shopping
with the help of Euclid

2. #SMX #14A @whoop_app
Intro
Euclid was not exactly a PLA-Shopper
Open the blackbox Product Listing Ads
1. Blackbox-Bidding
2. First Dimension (Product Targets)
3. Second Dimension (Devices)
4.Third Dimension (Query Types)
5. Moderate the Google Shopping autopilot
Agenda

3. #SMX #14A @whoop_app
Who am I and what we are doing all day long
1,2 billion
bidchanges per month
250
managed datafeeds
15 million
products
500 mil.
search queries per month
The monthly workload for our
PLA Bidding Tool
Christian Scharmüller
Strategic Customer Development
whoopapp.com

4. #SMX #14A @whoop_app
Euclid (of Alexandria) or “Father of Geometry”

5. #SMX #14A @whoop_app
One „all products“ target for your
whole assortment
Black Box Bidding
0,55$

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First Dimension: Items
$0.15 $0.32 $0.05 $0.17 $0.57 $0.10 $0.11
One Ad Group per SKU

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Second Dimension: Devices
$0.15 $0.32 $0.05 $0.17 $0.57 $0.10 $0.11
The ad group structure enables you to set device modifiers (= bids)
for every item

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Third Dimension: Query Types (or intent)
CAMPAIGN
GROUP
PRIORITY NEG.KEYWORDS BIDS BUDGET
Products low none
very
high
Brands medium
product-terms
like “free 5.0”
high
Shared
Budget
Other high
product-terms
brand terms
low
Nike Free 5.0
Running Shoes
Nike Men’s Running Shoes
Nike Free 5.0 …
99.90 €
shop.co.uk
Short explanation of the underlying concept

9. #SMX #14A @whoop_app
Characteristics of shopping queries
Low Med High
Query Word Count 1-2 2-4 3 or more
Brand Reference not likely very likely most likely
Intent-based Query
Components
not likely
likely
(top-rated. price.
comparison)
likely
(buy. online shop.
financing options)
Match to Inventory
very many products
match
many products match
only a handful of
products match
Last Click
Conversion Rates
low medium high
Traffic Volume high very low to low medium to high

10. #SMX #14A @whoop_app
Third Dimension: Query Types
$0.15 $0.32 $0.05 $0.17 $0.57 $0.10 $0.11
Based on Query Sculpting

11. #SMX #14A @whoop_app
Query Sculpting Moderate
the Google Shopping autopilot

12. #SMX #14A @whoop_app
There are no keywords for Shopping Campaigns. but you are able to use negative keywords!
Shopping campaigns are auto-targeted

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Target-ROAS: 5 Actual ROAS: 2.17
Action: Reducing the bids
PRODUCT CLICKS CONV CR VPC CPC
Nike Free 5.0 Running Shoes Neon 1500 19 1.26 % € 1.26 € 0.58
Every type of query is treated the same!
The problem of Google Shopping:
Nike Free 5.0 …
99.90 €
shop.co.uk
Query Sculpting
Solving a big problem of Google Shopping

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Query Sculpting
SEARCH TERMS (= Queries) CLICKS CONV CR VPC CPC ROAS
Nike Free 5.0 100 3 3% € 3 € 0.5 6
Buy Nike Men’s Running
Shoes Free
250 12 4.8% € 4.8 € 0.4 12
Men’s Running Shoes 300 0 0% € 0 € 0.6 0
Running Shoes 600 1 0.16% € 0.16 € 0.7 0.22
Nike Men’s Running Shoes 250 3 1.2% € 1.2 € 0.5 2.4
Nike Free 5.0 …
99.90 €
shop.co.uk
Solving a big problem of Google Shopping

15. #SMX #14A @whoop_app
SEARCH TERMS (= Queries) CLICKS CONV CR VPC CPC ROAS
Nike Free 5.0 600 1 0.16% € 0.16 € 0.7 0.22
Buy Nike Men’s Running
Shoes Free
250 12 4.8% € 4.8 € 0.4 12
Men’s Running Shoes 300 0 0% € 0 € 0.6 0
Running Shoes 100 3 3% € 3 € 0.5 6
Nike Men’s Running Shoes 250 3 1.2% € 1.2 € 0.5 2.4
Nike Free 5.0 …
99.90 €
shop.co.uk
Query Sculpting
Solving a big problem of Google Shopping

16. #SMX #14A @whoop_app
3 Buckets for your Search Queries
QUERIES CLICKS CONV CR VPC CPC ROAS SCORE
Nike Free 5.0 600 1 0.16% € 0.16 € 0.7 0.22 high
Buy Nike Men’s Running Shoes 250 12 4.8% € 4.8 € 0.4 12 high
Men’s running shoes 300 0 0% € 0 € 0.6 0 low
Running Shoes 100 3 3% € 3 € 0.5 6 low
Nike Men’s Running Shoes 250 3 1.2% € 1.2 € 0.5 2.4 med
We use a score for defining the likeliness of a conversion.
The score is used to group the queries into 3 buckets.

