Top 5 Pain Points in Marketing Budget Allocation (and How to Fix Them)

Marketers have more performance data than ever, yet trust in that data isn’t really improving.

Key Takeaways

Marketing pain points and fixes:

• Unclear ROI: Platform metrics often fail to show true business value.

  • Fix: Use Marketing Mix Modeling (MMM) to measure incremental revenue and ROI that Finance trusts.

• Data Silos: Fragmented data prevents holistic measurement.

  • Fix: Align spend and outcomes into a unified MMM view to reveal hidden interactions and blind spots.

• Competing Metrics: Teams fight for budget using isolated KPIs (e.g., ROAS vs. Brand Lift).

  • Fix: Adopt MMM as a "common currency" to optimize the entire portfolio based on incremental impact.

• Guesswork Forecasting: Planning often relies on static spreadsheets.

  • Fix: Use MMM response curves to accurately simulate "what-if" budget shifts and saturation levels.

• Attribution Debates: Stakeholders argue over what drove results.

  • Fix: Use MMM to scientifically decompose baseline demand vs. marketing drivers, creating a single source of truth.

The Marketing Performance Gap Is Astonishing

Recent research from TransUnion and eMarketer shows that marketers’ confidence in measurement has stalled, even as pressure to prove ROI keeps rising. Around 60% say internal stakeholders question their metrics at least sometimes, and nearly a third report that up to 20% of their marketing budgets have been reallocated or put at risk due to doubts about measurement accuracy.

At the same time, Nielsen’s recent Marketing ROI work shows a clear gap between confidence and actual practice: about 85% of marketers say they’re confident measuring ROI, but only ~32% actually do it holistically across traditional and digital media.

So Marketing and Finance often agree on one thing:

“We’re spending a lot on marketing. We’re not sure it’s going to the right places.”

Below are five recurring pain points we see in budget allocation, and how Marketing Mix Modeling (MMM) can help — including where a platform like Kairos fits in the overall stack.

Pain Point No. 1: “We spend a lot, but don’t know what we really get back”

Budget goes into Google, Meta, LINE, TV, influencers, CRM, affiliates…Ad platforms report strong CTR, conversions and “ROAS”, but Finance still asks:

• “How much incremental revenue did all of this actually generate?”

• “If we cut this channel by 20% next year, what happens to sales and profit?”

The problem is not that platform metrics are “wrong”; they are simply local metrics. They optimally describe performance inside each walled garden, not the full P&L impact.

How MMM helps

MMM estimates the incremental contribution of each channel to your KPI (revenue, orders, leads…), while controlling for promotions, seasonality, distribution and macro factors.

Nielsen’s work with TikTok and other partners describes MMM as a long-established, aggregated, privacy-safe standard for measuring efficiency and effectiveness across channels over the last 30+ years.

Practically, you move from:

• “This campaign generated 1,000 conversions.”

to:

• “At last year’s spend level, this channel generated X incremental revenue and Y ROI.”

That’s the language Finance can put into forecasts, margin analysis and capital allocation.

Pain Point No. 2: Fragmented data that never quite lines up

Most organizations don’t suffer from a lack of data — they suffer from data that doesn’t line up:

• Media spend and impressions live in separate platform UIs

• Sales, margin and product mix sit in finance and BI systems

• Promotions, pricing, inventory and macro indicators live somewhere else entirely

Nielsen’s own reporting calls out fragmented tools and siloed data as a key reason many marketers overestimate their ability to measure ROI: when only part of the mix is measured together, hidden interactions and blind spots remain.

How MMM helps (and where Kairos sits in your stack)

MMM forces everyone to work from a shared, time-aligned view:

• Spend and impressions by channel / tactic

• Business outcomes (revenue, orders, applications, leads)

• Control variables: promos, holidays, distribution, competition, macro trends

Here’s the important nuance to keep in mind:

MMM and Kairos don’t replace your data warehouse or existing ETL. They sit on top of that stack.

In most engagements:

• Your BI / data teams own extraction, cleaning and joining across sources.

• Kairos provides schemas, validation checks and model-ready templates so that once your data is aligned at the weekly or daily level, it can flow into MMM with minimal friction.

So instead of saying “our product can’t clean and align data”, you can frame it as:

• Kairos assumes a certain level of data readiness,

• then turns that work into cross-channel, Finance-grade measurement and planning, rather than leaving it trapped in disconnected dashboards.

Pain Point No. 3: Channel teams fighting for budget with different metrics

Inside budget meetings, you often hear:

• “Search has the best ROAS — we should shift budget there.”

• “TV builds long-term demand — last click under-values it.”

• “CRM and LINE keep customers returning — don’t cut us.”

Each team uses its own KPI, attribution window and narrative. The discussion turns into metric lobbying, not portfolio optimization.

Nielsen’s Marketing ROI reports and related commentary highlight how over-investing in short-term performance channels and under-investing in brand can actually reduce total ROI — even when each channel’s dashboard looks “good” in isolation.

