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Beam 101

Stage: How It Works

Target: CS, Platform Specialists, customers

Reading time: ~12 minutes

The Problem Beam Solves

Marketers know they should scale what works and cut what does not — but they rarely have the data to do it confidently. Traditional tools show what happened yesterday but cannot tell you what will happen if you spend more (or less) tomorrow.

Beam uses saturation curves — visual models showing how revenue grows with spend, and where returns start to flatten. It forecasts revenue, conversions, and ROAS at different spend levels using your last 90 days of performance data, helping you identify untapped growth potential, cut waste, and justify budget decisions across channels.

Customer Outcomes

  • Medik8 — Identified 50% headroom in Paid Shopping, leading to confident scaling
  • END Clothing — Improved efficiency without increasing total spend
  • Average 43% ROAS uplift when Beam insights fed into Prism automation

Module Outcomes

  • Explain Beam's purpose and how it forecasts revenue, conversions, and ROAS at different spend levels
  • Interpret saturation curves, Growth Potential, CAC targets, and RAG status
  • Apply Beam for budget decisions — scaling, cutting waste, sale period planning

Topic 1 — How Beam Works (The Science)

Bayesian Inference

Rather than merely observing past results, Beam uses Bayesian inference to model the underlying cause-and-effect relationship between spend and conversions. The system:

  • Learns a performance response curve showing how results change with spend increases
  • Continuously refines predictions using historical data
  • Estimates causal impact while accounting for diminishing returns, uncertainty, and data variability
  • Provides confidence intervals for scenario planning

Growth Potential

Growth Potential shows how much more you could profitably spend on a channel before hitting diminishing returns. For example, a channel might show 59% Growth Potential — meaning spend could increase by that amount while still driving profitable growth, though efficiency may gradually decline as scale increases.

Sale Period Flags

Sale Period Flags let you exclude sales spikes from modelling to see true business-as-usual (BAU) headroom. You can toggle between including sales dates (to model future promotions) and excluding them (for BAU planning). The system automatically detects likely sales periods, allowing manual confirmation.

Topic 2 — How to Read Beam Outputs

Saturation Curves

Saturation curves show expected conversions at every spend level. Here is how to read them:

Confidence intervals (grey shaded area) indicate model reliability. Narrow bands = high confidence (safe to act). Wide bands = lower confidence (test with smaller budget shifts first).

RAG Status System

Beam uses a dynamic Red / Amber / Green system to colour-code predicted outcomes:

  • Green — Performance at or above target. Strong results expected.
  • Amber — Performance near target. Moderate risk with room for improvement.
  • Red — Performance below target. High underperformance risk.

RAG thresholds adjust dynamically based on your last 90 days of blended performance data.

Summary Table Metrics

Topic 3 — Budget Optimisation Workflow

Beam enables a structured five-step approach to budget decisions:

Step 1: Identify Opportunities — Use Channel Health Check to pinpoint segments worth analysing, then examine those segments in Beam to evaluate scaling headroom and saturation levels.

Step 2: Review Channel Summary — Scan the summary table for channels beating CAC targets with high headroom (candidates for scaling) and those over-saturated or missing targets (candidates for reduction).

Step 3: Analyse Individual Curves — Examine saturation curves for selected channels. Note current spend position, target line proximity, confidence interval width, and maximum observed spend reference points.

Step 4: Make Budget Decisions:

  • Target met + high headroom — Increase spend gradually
  • Near target + flat curve — Hold or reallocate
  • Above target or near saturation — Reduce spend
  • Fully saturated — Pull back budget entirely

Step 5: Plan Budget Tests — Identify high-opportunity channels with headroom, select test budgets within CAC targets, establish observation timeframes, and refine based on actual results versus predictions.

Why It Matters

  • Beam turns measurement into forward-looking decisions — not just reporting on the past
  • Saturation curves make the abstract concept of diminishing returns tangible and visual
  • Growth Potential gives marketers a clear, defensible number when requesting budget increases
  • Sale Period Flags ensure forecasts reflect true BAU performance, not promo spikes

Key Takeaways

  • Beam forecasts revenue, conversions, and ROAS at different spend levels using Bayesian inference
  • Saturation curves show where each channel sits relative to its efficient frontier
  • Growth Potential = how much more you can profitably spend before diminishing returns
  • RAG status gives instant visual guidance: Green (scale), Amber (watch), Red (reduce)
  • The five-step budget optimisation workflow turns Beam outputs into action