Sellforte MCP Is Now Generally Available: Bring MMM, Incrementality Testing, and Budget Optimization Into Your AI Workflows
Sellforte MCP is now in general availability, accessible to marketers worldwide, and has been rolled out to all Sellforte customers. All the capabilities of Sellforte are available through Sellforte MCP.
When we introduced Sellforte MCP in August, our goal was to make Sellforte's Marketing Mix Modeling, experiment data, and planning capabilities available inside the LLMs and AI workflows where marketers increasingly work. Instead of always opening Sellforte to analyze results, build scenarios, and find recommendations, marketers could bring Sellforte directly into AI assistants like Claude, ChatGPT, and Copilot.
Since then, we've expanded the capabilities available through MCP, including support for Sellforte Performance and Experiments. We've also seen early users develop new ways of working with their marketing data, from creating management reports to managing campaign optimization through AI.
With Sellforte MCP, marketers can now use their AI workflows to:
- Run incrementality testing workflows: Analyze geo lift, conversion lift, and A/B test results, and identify which experiments to prioritize next.
- Analyze Marketing Mix Modeling results: Understand what's driving incremental sales, investigate changes in performance, and compare channels and markets.
- Optimize budget allocation: Create Media Optimizer scenarios to identify how marketing budgets should be allocated across channels and markets.
- Optimize campaign-level spend: Identify opportunities to change budgets and bidding targets based on incremental performance, and understand the impact of previous changes.
All powered by Sellforte's independent incrementality measurement, directly inside your AI environment.
For Juha Nuutinen, CEO and Co-Founder of Sellforte, this represents a fundamental shift in how marketers will work.
"I use Sellforte MCP every day, and our Customer Success team is using it to analyze results, validate findings, and answer customer questions. We're not simply connecting marketing data to AI. We're bringing the intelligence behind incrementality measurement, budget allocation, and campaign optimization directly into the tools marketers already use. This is one of the most exciting things we've built at Sellforte, and I want every single customer to experience it."
-Juha Nuutinen, CEO and Co-Founder, Sellforte
The bigger opportunity goes beyond making marketing analysis easier. It's about giving AI agents the independent measurement they need to make better marketing decisions and take the correct action.
AI Agents Are Only as Good as the Measurement Data They Use
AI is quickly changing how performance marketers work. LLMs can connect to advertising platforms, analyze campaign performance, recommend budget changes, and increasingly help execute those decisions.
But there's an important problem. An AI agent optimizing your marketing based on the wrong measurement data can make bad decisions much faster.
Imagine asking your AI assistant to optimize your marketing budget. It connects to Google Ads, Meta, and TikTok, analyzes campaign performance, and identifies your highest-ROAS campaigns. Branded search and retargeting come out on top.
The AI recommends moving most of your marketing budget into those campaigns. When you ask it to double-check using Google Analytics, it finds that last-click attribution largely supports the same conclusion. So you make the changes.
A week later, your reported ROAS looks fantastic. But actual revenue is declining and new customer acquisition has slowed.
What went wrong?
The AI optimized for attributed revenue, not incremental revenue. Branded search and retargeting often receive credit for conversions that would have happened anyway. Meanwhile, prospecting campaigns and upper-funnel channels can generate incremental demand without receiving the same attribution credit.
The AI was good at analyzing the data available to it. The problem was that the underlying data couldn't reliably tell it what was actually driving incremental growth. Connecting more advertising platforms or combining different attribution models doesn't solve that fundamental problem.
AI can make sense of fragmented marketing data, but it cannot turn attribution into causal measurement simply by analyzing it.
This is why independent incrementality measurement is becoming more important as AI agents take on more marketing decisions.
Give Your AI Access to Independent Incrementality Measurement
Sellforte MCP brings Sellforte's measurement and optimization capabilities directly into compatible LLMs and AI agents.
MCP, or Model Context Protocol, provides a standardized way for AI applications to connect to external tools and data sources. With Sellforte MCP, your AI can access the independent marketing intelligence you use inside Sellforte, including MMM results, incrementality experiments, budget optimization scenarios, and campaign-level performance recommendations.
Instead of relying entirely on what advertising platforms claim to have generated, the AI can use Sellforte to understand what marketing actually contributed to the business. That includes incremental sales, incremental ROAS, marginal incremental ROAS (miROAS), and recommendations based on Sellforte's causal measurement and optimization models.
Because Sellforte measures performance across channels using a consistent framework, your AI can compare investment opportunities across Google, Meta, TikTok, and the wider marketing mix.
