An Analytic Edge study using Marketing Mix Modeling in the Philippines suggests that several fast-moving consumer goods (FMCG) brands may be allocating advertising budgets in ways that do not fully align with measurable sales contribution.
The analysis, presented during an industry discussion hosted by adobo Magazine, examined 11 FMCG brands to assess how different media channels contribute to actual revenue performance.
At a time when marketing budgets face heightened scrutiny and finance teams demand clearer accountability, the findings point to a widening gap between historical allocation practices and modeled return on investment (ROI).
While the study centers on media planning, its implications extend into capital allocation and enterprise analytics — areas increasingly relevant to CFOs and financial decision-makers overseeing growth investments in 2026.
ROI performance and budget allocation diverge
Across approximately 70% of the Marketing Mix Models analyzed, TikTok delivered the highest ROI among modeled media channels. The average ROI across the dataset was approximately 2.2 times the investment.
In Consumer Packaged Goods comparisons, modeled ROI reached roughly 2.42x and, in certain cases, up to 4.7 times that of other media channels. Within the food and beverage segment, TikTok’s ROI was estimated at approximately 1.7 times that of total media.
Despite these results, TikTok accounts for only about 5% to 6% of total FMCG media spend within the dataset.
Television, by contrast, continues to command more than 70% of FMCG media allocation in the modeled sample, even as consumption trends shift. The persistence of high television allocation suggests that legacy planning frameworks — rather than marginal return analysis — may still influence budget distribution.
For companies operating under tighter financial oversight, this divergence between modeled performance and capital allocation raises a structural question: are investment decisions proportionate to measurable revenue impact?
Media sufficiency and the cost of underinvestment
A central concept introduced in the study is “media sufficiency,” defined as investing at a level where a channel delivers consistent and meaningful incremental sales impact.
Rather than spreading budgets thinly across multiple platforms to maintain presence, sufficiency-based planning seeks to identify the threshold at which incremental returns stabilize — and when diminishing returns begin to set in. The objective is scale optimization rather than simple diversification.
The modeling indicates that, in certain cases, investment levels could increase by up to 160% of current spend before performance begins to taper. For the FMCG brands included in the dataset, modeled sufficiency ranges corresponded to approximately 38 million to 144 million impressions per month.
This suggests that underinvestment — not necessarily channel inefficiency — may be limiting observable sales contribution in some cases. When spending remains below modeled sufficiency thresholds, performance curves may not fully develop, potentially distorting ROI comparisons.
In financial terms, underfunding a high-performing asset can suppress returns and create the appearance of weaker performance than is achievable at optimal scale.
Incremental reach and cross-channel effects
The study also evaluated audience duplication between digital video platforms and traditional television. Overlap between TikTok and linear TV was estimated at approximately 48% to 49%, indicating that more than half of TikTok exposure reaches audiences not fully duplicated by television.
When both channels were deployed together, modeling showed an incremental awareness lift of approximately 24.6%.
From an allocation perspective, this reflects additive reach rather than redundant spending. In fragmented media environments, incremental exposure becomes a growth lever — provided funding aligns with modeled contribution and sufficiency thresholds.
The findings suggest that a cross-channel strategy may require dynamic rebalancing instead of fixed historical splits.
Marketing mix modeling and financial discipline
Marketing Mix Modeling (MMM) in the Philippines is increasingly intersecting with enterprise analytics and financial governance. MMM uses econometric techniques to estimate the incremental sales impact of marketing activities while controlling for external factors.
As analytics adoption deepens and CFO oversight intensifies, marketing allocation decisions are becoming more closely tied to measurable marginal return.
The study does not prescribe immediate budget shifts. Instead, it underscores the importance of aligning investment levels with incremental return curves and of testing scaled deployment before concluding that a channel underperforms.
For Philippine FMCG brands entering 2026, the broader issue may not be platform selection but proportionality. If modeled contribution and capital allocation diverge, efficiency gaps can emerge — particularly in environments where every peso is scrutinized.
As financial accountability frameworks mature, marketing strategy is increasingly evaluated through the lens of capital optimization. In that context, MMM becomes less a reporting tool and more a decision architecture for disciplined growth.
