The Best Marketing Budgeting and ROI Platforms in 2026: A Practical Buyer's Guide

Marketing budgets have been flat at 7.7% of company revenue for two consecutive years. Meanwhile, 59% of CMOs say they lack sufficient budget to execute their strategy, and 63% cite budget and resource constraints as their top challenge for 2026. Yet 99% of CMOs say GenAI is a current priority, meaning new technology investments must come from existing budget -- not new dollars.

The math is unforgiving: flat budgets plus rising expectations equals an urgent need to prove exactly where every dollar goes and what it returns. According to The CMO Survey (Spring 2025), pressure from the board to prove marketing's value rose 21% between 2023 and 2025, with 63% of marketers now feeling increased pressure from the CFO specifically. And Forrester predicts that B2B marketing measurement confidence will slip another 7% in 2026 as AI-driven analytics introduce new transparency concerns.

This is where budgeting and ROI platforms come in. Not the generic project management tools that show up on every "top 10" list, but purpose-built platforms that help marketing teams plan spend, measure incremental impact, and reallocate in real time. This guide covers the platforms that actually matter, organized by what they do, what they cost, and who they are built for.

Why Spreadsheets Are Costing You More Than You Think

Before we get into platforms, it is worth understanding why the status quo fails. Most marketing teams still manage budgets through some combination of spreadsheets, slide decks, and tribal knowledge. According to HubSpot's 2026 State of Marketing, 40% of marketing teams still rely on spreadsheets for tracking and reporting. The problems are well-documented:

• Error rates are staggering. Research has consistently found that roughly 88-94% of spreadsheets contain errors, and the errors compound when multiple people are editing simultaneously across tabs, versions, and copies.
• Reconciliation eats time. Marketing teams using spreadsheets spend hours each week reconciling data from ad platforms, CRM, and marketing automation tools. That is time not spent optimizing campaigns.
• No real-time visibility. By the time a spreadsheet-based budget report reaches the CMO, the data is already stale. You cannot reallocate spend mid-quarter if you do not know what is working until the quarter is over.
• Attribution is impossible. Spreadsheets can track what you spent. They cannot tell you what that spend actually produced in pipeline or revenue -- a problem that compounds as buying committees grow larger and journeys span more touchpoints.

Adding to the problem: Gartner reports that marketing teams utilize just 33% of their martech stack capabilities, down from 58% in 2020. That means the tools you already own are likely underperforming -- which raises the stakes for choosing and properly implementing any new platform.

The solution is not just "get a better tool." It is understanding that marketing budgeting, ROI measurement, and attribution are three distinct problems that sometimes overlap but often require different platforms.

The Three Categories of Marketing ROI Platforms

Most listicles lump together wildly different tools. A project management app with a budget column is not the same as an analytics platform or a marketing mix model. The MPM software market alone is worth $574M in 2025 and growing at 6.5% CAGR -- but that only represents one of three categories you should understand.

Category 1: Marketing Performance Management (MPM)

These platforms centralize budget planning, spend tracking, and performance reporting. They are the "system of record" for marketing finance. Think of them as ERP for marketing.

Best for: Enterprise marketing teams (50+ people) that need to align budgets to strategy across regions, business units, and channels, and report results to the CFO's office.

Category 2: Marketing Attribution and Analytics

These platforms answer "which campaigns, channels, and touchpoints drove pipeline and revenue?" They connect marketing activity to business outcomes using multi-touch attribution, lift modeling, or both. This is especially critical for B2B teams where complex buying journeys make last-touch attribution nearly meaningless.

Best for: B2B and B2C growth teams that need to understand which marketing investments are actually driving results, not just generating clicks.

Category 3: Marketing Mix Modeling (MMM)

These platforms use statistical models to quantify the incremental impact of each marketing channel on business outcomes, even when individual-level tracking is impossible (think TV, podcast, out-of-home, or privacy-restricted digital). MMM has seen a resurgence: a Google-commissioned Kantar study found 60% of US advertisers are currently using MMMs, and 58% of those not using them are actively considering it.