As Emil Kauppi-Hoyer, Lead AI Engineer at Sellforte, explains:
"AI agents are getting very good at analyzing marketing performance and recommending campaign changes. But without incrementality measurement, they're still making those decisions based on platform attribution. Sellforte MCP brings independent measurement into that workflow, so agents can make recommendations based on what actually drives incremental growth."
The distinction is important. Your LLM provides the conversation, reasoning, and workflow. Sellforte provides the underlying measurement intelligence.
That intelligence can now support everything from strategic planning and incrementality testing to daily campaign optimization.
Four Ways to Use Sellforte MCP to Improve Marketing Performance
Since our initial launch, we've been collecting practical examples of how marketing teams can use Sellforte MCP. Here are four core workflows, along with real questions marketers can ask their AI assistants.
1. Incrementality Testing: Understand What Worked and What to Test Next
"Which incrementality test should we run next?"
Incrementality testing is one of the most effective ways to understand whether marketing actually caused additional sales. But running experiments is only part of the challenge. Marketers also need to understand what previous tests revealed, how reliable those findings are, and where additional testing could improve their measurement.
Sellforte MCP brings these workflows into your AI assistant. You can access your experiment results, including geo lift tests, Meta Conversion Lift Studies, and A/B tests, and ask your AI to analyze the findings.
For example, you could ask:
"Did our latest Meta Conversion Lift Study validate our MMM results?"
Your AI can retrieve the relevant experiment data, examine the measured incremental impact, and help you compare the findings with your MMM.
You can also use Sellforte's Test Prioritizer to identify where new experiments could provide the most valuable evidence. Instead of reviewing your entire test library manually, you can ask which channels have limited testing coverage, where the largest uncertainties remain, and which experiment should be prioritized next.
This creates a more connected workflow between incrementality testing, MMM validation, and future marketing decisions.
2. MMM Analysis: Understand What's Really Driving Performance
"Why did our Direct Mail ROI drop last quarter?"
Marketing Mix Modeling provides an independent understanding of how different channels contribute to incremental sales. With Sellforte MCP, marketers can explore those results conversationally without manually moving between reports, charts, and different time periods.
For example, you could ask your AI to investigate why Direct Mail performance declined. Sellforte provides the MMM results, allowing the AI to examine changes in incremental sales contribution, media investment, and effectiveness over time.
You can continue the conversation, asking it to compare markets, identify other channels that improved or declined, and create visualizations to explain the findings.
Or you could ask:
"Which channels generated the most incremental sales over the last 12 months, and how has their ROI changed?"
Your AI can retrieve the relevant measurement results and explain which channels contributed most to growth. And because you're working inside your AI environment, you can combine these findings with other connected business data to investigate performance in greater depth.
The analysis is grounded in Sellforte's MMM, not simply in conversions attributed to each channel.
3. Budget Allocation: Optimize Where Your Marketing Investment Goes
"Where should we move budget mid-month?"
Budget decisions rarely happen under perfect conditions. A campaign might be underperforming, the CFO might request a 10% budget reduction, or a business might receive additional investment to support an important sales period.
With Sellforte MCP, marketers can ask their AI to create Media Optimizer scenarios using Sellforte's underlying MMM response curves.
For example:
"We need to reduce our marketing budget by 10% next quarter. How should we reallocate our investment to minimize the impact on incremental sales?"
Your AI can use Sellforte's Media Optimizer to create a scenario based on those constraints. Instead of simply reducing every channel by 10%, the optimizer evaluates how the available budget should be allocated to maximize incremental business impact.
The resulting scenario identifies where investment should increase or decrease and estimates the expected impact on incremental sales and ROI. You can then ask your AI to compare scenarios, explain the trade-offs, or prepare a recommendation for leadership.
The same workflow works when budgets increase:
"We've received another €500,000 for next quarter. Where should we invest it?"
Your AI can create a new optimization scenario to identify where that additional investment is expected to generate the strongest incremental returns. These scenarios are saved in your Sellforte environment for your team to review and work with.
4. Campaign Optimization: Know Which Campaigns to Change and Why
"Which Meta campaigns should we change first this week?"
One of the biggest developments since our original MCP launch is the addition of Sellforte Performance.
Previously, Sellforte MCP focused primarily on accessing MMM results, analyzing marketing performance, and creating Media Optimizer scenarios. Now, AI assistants can also access Sellforte's more granular performance intelligence.
That means marketers can analyze campaigns and ad sets, identify optimization opportunities, review recommended budget and bidding changes, and investigate the impact of previous changes.
