SMX East 2016 - Optimize Google Shopping with the help of Euclid

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#SMX #14A @whoop_app

Optimize Google Shopping with the help of Euclid

#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

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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

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Euclid (of Alexandria) or “Father of Geometry”

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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 mediumproduct-terms

like “free 5.0”

high Shared Budget

Other highproduct-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

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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

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Third Dimension: Query Types

$0.15 $0.32 $0.05 $0.17 $0.57 $0.10 $0.11

Based on Query Sculpting

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Query Sculpting Moderate

the Google Shopping autopilot

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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 SculptingSolving 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

#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 SculptingSolving a big problem of Google Shopping

#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 ROASACTION

(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.

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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

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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

#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

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LEARN MORE: UPCOMING @SMX EVENTS

THANK YOU! SEE YOU AT THE NEXT #SMX

#SMX #14A @whoop_app

LEARN MORE: UPCOMING @SMX EVENTS

Additional Slides Implementation Guide

Query Sculpting

Get this presentation at:

https://whoop.rocks/smxeast16

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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 funnelwhich 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”

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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.