Best for: Brands spending $5M+ annually across a mix of digital and traditional channels, especially those affected by cookie deprecation and privacy regulations.

Some platforms span multiple categories. But understanding which problem you are solving first prevents you from buying a $100K attribution platform when you actually need a $6K budgeting tool (or vice versa).

The Platforms Worth Evaluating

Below are the platforms that consistently appear in Forrester, Gartner, and G2 evaluations, organized by category. I have included real pricing where available and noted where pricing is custom or enterprise-only.

Marketing Performance Management

1. Uptempo (formerly Allocadia + BrandMaker + Hive9)

Uptempo is the result of three acquisitions: Allocadia (budgeting), BrandMaker (workflow and execution), and Hive9 (analytics), unified under a single brand in 2022. It is the closest thing the market has to a comprehensive marketing operations suite.

• What it does: Centralized budget planning with real-time spend tracking, predictive impact modeling, campaign-to-revenue attribution, workflow automation, and asset management. Direct integrations with ERP and digital ad platforms allow mid-flight budget reallocation without manual uploads.
• Who uses it: 625,000+ marketers at 400+ enterprises including Autodesk, Best Buy, Daimler, Deutsche Bank, SC Johnson, and Unilever.
• Pricing: Custom enterprise pricing. Expect $50K-$200K+ annually depending on modules and team size.
• Best for: Enterprise marketing orgs that need a unified system of record for planning, budgeting, and performance management.

2. Planful for Marketing (formerly Plannuh)

Planful started as a financial planning and analysis (FP&A) platform and expanded into marketing with its acquisition of Plannuh. The marketing module connects campaign budgets and goals to the broader financial planning process, which makes it particularly strong for marketing-finance alignment.

• What it does: AI-driven budget automation, campaign planning and tracking, goal-to-budget alignment, integration with ERP and CRM systems, collaborative forecasting and reporting.
• Pricing: Starts at approximately $6,000/year for the marketing module. Mid-market companies typically pay $15K-$25K/year, with enterprise FP&A suite pricing custom.
• Best for: Mid-market to enterprise teams that want marketing budgeting tightly integrated with company-wide financial planning, especially if finance already uses Planful.

3. MARMIND

MARMIND is a marketing resource management platform built for global enterprises that need to coordinate budgets, campaigns, and results across multiple markets and business units.

• What it does: Advanced budgeting tools, real-time performance analytics, customizable dashboards, campaign planning across markets, integration with Salesforce, Dynamics 365, Power BI, Google Analytics 360, and Jira.
• Who uses it: Mercedes-Benz, Lufthansa Group, Springer Nature.
• Pricing: Four tiers from $1,200 to $3,500/month. The Business plan suits smaller teams; Professional adds monitoring and customization; Enterprise includes full budget and cost management. No free trial.
• Best for: Global marketing teams managing budgets across multiple regions and brands.

Marketing Attribution and Analytics

4. HockeyStack

HockeyStack has quickly become one of the most talked-about platforms in B2B attribution. It unifies marketing, product, and sales data into a single GTM data layer, then applies multi-touch attribution and AI-powered analytics on top.

• What it does: Full buyer journey tracking, multi-touch attribution and lift modeling, account-level intent signals, no-code funnel and cohort reporting, an AI analyst ("Odin") for natural-language queries, and a sales assistant ("Nova") for account intelligence.
• Who uses it: 8x8, DataRobot, AppsFlyer, Rakuten, RingCentral, LaunchDarkly, MasterCard.
• Pricing: Starts at approximately $2,200/month with usage-based scaling; median contract is around $28K/year. Enterprise plans are custom. Startup pricing available.
• Best for: B2B SaaS marketing and revenue teams that need to connect marketing spend to pipeline and revenue across complex buying journeys.

5. Dreamdata

Dreamdata automatically collects, models, and activates B2B go-to-market data, providing revenue attribution across the full customer journey from first anonymous touch to closed-won deal.