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Query Buckets
CLICKS CONV CR VPC CPC ROAS
ACTION
(for Target-ROAS > 5)
high
(lower funnel)
350 15 4.29% € 4.29 € 0.43 9.98 Large Increase of Bids
Med
(mid funnel)
250 3 1.2% € 1.2 € 0.5 2.4 Small Increase of Bids
Low
(upper funnel)
900 1 0.11% € 0.11 € 0.66 0.16 Large Decrease of Bids
You can see the results.

18. #SMX #14A @whoop_app
Campaign Structure – The Concept
Low Performing Queries
as Negative Exact
Low Performing Queries
as Negative Exact
High Performing Queries
as Negative Phrase
Low Priority
Medium
Priority
High
Priority
CAMPAIGN
PRIORITY
NEGATIVE KEYWORDS
none
Campaign 2 ”high”
Campaign 3 ”low”
Campaign 1 ”med”
Traffic

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Term Scoring
SCORE
Brand
reference
tdf/idf
weight
Color
reference
Performance
metrics
Term
length
Many
others

20. #SMX #14A @whoop_app
Term Scoring – A very simplified Example
WordCount + if (BrandRef = True, 2.0) + If (ColorRef = True, 3.0) + NormalizedConversionRate*2
further Reading: http://nlp.stanford.edu/IR-book/pdf/irbookonlinereading.pdf
“Running Shoes”
2.32=
0.16% CR
2 0 0 0.32+ + +
“Buy Nike Men’s Running Shoes Black”
20.6=2 3 9.66
4.8% CR
+ + +

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Scored terms based on an advanced model
CLICKS CR COST SCORE
asics gt 2000 4 235 6.38% 81.73 154.31
asics gt 2000 4 men 85 4.71% 31.98 145.48
adidas zx 750 522 4.79% 172.78 142.40
asics gel cumulus 17 211 4.27% 97.1 131.10
asics gt 2000 4 women 89 3.37% 37.76 124.15
asics gt 2000 276 3.26% 127.14 121.10
nike metcon 2 251 3.19% 63.63 120.14
asics kayano 22 132 3.03% 41.93 120.07
asics nimbus 18 104 2.88% 33.44 118.08
asics gel nimbus 18 130 2.31% 44.21 116.98
…
(Potential) High performers - Last 30 Days

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CLICKS CR COST SCORE
knee bandage 13 0.00% 5.23 1.5
asics 25 0.00% 12.89 1.67
sports duffle bag 17 0.00% 4.29 2.11
trail shoes 16 0.00% 6.82 2.25
beach slippers 33 0.00% 16.86 2.53
adidas leisure suit 13 0.00% 4.27 3.53
nike duffle bag 13 0.00% 3.63 3.79
nike bag 19 0.00% 6.11 3.85
adidas running shoes 28 0.00% 16.46 3.89
nike slippers 14 0.00% 5.28 3.89
running shoes women 13 0.00% 6.23 3.94
…
Scored terms based on an advanced model
(Potential) Low performers - Last 30 Days

23. #SMX #14A @whoop_app
Be as granular as possible
Setup up an item-based campaign structure
Set device-specific Bids per adgroup
Open the blackbox „Product Listing Ads“
set up 3 identical campaigns
set the right priorities
Score your search queries and build 3 buckets
set up proper negative keyword-lists
Conclusion

24. #SMX #14A @whoop_app
LEARN MORE: UPCOMING @SMX EVENTS
THANK YOU!
SEE YOU AT THE NEXT #SMX

25. #SMX #14A @whoop_app
LEARN MORE: UPCOMING @SMX EVENTS
Additional Slides
Implementation Guide
Query Sculpting
Get this presentation at:
https://whoop.rocks/smxeast16

26. #SMX #14A @whoop_app
Implementation Guide
high
(lower funnel)
Add with
medium Priority
low
(upper funnel)
Add with
low priority
flow
flow
Mid
(mid funnel)
Existing Campaign
Set to High Priority
Add 2 Campaigns
per existing
Shopping Campaign
All non-polarized queries are
managed via the mid funnel
which serves as a pool for them.
Low Performers List
as negative Exact
[knee bandage]
[sports duffle bag]
[trail shoes]
[beach slippers]
[adidas leisure suit]
High Performers List Low Performers List
as negative Phrase
[knee bandage]
[sports duffle bag]
[trail shoes]
[beach slippers]
[adidas leisure suit]
as negative Exact
“asics gt 2000 4”
“adidas zx 750”
“asics gel cumulus 17”
“nike metcon 2”
“asics kayano 22”

27. #SMX #14A @whoop_app
Choose the right Campaign Priorities
Don’t’ forget to clone all other campaign settings

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Tip: Use Negative Keyword Lists
And add them to all applicable campaigns.