What is BlueAlpha?
BlueAlpha is a system for continuously measuring, validating, and improving paid marketing decisions. It’s an AI action system designed to eliminate the gaps between measurement, analysis, and execution.
Most marketing stacks stop at reporting. BlueAlpha is designed to close the loop between measurement, decision making, and execution by integrating causal modeling, controlled experimentation, monitoring, and structured recommendations.
The system is built to answer one core question on a recurring basis:
What do I do next?
What is an Action System?
An action system is software designed to drive value in-market via ongoing decision making and execution rather than retrospective analysis alone. It closes the gap between insight and impact by embedding agentic intelligence into how teams operate day-to-day.
Growth teams typically face three structural limitations in paid marketing:
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Measurement drift where platform attribution diverges from true business impact
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Slow decision cycles where insights arrive too late to influence outcomes
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Execution gaps where insights are not translated into consistent action
BlueAlpha addresses these limitations with a single, agentic, full-stack marketing system that integrates measurement, monitoring, planning, and execution. Rather than surfacing insights in isolation, BlueAlpha is designed to help organizations drive growth at-scale: embedding agentic intelligence into their workflows, while keeping teams in control.
Marketing Mix Model
The Marketing Mix Model delivers a holistic, cross-channel view of how paid marketing drives business outcomes across both online and offline channels. Updated weekly, our MMMs provide consistently fresh and reliable information based on the latest available data, rather than quarterly or annual updates.
BlueAlpha builds marketing mix models using a Bayesian statistical framework designed for ongoing use rather than one time studies.
Modeling Approach
The modeling process evaluates multiple configurations across:
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Seasonality assumptions
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Advertising carryover and decay effects
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Channel specific response functions
Models are assessed using out of sample validation to reduce overfitting and ensure predictive reliability. Implausible or unstable models are excluded based on statistical and business constraints.
Results from Incrementality Testing are incorporated directly into the model as informed priors, allowing experimental evidence to improve attribution quality over time.
Outputs
The Marketing Mix Model essentially tells you what’s working:
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Channel level contribution with uncertainty bounds
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Marginal return curves and saturation points
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Estimates of baseline or non media driven performance
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Weekly contribution breakdowns
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Budget planning and forecasting scenarios
Models are retrained on a regular cadence to reflect changes in market conditions.
Incrementality Testing
The Incrementality Testing module is used to validate causal impact and reduce reliance on platform reported performance.
BlueAlpha supports geo based lift experiments designed to parse the impact of in-market strategy changes that can validate larger shifts in spend, while limiting risk.
Incrementality tests are used to:
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Validate or challenge model based conclusions
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Measure true incremental lift
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Assess new channels, creatives, or budget reallocations
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Reduce uncertainty in future planning
Tests are designed at the geographic level such as DMA, zipcode, state, region, or country and are integrated directly into the broader measurement system.
Detection Agents
The Detection Agents module provides continuous monitoring of marketing performance looking for anomalies and flagging issues.
Detection is designed to surface meaningful deviations early, before inefficiencies accumulate or performance degrades materially.
Detection Agents monitor for:
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Unexpected changes in spend or outcomes
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Efficiency degradation
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Creative performance decay
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Cross channel coordination issues
Alerts are contextualized using historical performance and model expectations to support faster diagnosis and response.
Budget Planner
The Budget Planner supports forward looking planning grounded in causal measurement rather than historical averages.
Using response curves and uncertainty estimates from the Marketing Mix Model, teams can:
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Compare efficiency and growth tradeoffs
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Identify where additional spend is likely to encounter diminishing returns
Budget planning is directly linked to observed performance dynamics and incrementality evidence.
Recommendation Engine
The Recommendation Engine translates measurement and monitoring into structured guidance. Powered by context-aware LLMs and agents, recommendations are tailored to your business context, reflecting your goals, constraints, channel strategy, and operating model, so all guidance is directly relevant and actionable.
Recommendations are generated at the campaign level and focus on:
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Where spend should be increased
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Where spend should be constrained or reduced
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How budgets should be reallocated across channels or campaigns
The Recommendation Engine is designed to support a consistent weekly operating cadence, enabling faster, more confident decision-making, while reducing reliance on ad hoc analysis.
Chat With Your Data
The Chat With Your Data module provides access to a unified, natural language interface to the full BlueAlpha system.
It allows users to interact directly with underlying data, models, assumptions, and outputs without requiring manual analysis or custom queries. The interface has access to platform data, first party data, marketing mix models, incrementality test results, and system generated recommendations.
Users can use natural language to:
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Surface and explore raw and aggregated data across platforms and internal sources
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Inspect model outputs, uncertainty bounds, and methodological assumptions
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Generate and iterate on analyses and reports
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Evaluate alternative budget or execution scenarios in real time
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Review and refine recommendations before execution
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Trace how conclusions are derived from data and models
The interface is grounded in the system’s methodological documentation, ensuring responses reflect the same definitions, constraints, and assumptions used throughout BlueAlpha.
By providing a shared, interactive layer across data, measurement, and decisions, Chat With Your Data enables marketing, finance, and leadership teams to ask and answer complex questions consistently, without translation loss or delays.
Activity Log
The Activity Log provides a consistent record of decisions, recommendations, and actions taken within the system.
The Activity Log captures:
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Model updates and material changes in attribution
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Recommendations issued by the system
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Budget changes and execution decisions
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Notes or context added by users
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Outputs from detection agents
This creates an auditable history of why decisions were made, what evidence supported them, and how performance evolved over time.
The Activity Log is designed to improve accountability, institutional memory, and analysis of decision quality.
Built to Drive
Business Outcomes
BlueAlpha is designed to drive sustained business outcomes through continuous decision support rather than periodic analysis.
Instead of producing insights that quickly become outdated, the system operates in real time to keep decisions aligned with current performance, market conditions, and business objectives.
The system supports:
Regular model updates to maintain accurate measurement as performance dynamics change
Ongoing incrementality testing to validate assumptions and reduce wasted spend
Recurring planning and recommendation cycles to translate measurement into action
By operating continuously, BlueAlpha enables teams to:
Reduce budget misallocation before inefficiencies compound
Reallocate spend with greater confidence and speed
Maintain alignment between marketing, finance, and leadership
Improve decision quality over time through accumulated evidence
This replaces fragmented workflows that rely on disconnected tools, manual analysis, or platform reported metrics with a system designed to support durable, repeatable business impact.