• What it does: Automated data collection from CRM, marketing automation, ad platforms, and web analytics. Multi-touch attribution, account-based analytics, content performance measurement, and audience activation for ad targeting.
• Pricing: Free tier available. Activation Starter at $750/month (billed annually). Advanced Attribution and Activation plans are custom based on data volume.
• Best for: B2B companies with longer sales cycles that need to attribute revenue to content, campaigns, and channels across multi-month buying journeys. Works well alongside ABM tools for account-level spend analysis.

6. Funnel.io

Funnel is a marketing data hub that automatically collects, normalizes, and routes data from 600+ marketing and advertising platforms into your data warehouse, BI tools, or dashboards.

• What it does: Automated data collection from ad platforms, analytics tools, CRMs, and e-commerce systems. No-code data transformation and normalization. Export to Looker Studio, Tableau, Power BI, BigQuery, Snowflake, and Redshift.
• Who uses it: Home Depot, Havas Media, Samsung, and 2,000+ other companies.
• Pricing: Three plans based on "flexpoints" -- Starter ($1.20/flexpoint/month), Business ($1.50), and Enterprise ($2.00), with a 400-flexpoint minimum. That sets the floor at $480/month. Average contract is $73,500/year per Vendr data, though large implementations can exceed $1M annually.
• Caveat: Multiple reviewers note that costs can spike unpredictably as you add connectors, breakdowns, and destinations. Understand flexpoint economics before committing -- request a usage projection for your specific stack.
• Best for: Marketing teams and agencies that need a clean data pipeline from dozens of ad platforms into a central analytics layer, especially if you already have a BI tool like Looker or Tableau.

7. Singular

Singular unifies cost, revenue, and attribution data across hundreds of ad networks. Originally built for mobile marketing attribution, it has expanded into cross-channel cost aggregation and ROI analytics.

• What it does: Cross-channel cost aggregation, deterministic and probabilistic attribution, SKAdNetwork support, fraud prevention, ROI and LTV analytics, custom attribution models, and cross-device attribution.
• Who uses it: LinkedIn, Lyft, Warby Parker, Rovio.
• Pricing: Free plan with limited features. Custom pricing for growth and enterprise tiers based on data volume.
• Best for: Mobile-first and performance marketing teams that need to aggregate cost data across many ad networks and tie it to revenue.

Marketing Mix Modeling

MMM has gained significant institutional recognition. The 2025 Gartner Magic Quadrant for Marketing Mix Modeling Solutions (published November 2025) named Analytic Partners, TransUnion, and Ipsos MMA as Leaders. On the SaaS side, here are three platforms worth evaluating:

8. Google Meridian

Google Meridian is an open-source marketing mix modeling framework built on years of Google's internal MMM research. It launched broadly in 2025 and represents a significant shift in making MMM accessible beyond Fortune 500 companies.

• What it does: Bayesian marketing mix modeling with reach and frequency integration (not just impressions), calibration against incrementality experiments, performance media measurement (including Search), non-media variable support (pricing, promotions), marginal ROI priors, and full code transparency.
• Ecosystem: 30 certified global partners trained on Meridian implementation, plus an active Discord community for technical support. Integration with Google Marketing Data Platform streamlines data processing.
• Pricing: Free and open-source. Requires data science resources to implement and maintain.
• Caveat: "Free" is relative. You need a data team comfortable with Python and Bayesian statistics. Implementation costs are in data science time, not software licenses.
• Best for: Data-mature marketing organizations with in-house data science teams that want full control over their MMM methodology. Google's position is that open-source MMM builds more trust than black-box vendor models.

9. Keen Decision Systems

Keen provides an AI-powered marketing mix modeling platform that lets marketers run scenario-based planning without requiring a data science team. Named a Niche Player in the 2024 Gartner Magic Quadrant for MMM Solutions.

