Measurement company Fospha, working alongside Google, this month published findings from a structured Q4 2025 program showing that retail eCommerce brands which spread their budgets across more of Google's advertising channels - particularly Demand Gen and YouTube - achieved substantially higher returns than those concentrated in Performance Max and Brand Search alone.

Fospha released the Full-Funnel Google Report in 2026 documenting the results of a joint program that ran between October 29 and December 16, 2025. The program covered 25 retail eCommerce brands across three industries - fashion, beauty, and consumer goods - spanning 28 market deployments. Brands participated for three months of structured support from Fospha and Google. Results were benchmarked against a matched control group of Fospha advertisers who did not take part, designed to isolate program effects from broader seasonal market trends.

According to Fospha, the analysis window for the formal comparison ran from November 1 to December 31, 2025. The control cohort was selected by analyzing the funded group's spending patterns and share of wallet, then identifying comparable non-funded clients with metrics within one standard deviation of both the funded cohort's average spend and Google share of wallet. All figures in the report use Fospha measurement rather than platform-reported data, a distinction the company treats as central to the findings.

The measurement gap the report is built around

The structural argument in the report starts with last-click attribution. According to Fospha, the past decade of digital measurement has narrowed around click-based attribution systems that systematically overvalue channels that capture demand - Search, Brand Search, Performance Max - while undervaluing channels that create it, specifically Demand Gen and YouTube. Google's ecosystem now spans YouTube, Discover, Gmail, Shopping, and Search, but most measurement frameworks have not kept pace with that expansion.

The commercial consequence is direct. Brands investing only in demand capture, according to Fospha, are limiting their growth ceiling. Performance Max and Brand Search remain strong conversion engines, but the report argues their efficiency ceiling rises when Demand Gen and YouTube are actively expanding the pool of warm, high-intent audiences available to convert. The report frames this not as a trade-off between channel types but as a compounding effect: upper-funnel investment makes lower-funnel channels more efficient, which in turn builds the commercial case to invest more in both.

This is a problem the advertising industry has been circling for several years. As Demand Gen expanded across Google's inventory surfaces and replaced Video Action Campaigns by April 2025, the channel's measurement challenges - rooted in its impression-driven rather than click-driven impact - became more pressing. The same attribution discrepancies that affect Performance Max reporting affect Demand Gen and YouTube, where last-click models assign zero credit to interactions that preceded the final conversion touchpoint.

Channel diversification and ROAS: the numbers

The first major finding from the report concerns channel mix diversification. According to Fospha, brands that added just one additional Google channel to their existing mix achieved 14% higher ROAS compared with brands that maintained their channel count. Those that added two channels achieved 37% higher ROAS than brands that did not grow their channel count at all.

The mechanism Fospha identifies is signal quality. A broader channel mix gives Google's automated systems more data to work with and creates multiple touchpoints across the customer journey. Each additional channel provides incremental behavioral signal that helps the algorithm identify and reach audiences more efficiently across the full stack.

The 37% ROAS gap between brands adding two channels and those adding none is a substantial spread, particularly during Q4 when competition for Google's inventory typically compresses margins. It suggests that brands relying on a concentrated mix - typically PMAX and Brand Search, which remain most advertisers' default starting point - may be hitting an efficiency ceiling that is structural rather than executional.

Demand Gen budget share and overall Google ROAS

The second finding concerns how much of the total Google budget brands allocated to Demand Gen specifically. Within the Deep Dive cohort, the relationship between Demand Gen share of wallet and overall Google ROAS was pronounced. According to Fospha, brands allocating between 5% and 10% of their Google budget to Demand Gen already outperformed those in the 0-5% range. The gap widened considerably at higher allocation levels: brands investing between 10% and 20% of their Google budget in Demand Gen achieved double the ROAS of those in the 0-5% range. The report states this as a 100% ROAS difference between the two groups.

That finding carries practical implications for how most brands currently structure their Google accounts. The report notes that most accounts still spend well below the highest-performing threshold of 10-20%, suggesting room to scale without cannibalizing lower-funnel campaign performance. The data from the report supports the opposite conclusion to the one many advertisers have historically assumed: that directing budget toward Demand Gen would come at the expense of performance-oriented campaigns.

The Fospha findings on Demand Gen share of wallet connect to a broader industry shift. Google launched four new Demand Gen capabilities in November 2025, adding asset experiments, video enhancements, brand suitability controls, and AI image automation. The platform's own internal data, referenced at the time of that announcement, showed Demand Gen advertisers achieved an average 20% increase in conversions or conversion value during the first half of 2025 across more than 100 product launches. The Fospha program extends that directional finding into a Q4 context with a controlled comparison group.

