How Daytrip lifted ROAS 47% by consolidating bid management into Multi-Target Portfolios
Google Marketing Platform wrote and published this one, and Daytrip approved being named in it. Daytrip was running campaigns across multiple platforms and ad types, each bidding in its own silo against its own thin conversion data. The account moved to Search Ads 360 Multi-Target Portfolios, so campaigns pool their learning while keeping separate targets per subgroup.
Year over year, conversions rose 118%, cost per action fell 33%, and return on ad spend rose 47%. Google's write-up is direct that this came from a holistic effort: internal ad strategy work plus favorable external factors, with Multi-Target Portfolios as the bidding piece. What the consolidation specifically delivered was better bidding efficiency across the board, lower bid-management cost, and a campaign-management load the team describes as significantly simplified.
“Daytrip achieves 47% ROAS uplift streamlining bid management using MTP”
Google wrote, approved and published this case study. It names Daytrip, credits eCommvert as the agency, and quotes Daytrip's Head of Performance on the record. The numbers below are Google's, not ours. Here is the original document.
Read the original Google case studyThis one is not our write-up. Google Marketing Platform wrote and published it, Daytrip approved it, and the client is named with their permission. The quote and the three headline numbers below are Google's. We have kept their framing, including the part where they say the growth came from more than one thing.
Who Daytrip is
Daytrip is a global travel platform founded in 2015. It sells private, door-to-door car transfers with professional drivers, built as a comfortable alternative to taking public transport between cities. The company is based in the Czech Republic and sells across EMEA and beyond.
Primary marketing objective: generate leads. Featured product area: Search Ads 360 bidding.
The problem: bids managed in silos
Daytrip was running a lot of paid activity at once. Multiple campaigns, across different platforms, across different ad types, each with its own performance goal.
Managed the ordinary way, that setup turns every campaign into an island. Each one bids off its own conversion data only, so the smaller ones never gather enough signal to bid well. And someone has to keep every target straight by hand, which is a real weekly cost once the account gets big enough.
Daytrip wanted three things out of a fix:
- Higher overall campaign productivity.
- Better return on the money going in.
- Less day-to-day management, so the team spends its hours on strategy instead of bid hygiene.
The approach: Enterprise Bidding with Multi-Target Portfolios
The account moved to an Enterprise Bidding setup built on Search Ads 360 Multi-Target Portfolios.
Two things make this work, and they pull in opposite directions until you combine them.
A portfolio bid strategy pools campaigns under one bidding model, so they learn from each other's conversions rather than each starving alone. That is the upside of consolidation. The catch is that a plain portfolio wants one target, and campaigns with genuinely different economics should not share one.
Multi-Target Portfolios remove that catch. You carve the portfolio into subgroups and give each subgroup its own target. Campaigns with different goals sit inside one strategy without being forced onto one number. And because Search Ads 360 sits above the ad platforms rather than inside one of them, a single portfolio can span cross-publisher campaigns, not just Google Ads.
So instead of managing bids in silos, the account structure was rebuilt around portfolios tailored to specific subgroups with distinct targets. Cross-campaign-type and cross-publisher activity merged into one unified bidding strategy.
"By consolidating cross-campaign and cross-publisher efforts into subgroups with tailored targets [through Multi-Target Portfolios (MTP)], we significantly simplified our campaign management."
Marek Lacina, Head of Performance, Daytrip
What we did
eCommvert handled the integration of Daytrip's Multi-Target Portfolio setup into Search Ads 360, so cross-channel conversion insight lands in one place.
That plumbing is the part people skip, and it is the part that decides whether any of this works. Automated bidding is only ever as good as the conversion data it optimizes against. Leave the data split by channel and the algorithm optimizes against a partial picture, confidently. Centralize it and the same algorithm starts bidding against full-funnel performance.
The results
Year over year, across the account:
| Metric | Change |
|---|---|
| Conversions | +118% |
| Cost per action | -33% |
| Return on ad spend | +47% |
Google's own write-up is direct about where that came from, and we are keeping their wording rather than improving on it. The year-over-year growth was the result of a holistic approach, driven by internal ad strategy optimizations and favorable external factors. Multi-Target Portfolios were the bidding piece of it.
What the consolidation specifically did: it improved bidding efficiency across the board, cut the cost of managing bids, and took a large amount of manual target-wrangling out of the week. Alongside the wider strategic work, that is what produced the numbers above.
What other teams could steal
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Consolidate the bidding, keep the targets separate. The usual trade-off is a false one. You do not have to choose between pooled conversion data and per-goal targets. A multi-target portfolio gives you both, which is why it beats both the one-strategy-per-campaign setup and the everything-on-one-target setup.
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Small campaigns bid badly because they are alone, not because they are bad. A campaign that cannot gather enough conversions on its own will never bid well on its own. Grouping it with related campaigns is usually a bigger lever than anything you can do to the campaign itself.
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Fix the conversion data before you judge the bidding. Cross-channel conversion insight sitting in one place is not admin work you get to do later. Until the data is centralized, automated bidding is optimizing against a partial view and you have no idea how good it could be.
Key Takeaways
Three things worth taking away.
Consolidate the bidding, keep the targets separate.
The usual trade-off is a false one. You do not have to choose between pooled conversion data and per-goal targets. A multi-target portfolio gives you both, which is why it beats both the one-strategy-per-campaign setup and the everything-on-one-target setup.
Small campaigns bid badly because they are alone, not because they are bad.
A campaign that cannot gather enough conversions on its own will never bid well on its own. Grouping it with related campaigns is usually a bigger lever than anything you can do inside the campaign itself.
Fix the conversion data before you judge the bidding.
Cross-channel conversion insight sitting in one place is not admin work you get to do later. Until the data is centralized, automated bidding is optimizing against a partial view and you have no idea how good it could be.
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