• What it does: Bayesian MMM that adapts over time, scenario planning ("what happens if I cut budget 15%?"), forward-looking optimization by channel and week, and industry benchmarking built from $42 billion in spend data across 400+ brands.
• Pricing: Annual subscription with transparent pricing (contact for quote). Keen offers a free 14-day trial with full platform access. Customers report an average 25% lift in marketing effectiveness in year one.
• Best for: Mid-market brands spending $5M+ on marketing that want MMM insights without building an internal data science team.

10. Paramark

Paramark is a newer entrant that combines marketing mix modeling with incrementality testing in a single platform, backed by $8M in funding (Greylock-led seed round with angel investors including former CMOs from Dropbox, Salesforce, and Amazon). Used by brands like Square, ClickUp, Speak, and Chime.

• What it does: Unified MMM and incrementality testing, causal experimentation design, channel-level incremental impact measurement, growth advisory. Analyzes over $1.5 billion in marketing investments.
• Pricing: Custom pricing. Contact for a quote.
• Best for: Growth-stage and mid-market brands that want to combine modeled insights (MMM) with experimental proof (incrementality) in one platform, rather than stitching together separate tools.

Honorable Mentions: Budget-Friendly Starting Points

Not every team needs a six-figure platform. If you are a smaller team or just starting to formalize your budgeting process, these options provide real value at lower cost:

• ClickUp: Marketing budget templates with ROI prioritization fields, campaign tracking, and goal alignment. Free plan available; paid plans start at $7/user/month.
• Smartsheet: Spreadsheet-database hybrid with marketing budget templates, automated workflows, and stakeholder dashboards. Starts at $9/user/month.
• Rows: AI-powered spreadsheet with built-in integrations to ad platforms and analytics tools. Free tier available.

These are not dedicated ROI platforms, but they are a major step up from raw spreadsheets and can serve as a bridge until your team's budget justifies a purpose-built solution.

How to Choose: A Decision Framework

With ten platforms spanning three categories, the selection process can feel overwhelming. Here is a framework that cuts through the noise:

Step 1: Define Your Primary Problem

Be honest about which problem is most urgent:

• "We cannot track what we are spending." You need an MPM platform (Uptempo, Planful, MARMIND) or a structured project management tool (ClickUp, Smartsheet).
• "We do not know which campaigns drive revenue." You need an attribution platform (HockeyStack, Dreamdata) or a data pipeline (Funnel, Singular). If your outbound metrics are strong but you cannot attribute pipeline to specific campaigns, start here.
• "We cannot prove marketing's incremental impact." You need MMM (Meridian, Keen, Paramark).

Step 2: Assess Your Data Maturity

The most common reason ROI platforms fail is not the software -- it is the data going into it. Before evaluating platforms, audit your readiness:

• Basic: You have ad platform accounts and a CRM, but no consistent UTM taxonomy or data warehouse. Start with Funnel or a structured spreadsheet tool. Also consider data enrichment platforms to clean up your foundation.
• Intermediate: You have a data warehouse, consistent tracking, and a BI layer. You are ready for HockeyStack, Dreamdata, or Planful.
• Advanced: You have a data team, experiment infrastructure, and cross-functional alignment between marketing and finance. You are ready for Uptempo, Meridian, Keen, or Paramark.

Step 3: Map Budget to Category

Step 4: Run a 90-Day Proof of Value

Do not sign a multi-year contract based on a demo. Most platforms on this list offer trials or pilots. Structure your evaluation:

1. Days 1-30: Connect data sources and establish baseline metrics. Document what you can and cannot measure today.
2. Days 31-60: Run the platform in parallel with your current process. Compare insights, speed, and accuracy.
3. Days 61-90: Present findings to finance. If the platform identified at least one reallocation opportunity that improved results, you have your business case.