The third finding is the one Fospha describes as most directly challenging to conventional last-click-based measurement. Deep Dive brands increased Demand Gen spending by 367% year-over-year and YouTube spending by 118% year-over-year. The control group, by contrast, grew Demand Gen by only 43% and cut YouTube spend by 57% year-over-year.

The downstream effect on lower-funnel channels was measurable. For Performance Max, Deep Dive brands saw 8% ROAS growth year-over-year and a 8% reduction in customer acquisition cost. The control group's PMAX ROAS grew by only 5% while CAC increased 11%. For Brand Search, the difference was larger: Deep Dive brands achieved 9% ROAS improvement and a 12% CAC reduction, while the control group saw Brand Search ROAS decline 17% and CAC increase 33%.

The report frames these figures as evidence that upper-funnel investment actively protects and amplifies lower-funnel returns. Demand Gen warms audiences and builds brand familiarity, which directly improves conversion rates and lowers costs at the PMAX and Brand Search stage. According to Fospha, Google's algorithms receive richer signal when brands build demand upstream, and audiences arriving at conversion formats are warmer and more likely to convert.

The attribution problem that obscures this relationship is significant. As PPC Land has reported on Demand Gen's platform-comparable conversion columns, last-click models assign zero value to YouTube and Demand Gen impressions that drive Brand Search queries or PMAX conversions days or weeks later. Fospha's full-funnel measurement captures what it calls the "true downstream impact" - the attribution that click-based models structurally cannot see.

YouTube: scale, creative formats, and algorithm continuity

YouTube functions as the top of the full-funnel framework in Fospha's model, positioned to build awareness and consideration before Demand Gen converts that attention into action. According to Fospha, YouTube has over 2.7 billion monthly active users with more than a billion hours of video watched daily. The platform's scale, combined with its impression-driven impact, means click-based attribution understates its contribution significantly. Fospha's full-funnel measurement consistently reveals higher true ROAS than platform-reported figures across clients in its base.

The report references Fospha cross-client analysis from 2025 indicating that brands investing in both YouTube and Demand Gen achieved 32% stronger blended revenue growth year-over-year versus brands that did not scale those channels. The most aggressive scalers - those increasing spend by more than 400% - saw 145% stronger growth, which Fospha describes as demonstrating that returns compound as investment scales.

From a campaign execution standpoint, the report notes that YouTube's algorithm requires sustained, consistent spend to function well. Switching spending on and off prevents the algorithm from exiting its learning phase. The technical recommendation - derived from Google's own guidance cited in the report - is that Video Reach Campaigns using AI-powered mixed formats, combining In-Stream, In-Feed, and Shorts, deliver 40% higher ROAS than In-Stream only formats. AI-powered Video View Campaigns mixing those three formats drive 40% more views, 30% lower cost per view, and 25% higher search lift than In-Stream only.

Demand Gen: campaign structure and bid strategy patterns

Demand Gen reaches users across YouTube Shorts, Discover, and Gmail. Its role in the Fospha framework is explicitly mid-funnel: creating and converting demand by bridging broad awareness and lower-funnel intent capture. The report includes operational data from the 25 deep-dive brands showing that successful performers ran an average of 2.2 active Demand Gen campaigns per client market combination.

That is a deliberately low number. The report notes that "less is more from a campaign perspective" for Demand Gen. Campaign distribution data shows 43% of clients ran a single campaign, 32% ran two campaigns, 11% ran four, and 7% ran six to eight. The concentration in lower campaign counts reflects Fospha's finding that consolidation gives Google's algorithm more conversion signal to work with, which speeds up the learning phase and improves optimization quality.

Maximize Conversions was the dominant bid strategy, used by 68% of clients, followed by Target ROAS at 18%, Target CPA at 7%, Maximize Conversion Value at 4%, and Maximize Clicks at 3%. Purchases was the primary campaign goal for 61% of total goal instances recorded, followed by customer acquisition at 16%, add to basket at 13%, and begin checkout at 5%.

On budget thresholds, the report references Google's recommended minimum of approximately $130 per day per campaign and advises limiting bid changes to within 15% to prevent the algorithm from resetting. Demand Gen typically requires more than 50 conversions in 30 days to exit the learning phase. The operational note on pausing is pointed: lowering to a maintenance budget rather than pausing spend prevents performance volatility. Pausing entirely forces the algorithm to restart its learning phase when spend resumes.

For creative setup, the guidance calls for a minimum of nine different assets at launch - three horizontal videos, three vertical, and three square - to give the AI sufficient variation for testing. This connects to Google Think Week 2025's emphasis on AI-driven creative testing through Asset Studio, which became central to Google's retail advertising pitch for Q4 2025.

Case studies: three brands and their numbers

The report includes individual brand results from three program participants. Each case illustrates a different entry point into full-funnel investment.