How MMM + Kairos helps

MMM puts everything on a common currency: incremental business impact:

• ROI per channel (or per tactic) on the same definition

• Diminishing returns / saturation curves, not just marginal CPA

• The ability to ask: “Given our target, where does the next dollar work hardest?”

With a platform like Kairos, that’s not just a slide from the data science team. It becomes a shared interface where Marketing and Finance can explore the same curves and stress-test the same assumptions.

Budget conversations shift from “my metric vs your metric” to “what mix maximizes total ROI under our constraints?”

Pain Point No. 4: No reliable ways to forecast “what if we change the mix?”

Planning cycles are full of hypothetical questions:

• “What if we move 10–15% out of TV into digital?”

• “Can we defend holding budget flat and still hit a higher revenue target?”

• “What does a ‘resilient’ mix look like in a shaky economy?”

Without a proper model, these become Excel scenarios with hidden assumptions. Everyone leaves with different mental models of what will actually happen.

MMM solves this by learning response curves for each channel:

• How much incremental outcome you get as you increase spend

• Where the curve starts to flatten (saturation)

• How channels interact (e.g., TV priming search, TikTok amplifying TV, CRM amplifying paid)

TikTok’s MMM meta-analysis with Nielsen for CPG brands in Southeast Asia, for example, quantified how TikTok contributed to full-funnel impact and showed strong ROAS and incremental sales when combined with other media, rather than evaluated in isolation.

How MMM + Kairos helps

Kairos packages those curves into scenario tools:

• “If we cut Channel A by 10% and reinvest into Channel B, what happens to revenue and ROI?”

• “What mix hits our revenue target at minimum cost?”

• “What mix maximizes profit subject to a budget cap?”

Instead of debating whose Excel is “more realistic”, teams can interrogate one shared model, with assumptions that are explicit and adjustable.

Pain Point No. 5: Endless cross-department debates about “what really drove results”

When performance is strong, everyone wants credit.

When it’s weak, narratives multiply:

• “It’s the economy; nothing would have worked.”

• “It was creative fatigue, not budget.”

• “Ops couldn’t handle the demand; the campaign was fine.”

TransUnion’s recent research shows that many marketers feel their measurement confidence is flat or slipping, and that internal skepticism is directly putting budgets at risk.

How MMM + Kairos helps

MMM won’t eliminate all disagreement, but it does three important things:

1. Decomposes outcomes into baseline (what would have happened anyway) vs marketing-driven.

2. Attributes relative contribution to different channels and non-media drivers (price, promo, distribution, macro).

3. Makes assumptions and uncertainty explicit — you can see intervals, diagnostics and model fit, instead of pretending the world is deterministic.

From a governance perspective, that’s crucial: rather than arguing from separate dashboards, stakeholders debate one documented model, backed by a methodology that regulators and auditors increasingly recognize for aggregated, privacy-safe measurement.

Kairos’ role is to make that model usable and explainable to non-data-scientists: surfacing contributions, intervals and “what-if” scenarios in a way that supports board-level and budget-level decisions.

Where MMM and Kairos fit in your roadmap

Industry signals from TransUnion, eMarketer, Nielsen and major platforms all point in the same direction:

• More focus on incremental ROI and business outcomes, not vanity metrics.

• More holistic measurement across channels, rather than isolated dashboards.

• Renewed interest in MMM as a privacy-safe, data-agnostic backbone for budget planning in a fragmented, post-cookie environment.

In that landscape:

• Your data warehouse / BI stack remains the system of record and integration.

• MMM provides the statistical engine that converts that data into cross-channel incrementality and response curves.

• Kairos is the product layer that operationalizes this: templates, modeling, diagnostics, and decision tools that both Marketing and Finance can work with.

Call to Action

If you recognize these pain points — budget debates, siloed metrics, limited forecasting — a useful next step isn’t a big bang project. It’s a lightweight “MMM readiness” conversation:

• What data and granularity do you already have?

• Which budget decisions are most painful or political today?

• Where could a shared, Finance-grade MMM model (via Kairos) plug into your existing planning cycle?

From there, it becomes much easier to decide whether MMM is the right lever now, and what a realistic first 90 days would look like.

Sources

1. TransUnion & eMarketer – trust and confidence in marketing measurement

• “New TransUnion Research Reveals Marketers’ Confidence in Measurement Has Stalled” (GlobeNewswire / TransUnion, Oct 2025).

• “Emergency Rehab: Why Rebuilding Trust in Marketing Measurement Matters” (TransUnion blog, Oct 2025).

2. Nielsen – ROI confidence vs holistic measurement

• “Maximizing ROI in a Fragmented World – Annual Marketing Report” (Nielsen, 2024).

• “Nielsen Unveils Marketing ROI Blueprint” and related coverage showing 85% confidence but only 32% holistic ROI measurement.

3. Nielsen & TikTok – MMM case studies

• “TikTok SEA CPG MMM 2021 Study / Southeast Asia: CPG Marketing Mix Modeling Meta Analysis” (Nielsen + TikTok).