The AI Layer: What Is Real and What Is Hype

Nearly every platform on this list now markets AI capabilities. Forrester warns that B2B companies will lose more than $10 billion in 2026 from ungoverned use of generative AI, which applies to measurement tools as much as content creation. Here is what is genuinely useful versus what is marketing theater:

Useful AI Applications

• Anomaly detection: Flagging when a campaign's cost-per-acquisition suddenly spikes or a channel's contribution drops. This is well-established and works reliably.
• Scenario modeling: Running "what if" simulations faster and across more variables than manual analysis. Keen and Paramark both do this well.
• Natural-language querying: Asking "what was our most efficient channel last quarter?" instead of building a report. HockeyStack's Odin AI is a strong example.
• Automated data normalization: Reconciling different naming conventions and data formats across platforms. Funnel's core value proposition. If you are also evaluating predictive analytics tools, look for platforms that can share normalized data across your stack.

AI Hype to Question

• "AI-powered budget optimization" that automatically reallocates spend without human oversight. The models are not good enough for fully autonomous budget decisions yet. Use AI for recommendations; keep humans in the approval loop.
• "Predictive ROI" that claims to tell you exactly what a campaign will return before you launch it. Historical models help with directional estimates, but marketing does not happen in a vacuum. New creative, competitive shifts, and macro trends make precise prediction unreliable.

Forrester's recommendation for 2026 is to build a "measurement-centered culture" -- one where data-backed models provide guardrails, but teams use judgment to interpret and act on the signals. That is the right mental model for AI in marketing budgeting.

Making the Case to Finance

The hardest part of adopting a budgeting or ROI platform is often not choosing the tool -- it is getting budget approved to buy a budgeting tool. Here is how to frame the conversation for your CFO:

• Lead with the cost of the status quo. Quantify the hours your team spends on manual reporting, the lag time in budget decisions, and the last reallocation you made too late.
• Tie to CFO priorities. According to Gartner's 2026 CFO survey, the top three CFO priorities are cost optimization (56%), forecast accuracy (51%), and revenue growth (47%). A marketing ROI platform directly supports all three.
• Propose a pilot, not a purchase. Most of these platforms offer trials. Ask for 90 days and a modest budget to prove value before committing to a multi-year contract.
• Show, do not tell. One concrete example of "we discovered Channel X was 3x more efficient than Channel Y and reallocated $50K, generating an additional $150K in pipeline" is worth more than any vendor's ROI calculator.
• Frame around efficiency, not headcount. With 39% of CMOs planning labor and agency cuts, position the platform as a way to maintain output with fewer resources -- not as a new expense.

Where Signal Intelligence Fits In

Budgeting and ROI platforms tell you where to spend and what it returned. But they do not tell you who to spend it on. That is where signal-based selling and buyer intelligence come in.

The most effective marketing teams in 2026 are combining spend optimization with buyer intent signals to ensure budget is not just allocated to the right channels, but directed at the right accounts at the right time. Platforms like Autobound surface real-time signals -- hiring activity, competitive mentions, funding events, leadership changes -- that help marketing and sales teams focus their budget on accounts that are actually in-market, rather than spreading spend evenly across an entire TAM.

This is not a replacement for the platforms listed above. It is a complementary layer: use an MPM or attribution platform to manage budget and measure ROI, and use signal intelligence to improve the targeting precision of that budget. When your sales funnel is fed by real buying signals, even flat budgets can produce outsized results.

Key Takeaways

• Understand the three categories before you evaluate tools. Marketing Performance Management, Attribution, and Marketing Mix Modeling solve different problems.
• Match the platform to your maturity. A $100K Uptempo deployment will fail if your UTM taxonomy is broken. Start where your data is and grow from there.
• Budget stagnation makes measurement more important, not less. With 39% of CMOs planning labor and agency cuts and only 33% of martech stack capabilities being utilized, proving what works is no longer optional.
• AI is a useful accelerator, not a replacement for judgment. Use AI for anomaly detection, scenario modeling, and data normalization. Keep humans in the decision loop for budget allocation.
• Run a 90-day pilot. No vendor demo can substitute for seeing your own data in the platform. Structure a proof of value before signing a contract.
• Layer in signal intelligence. The best ROI comes from measuring spend and directing it at accounts showing real buying intent.