Finisterre, an outdoor apparel brand, had historically concentrated its Google activity in lower-funnel channels. Through the program, working with Push agency, Finisterre positioned Demand Gen as its primary upper-funnel lever heading into Q4. Over the program period from October 29 to December 16, 2025, Demand Gen daily spend increased by 5.7 times. According to Fospha, Finisterre achieved a 69% increase in Demand Gen share of Google revenue year-over-year, a 73% reduction in Brand Search CAC in Q4 year-over-year, and a 27% increase in total Google revenue year-over-year.

Derek Rose, a luxury brand, had concentrated its Google strategy in PMAX and Brand Search, making peak performance dependent on existing brand interest. The brand implemented a two-phase approach: more than doubling Demand Gen spend pre-peak to build awareness, then reallocating that budget to PMAX and Brand Search during the highest trading days. By Q4, Demand Gen represented 7% of the total Google mix. Results included Brand Search ROAS up 111% year-over-year, generating 39% more revenue at 34% less spend, and overall Google ROAS up 44% with 33% more revenue at 7% lower spend in Q4 year-over-year.

Corston Architectural Detail had seen Demand Gen results in the UK but had not launched the channel in France, where the mix was weighted toward Search and PMAX. The program provided the structure to introduce Demand Gen in France gradually, with Fospha delivering spend plans for incremental scaling and Google providing campaign setup guidance. According to Fospha, after the launch, Corston's Google mix drove 61% more new conversions at 13% improved CAC in Q4 year-over-year, with overall Q4 improvements including 47% greater revenue, 69% more new conversions, and 24% improved CAC year-over-year.

Why measurement is the precondition

The report is explicit that the outcomes reported by these brands were only legible because Fospha's full-funnel measurement was in place from the start. Without attribution that captures the downstream impact of Demand Gen and YouTube on PMAX and Brand Search performance, the investment case for upper-funnel Google channels rests on inference rather than data.

That measurement gap is not unique to Google. TikTok's Attribution Portfolio launch in May 2026 addressed the same structural problem on a different platform: last-click models consistently undervalue channels that operate earlier in the customer journey. Google Analytics' cross-channel budgeting and attribution update in January 2026 added multi-touch attribution capabilities that begin to address this gap natively, though Fospha argues that its daily, always-on full-funnel measurement provides a more continuous read than periodic studies or platform-native attribution can deliver.

According to Fospha, the program ran in two phases. The first phase built mid-to-upper funnel momentum in the weeks leading up to the peak trading period. The second phase shifted focus to demand capture as peak trading began. This phasing strategy - building awareness before peak, then capturing the demand created - is visible in the Derek Rose case, where the budget was explicitly shifted between phases, and in the Corston case, where Demand Gen was scaled gradually as in-flight measurement confirmed results were materializing.

Fospha's measurement approach brought Google Ads reporting, client analytics, and Fospha attribution into a single view, providing daily in-flight performance reads that enabled real-time optimization throughout the program. That cadence - daily measurement across a two-month peak period - is what the report's authors say gave brands the confidence to scale Demand Gen and YouTube spending rather than retreating to the lower-funnel channels where last-click attribution makes performance visible.

For the marketing community, the Fospha report adds a controlled, multi-brand data point to a debate that has been largely theoretical for performance-focused advertisers. The 37% ROAS gap between brands that diversified their channel mix and those that did not, measured across 25 brands against a comparable control group during Q4 2025, provides a specific benchmark that media planners and performance teams can reference when building the internal case for upper-funnel Google investment.

20 best practices from the report

The following practices are drawn directly from the Fospha Full-Funnel Google Report, combining the program's data findings with the campaign guidance cited as recommended by Google and applied by the Deep Dive cohort.