For example, a performance marketer could ask:
"Which Meta campaigns should we scale, and where should we reduce spend?"
Instead of simply ranking campaigns by Meta's reported ROAS, the AI can retrieve Sellforte's campaign-level recommendations. Those recommendations are based on marginal incremental returns and can include specific budget or bidding changes, alongside their projected incremental business impact.
You can ask follow-up questions about individual campaigns, compare opportunities, and prioritize changes expected to deliver the greatest incremental return.
And after making those changes, the workflow continues:
"Did our budget changes pay off?"
Through Sellforte Performance and Change Intelligence, your AI can investigate previous changes, review the available change history, and examine how performance developed afterward.
This helps marketers connect the decisions they made with the results they achieved, bringing previous outcomes into future optimization decisions.
The objective is not to improve the ROAS reported by an advertising platform. It's to identify the changes most likely to generate additional incremental sales.
These are just a few examples. We've created a dedicated Sellforte MCP Use Case Library, with real questions marketers ask, example prompts, and explanations of what each workflow can deliver.
From Analysis to Action: Bringing Marketing Workflows Together
The bigger opportunity emerges when these different capabilities become part of the same workflow.
Imagine preparing your marketing plan for the next quarter. You start by asking your AI which channels generated the most incremental sales over the previous quarter. Then you explore your recent experiment results to understand which findings support the MMM, where uncertainties remain, and which additional tests would be most valuable.
Next, you ask your AI to create an optimized budget scenario for the next three months, including constraints on certain channels and markets.
Once you've agreed on your overall plan, you move to tactical execution. You ask which campaigns have the strongest opportunities to scale, which budgets or bidding targets should change, and what incremental impact those changes are expected to generate.
You review the recommendations and make the changes through your existing campaign management workflows. After the changes have been running, you return to your AI assistant to analyze what happened and identify the next opportunities.
This connects the different stages of marketing optimization:
Measure → Test → Analyze → Plan → Recommend → Act → Measure Again
Sellforte MCP makes measurement, experiment insights, analysis, planning, and performance recommendations available in AI workflows. Campaign execution can happen through Sellforte Activate or other connected advertising platform tools, depending on your setup. Sellforte MCP itself does not currently push campaign changes live.
This reflects an important shift in how we think about AI-powered marketing.
We don't believe every action needs to happen inside Sellforte. AI environments are increasingly becoming the interface where marketers bring together data, business context, recommendations, and execution tools.
Our role is to provide the independent measurement and optimization intelligence those workflows need.
Sellforte tells your AI what actually works, so it can help you decide what to do next.
How to Get Started With Sellforte MCP
Sellforte MCP works with Claude, ChatGPT, and other AI applications that support connecting to MCP servers.
To get started, contact your Sellforte Customer Success Manager or Sellforte contact to arrange your MCP access invitation. Once your access is enabled, you can add Sellforte as an MCP connector inside your supported AI application and authenticate using your Sellforte account.
If you are not yet a Sellforte customer, you can book a demo to see Sellforte MCP in action.
The specific capabilities available depend on the Sellforte modules included in your subscription. You don't need to manually export your data, configure individual Sellforte APIs, or know which specific MCP tool to call.
One of the easiest ways to get started is simply to ask your AI:
"What can you do with Sellforte?"
Your AI can discover the available Sellforte capabilities and help you explore them through natural language.
For step-by-step instructions, see our Sellforte MCP connection guide.
👉 Explore the Sellforte MCP Use Case Library
👉 Learn more about Sellforte MCP
The Future of Marketing Optimization Is Agentic and Incremental
AI agents are becoming increasingly capable of analyzing marketing data, recommending changes, and supporting campaign execution. But the quality of those decisions depends on the measurement behind them.
An agent optimizing against platform-reported ROAS can make the same mistakes as a marketer relying on attribution, only faster and at a much greater scale.
The next generation of marketing optimization needs something better. It needs independent, cross-platform measurement that identifies incremental business impact, experiments that validate what works, budget optimization that directs investment toward growth, and granular campaign recommendations that show where the next dollar should go.
That's what we're building with Sellforte. Our measurement intelligence can now become part of the AI workflows marketers already use, helping them make better decisions about where to invest, what to test, and which campaigns to optimize.
Sellforte MCP is now in general availability, available to all Sellforte customers, and included in their existing subscriptions at no additional cost.
Because the future of marketing isn't just about giving AI agents more data. It's about giving them the right data to make better decisions.
