The document provides 5 tips for increasing ROI on Google Shopping campaigns: 1) Choose the right metric like ROAS or ROI instead of CPC, 2) Use a granular campaign structure down to the SKU level with consideration for query intent, 3) Allocate budgets intelligently across devices based on performance, 4) Go beyond standard bidding algorithms by incorporating data from Google Analytics, and 5) Use sophisticated audience segmentation like RLSA (Reach, Loyalty, Spend, Affinity) beyond standard or basic audiences.

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Gerasimos Nikolopoulos, CEO adaplo
(@gerasini, @adaploAds)
5 tips to increase your ROI on Google Shopping
Automated ads that drive sales

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Launch sophisticated campaigns on Google AdWords and
Facebook ads based on real-time data from your Magento store

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Sophisticated advertisers invest on Shopping

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Let’s make “Shopping” even better!

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Let’s score some quick wins

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Quick wins -> Performance improves -> More available budget ->
More sales -> Deeper optimisations -> More sales
So that we can expand

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1. Choose the right metric

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CPC = Cost / Clicks
CPC = 5.453€ / 32.456 clicks = 0.23€
CPC

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CPA = Cost / transactions
CPA = 5.453€ / 550 transactions = 9.91 €/transaction
CPA > CPC

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ROAS = Revenue / Ad Cost
ROAS = 5.453€ / 745€ = x7.32
ROAS > CPA > CPC

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Substitute revenue with net revenue.
Not all products have the same margins.
ROI > ROAS > CPA > CPC

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Full ROI (lifetime value, ROPO) > ROI > ROAS > CPA > CPC

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Full ROI (lifetime value, ROPO) > ROI > ROAS > CPA > CPC

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You are not going for perfection,
you are going for one step closer to the
truth

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2. Granural campaign structure

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One more level on the account hierarchy

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Suboptimal account structures

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We have the option to go really granural
SKU-level bidding

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Think also query intent

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Think also query intent

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3. Intelligent device budget allocation

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Different devices. Different performance.

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Different devices. Different performance.

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If you do not work on it, you are losing $

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You need to add bid modifiers. Look at GA.

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4. Go beyond standard bidding algorithms

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Bidding algorithms are hard

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Different bidding options

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Standard bidding method limitations
1.Need lots of data to work (not good for smaller clients)
2.Need training time, which means training $$$
3.Do not take into account other forms of value (profit,
offline, etc)

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Google Analytics is a great source to enhance your bidding

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5. Use RLSA

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We could advertise with no segmentation
All visitors
Bid 0.10

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Having the same bid for all different audiences
Non-visitor
Bid 0.10
Returning visitor
Bid 0.10
Customer
Bid 0.10

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Different audiences, however, respond differently
Non-visitor
Bid 0.10
Returning visitor
Bid 0.10
Customer
Bid 0.10
(CR 0.7%) (CR 1.2%) (CR 2.8%)

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By segmenting and customizing we can get better performance
Non-visitor
Bid 0.07
Returning visitor
Bid 0.14
Customer
Bid 0.21
(CR 0.7%) (CR 1.2%) (CR 2.8%)

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3 audiences, however, is not enough these days
Standard audiences
●All visitors
●Cart abandoners
●Converters
●“Smart lists”
Advanced audiences
Combination of dimensions below
●Intent (all, view, cart, purchase)
●Duration (1, 3, 7, 14, 30, 30+)
Special lists
●CRM targeting (all past customers, RFM segments from our lists)
●High potential lists (viewed top products, visited X times)

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1.Choose the right metric
2.Setup a granular campaign structure
3.Implement intelligent device budget allocation
4.Go beyond standard bidding algorithms
5.Use RLSA
Summary

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Why not start today?