  • Add at least one new Google channel if the account is currently running only Performance Max and Brand Search. The report shows a single channel addition produced 14% higher ROAS; adding two produced 37% higher ROAS compared to brands that kept their mix unchanged.
  • Target a Demand Gen share of 10-20% of the total Google budget. Brands in the 10-20% range achieved double the ROAS of those allocating 0-5% to Demand Gen. The report notes most accounts are still well below this threshold.
  • Do not treat upper-funnel and lower-funnel channels as competing for the same budget. Program data shows that Deep Dive brands scaled Demand Gen and YouTube while simultaneously growing their PMAX and Brand Search investment, not reducing it.
  • Use full-funnel measurement before scaling Demand Gen or YouTube. Without attribution that captures downstream impact on PMAX and Brand Search, the contribution of upper-funnel channels is structurally invisible to last-click reporting. The report treats this as the precondition for confident scaling, not a follow-on step.
  • Treat YouTube as an always-on investment, not a campaign burst. Consistent spend compounds returns. Switching on and off prevents the algorithm from exiting its learning phase and resets optimization progress each time.
  • Use Video Reach Campaigns mixing In-Stream, In-Feed, and Shorts rather than In-Stream only. According to Google guidance cited in the report, AI-powered mixed-format VRC delivers 40% higher ROAS than In-Stream only formats.
  • Use Video View Campaigns with the same three-format mix for consideration objectives. AI-powered VVC mixing In-Stream, In-Feed, and Shorts drives 40% more views, 30% lower cost per view, and 25% higher search lift than In-Stream only, according to the report.
  • Upload both horizontal and vertical video assets to take advantage of Shorts and other vertical viewing environments. Restricting creative to a single orientation limits inventory access and format efficiency.
  • Start Demand Gen with a minimum of nine creative assets: three horizontal videos, three vertical, and three square. This gives Google's AI sufficient variation to test and identify top performers before the campaign exits its learning phase.
  • Run an average of approximately two active Demand Gen campaigns per market. The deep-dive clients that saw the strongest results ran a mean of 2.2 campaigns per client market combination. Campaign consolidation concentrates conversion signal, which improves algorithm optimization.
  • Use Maximize Conversions as the default Demand Gen bid strategy when launching. It was used by 68% of deep-dive clients and by 55% of Fospha's top Demand Gen advertisers at launch. It does not require prior conversion volume thresholds, unlike Target ROAS.
  • Set Purchases as the primary Demand Gen campaign goal for eCommerce. Purchases accounted for 61% of total goal instances across program participants. Customer acquisition was second at 16%, followed by add to basket at 13%.
  • Maintain a minimum daily Demand Gen budget of approximately $130 per campaign. This is the floor referenced in the report for keeping the algorithm in an active learning state. Budgets below this level risk underdelivery and extended learning phases.
  • Limit bid adjustments to within 15% at a time. Larger changes can trigger an algorithm reset, restarting the learning phase and temporarily degrading performance. The 15% ceiling applies to Demand Gen bid strategy changes during active campaigns.
  • Lower to a maintenance budget rather than pausing Demand Gen spend. Pausing forces the algorithm to restart its learning phase. Reducing to a lower maintenance level preserves accumulated optimization data while managing costs.
  • Split Demand Gen campaigns into Prospecting and Retargeting at the ad group level, rather than running both in a single campaign. This gives the algorithm clearer objectives per ad group and enables separate budget management and performance evaluation.
  • Use Customer Match lists to build Lookalike Segments in Demand Gen. Lookalike targeting extends reach to users sharing characteristics with the existing customer base, improving audience quality beyond manual interest or demographic targeting.
  • Enable optimized targeting in Demand Gen to allow Google's system to find high-value users beyond manually selected audiences. This was cited in the report as part of Google's 2026 guidance for Demand Gen campaign setup.
  • For VRC, start audience targeting with Affinity or Demographic audiences at the upper-funnel stage. For VVC, use In-Market or Custom Audiences to reach users with demonstrated interest in the product category. Create remarketing lists from VRC and VVC exposure and use them in performance-focused campaigns downstream.
  • Apply a two-phase budget strategy during peak periods. Build Demand Gen and YouTube investment in the weeks before peak to create warm audiences, then shift emphasis toward PMAX and Brand Search capture during peak trading days. Derek Rose applied this approach in Q4 2025, ending with Demand Gen at 7% of the Google mix and achieving 44% higher overall ROAS year-over-year.

Timeline

Summary

Who: Fospha, a marketing measurement company, in collaboration with Google. The program involved 25 retail eCommerce brands across fashion, beauty, and consumer goods, spanning 28 market deployments. Results were measured against a matched control group of comparable Fospha advertisers.

What: The Full-Funnel Google Report presents findings from a structured Q4 2025 program measuring the impact of full-funnel Google investment on ROAS and CAC. Three primary findings: adding one new Google channel produced 14% higher ROAS, adding two produced 37% higher ROAS; allocating 10-20% of Google budget to Demand Gen doubled ROAS versus a 0-5% allocation; and scaling Demand Gen and YouTube spending improved Performance Max ROAS by 8% and Brand Search ROAS by 9% year-over-year for the program group, while the control group's Brand Search ROAS declined 17%.

When: The program ran from October 29 to December 16, 2025, with a formal analysis window covering November 1 to December 31, 2025. The report was published in 2026.

Where: The program covered 28 market deployments across retail eCommerce brands operating primarily in fashion, beauty, and consumer goods. Individual case studies include UK and French market deployments from Finisterre, Derek Rose, and Corston Architectural Detail.

Why: Most retail brands operating on Google concentrate their budgets in Performance Max and Brand Search, channels that capture existing demand. Last-click attribution makes it difficult to measure the downstream contribution of Demand Gen and YouTube, leading brands to under-invest in channels that create the demand those lower-funnel campaigns later capture. The report presents a controlled study showing a significant efficiency and revenue gap between brands that diversify their Google channel mix and those that do not.

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