Samsung Electronics
Adding a Performance Max campaign on top of existing Display and Discovery campaigns, with ML steering of bids, creative mix, and cross-channel allocation on an e-commerce conversion goal
Samsung Electronics multiplied conversions by 2.5 and cut cost per conversion by 60% by adding a Google Performance Max campaign on top of its Display and Discovery campaigns for the Galaxy Campus Store in Korea (controlled test over five weeks, 2022).
Key points
- Google Performance Max campaign added on top of existing Display and Discovery campaigns (Galaxy Campus Store).
- ML steering of bids, creative mix, and cross-channel allocation, tested against a control over five weeks.
- 2.5x conversions, cost per conversion -60%, click-through rate doubled.
- Evidence level B, mixed signals status.
Objective
Amplify the promotions of the Galaxy Campus Store, Samsung's online store reserved for Korean students, by finding new audiences without blowing up the cost per conversion.
The deployment
Samsung Electronics set up a controlled test in Korea on its Galaxy Campus Store, a store dedicated to students for mobile and IT products. The control group ran with its Display and Discovery campaigns alone; the test group added a Performance Max campaign on top. All targeted the same conversions: a page view or a purchase on the Samsung site. You upload the assets (videos, images, text), and Google's algorithm continuously decides which creative to show, on which channel among Search, YouTube, Display, Discover, Maps, and Gmail, and at what bid. The test ran for five weeks. On top of the existing campaigns, Performance Max produced 2.5 times more conversions, with cost per conversion down 60% and click-through rate doubled. After this result, Samsung extended its use of Performance Max, including on short campaigns, and began rolling out Video action campaigns in the first quarter of 2022.
Results Proof B
Quantified Think with Google case study, drawn from a controlled test (control group vs test) with a named quote from a Samsung Korea lead - platform bias. The reality of the store (Galaxy Campus Store) is corroborated by an independent press source, but the incremental effect is not confirmed in financial results.
How it works
Documented architectureThe stack in detail
- plateforme Google Ads Performance Max single campaign driven by Google's ML: bids, channel choice, and creative rotation across Search, YouTube, Display, Discover, Maps, and Gmail
- outil Smart Bidding automated bidding optimized on the defined conversion action (page view or purchase)
- outil Google tag / GA4 placement of the e-commerce conversion signal, shared between the control group and the test group
- plateforme Campagnes Display et Discovery existing campaigns kept as the control group, PMax added on top in the test group
How it runs, concretely
For ops teams-
1Set up conversion tracking properly Data team
Define the same conversion action for all campaigns (page view or purchase on the site), otherwise the A/B test is not comparable.
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2Structure the test incrementally Media team
A control group with Display + Discovery alone, a test group with Performance Max added. It is the delta between the two that measures the real contribution.
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3Supply assets in volume Creative team
Videos, images, and headlines in quantity to give the algorithm material. Few assets and it cycles through the same combinations.
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4Let it converge before concluding Google AI
Two weeks of ramp-up minimum. Cutting or reworking during this phase distorts the readout.
The e-commerce conversion (page view or purchase). If the conversion tag is poorly placed or incomplete, the algorithm optimizes on noise and the cost per conversion does not come down.
How your customers perceive this type of use
Sourced studiesLe pricing algorithmique est le terrain le plus inflammable : 68% des consommateurs disent se sentir leses quand les marques utilisent le pricing dynamique et 80% jugent plus dignes de confiance les marques aux prix constants (Gartner, 2024). L'equite percue varie selon le secteur : le pricing dynamique n'est juge juste que par 33% a 40% des repondants selon qu'il s'agit de concerts ou de cinemas (YouGov, 17 marches). Le prix personnalise par les donnees individuelles est le plus rejete : 47% des Americains s'y opposent fermement (Consumer Reports, 2024).
Acceptance conditions
- La constance des prix comme signal de confiance : 80% jugent plus fiables les marques aux prix stables (Gartner 2024)
- Le secteur conditionne l'equite percue : le pricing dynamique est mieux tolere pour les cinemas (40% le jugent juste) que pour les concerts (33%) (YouGov 2024)
Red lines
- Le pricing dynamique percu comme abus : 68% se sentent leses (Gartner 2024)
- Le prix individualise a partir des donnees personnelles : 47% d'opposition ferme (Consumer Reports 2024)
- Les frais caches et hausses imprevues, vecus par 79% des consommateurs sur un an et associes a la perte de confiance (Gartner 2024)
Sources: Gartner 2024 · YouGov 2024 · Consumer Reports 2024
How to replicate
Inference, not sourcedData prerequisites
- Reliable e-commerce conversion tracking (page view / purchase)
- Consent Mode v2 in the EU
- A clean product feed if selling online
Org prerequisites
- Video/image/text creative assets in volume
- Ability to structure an incremental test (control vs test)
Possible stack
- Google Ads Performance Max + GA4, on top of existing Display/Discovery campaigns
The plan, step by step
- Step 1Validate conversion tracking: a single conversion action (page view or purchase), identical across all campaignsDeliverable: Tag validated in Google Ads / GA4, same action for control and test
- Step 2Gather assets in volume (videos, images, headlines, descriptions) for the asset groupsDeliverable: Asset bank loaded, several formats per group
- Step 3Structure the incremental test: Display + Discovery alone as control, PMax added on the test scopeDeliverable: Written test plan with budget and KPIs (conversions, cost per conversion)
- Step 4Launch the campaign and do not rework it during ramp-upDeliverable: Campaign live, two weeks of learning without intervention
- Step 5Compare conversions and cost per conversion between control and test, then decide on scalingDeliverable: Documented incremental readout and budget decision
First step: Launch an official Google Ads PMax test on top of the current campaigns, on a single conversion goal, and measure the delta rather than raw volume.
The same pattern, proven in other industries
adidas
AI-driven audience prospecting and bidding (ARO) across the full funnel
Allwyn
AI-driven omnichannel programmatic buying with retail data activation
Nivea
genAI testing and optimization of creative elements + automated localization at scale
Sources
- S1 How Samsung Electronics boosts conversions - Think with Google APAC Interested party archive pending
- S2 Korean students can get discounts on various Samsung products via Galaxy Campus Store - SamMobile Secondary archive pending
An error, newer info, a source?
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