A forecast is a decision range, not a revenue promise.

Planning starts with business economics and operating capacity rather than a trend line. Each assumption is documented, each scenario has a range, and the budget has clear rules for when to hold, move, or stop spend. You end up with a budget plan you can defend in the room: the range, the assumption behind it, and the exact evidence that would change it. For teams with a real spend or allocation decision pending and a named owner who can approve it.

A strategist plotting a paid-search budget scenario fan across conservative, base, and upside ranges

Some of the 500+ brands we've worked with

See all references
  • GE
  • Odeabank
  • Marble Systems
  • Ajansspor
  • Armut.com
  • S Sport Plus
  • Amazon
  • BMW
  • Shell
  • Hyundai
  • PepsiCo
  • Red Bull
  • Decathlon
  • MediaMarkt
  • Bayer
  • Sanofi
  • EY
  • KPMG
  • 3M
  • Domino’s
  • Lexus
  • Trendyol
  • Hepsiburada
  • Yandex

The scenario ledger shows where every assumption came from and what changed between versions. AI can calculate ranges, compare inputs, and flag variance. It cannot approve an assumption or make a live budget change.

How we hold ourselves to it

  • Assumptions stay beside every range
  • The next unit earns its allocation from current evidence
  • Pacing safety has its own rules
  • A named person approves each material change
  1. Frame the decision

    Name the decision, its owner, the time horizon, the spend envelope, and how much risk the business will tolerate. Note what the model is not being asked to decide. The client budget owner approves the decision contract.

    Approved decision contract naming the owner, horizon, spend envelope, risk tolerance and what the model is not deciding.

  2. Audit the data and the assumptions

    Normalize the economics, media history, quality signals, seasonality, and constraints. Reconcile the totals that matter and grade how much confidence each assumption deserves. The strategy lead validates the source choices and exclusions.

    Reconciled input set with each assumption graded for confidence and each exclusion recorded.

  3. Build three scenarios

    Calculate a conservative, base, and upside case, each with its own spend, outcome range, limiting constraint, cash timing, and uncertainty. Human strategist owns the formulas and their interpretation.

    Conservative, base and upside cases, each with its spend, outcome range, limiting constraint, cash timing and uncertainty.

  4. Design the allocation

    Set engine roles, query-family priorities, capacity limits, and a protected learning budget, then build the waterfall, caps, and pacing rules underneath them. The paid-search lead proposes the allocation. Client owner approves it.

    Allocation design: engine roles, query-family priorities, capacity limits, protected learning budget, caps and pacing rules.

  5. Hand off and pace the spend

    Give native teams the approved budget, dates, limits, and trigger matrix, then watch delivery and cost daily and separate a real safety issue from ordinary variance. The authorized humans apply every live change and approve corrective action.

    Handoff pack with the approved budget, dates, limits and trigger matrix, plus the daily pacing record.

  6. Reforecast

    When the evidence or an assumption changes materially, version the model, show exactly what moved, recalculate the ranges, and record the keep, move, or stop decision. Strategy lead and client budget owner approve the new version.

    Versioned model showing exactly what moved, the recalculated ranges and the keep, move or stop decision.

The assumption register, scenario model, pacing sheet, and decision log show the input behind every version of the plan.

  • Assumption register

    Every input with its source, owner, date, and confidence, keeping an observed value, a business choice, and a modeled guess clearly separated.

  • Three-scenario model

    Conservative, base, and upside spend-to-outcome ranges, each naming what has to stay true and the constraint that hits first.

  • Budget waterfall and pacing sheet

    The approved envelope split by engine, campaign or query family, and time period, with caps, reserve, expected range, actual delivery, and variance beside each line.

  • Reforecast and decision log

    A record of what changed, why the range moved, and which keep, move, or stop action was approved, so the plan's history stays visible.

One forecast number cannot represent every quarterly constraint. A single figure for next quarter's search budget is easy to circulate. It also hides the assumptions behind the range. Margin, capacity, saturation, and cash timing disappear, and the figure starts to look like a promise nobody meant to make.

A good fit when

  • A real spend or allocation decision is pending, but the person accountable for cash timing, margin, and capacity still needs a reviewable range.
  • Your commercial and media history is imperfect yet usable, so the model can show its uncertainty beside each assumption and range.
  • You want the assumptions beside the budget range, so everyone can see which evidence would move or stop spend.
  • Last year's percentage split carries into this year's plan without anyone checking whether the constraint behind it has changed.
  • Nobody can say whether the forecast means gross revenue or margin, or what happens to cash when spend and revenue land in different months.
  • A platform simulator's directional estimate gets treated as a guarantee.
  • Budget keeps going to last period's winner even when current evidence points elsewhere.

Better handled as other work when

  • The team needs one exact budget figure regardless of the evidence, so a scenario model with conservative, base, and upside ranges will not answer the brief.
  • Conversion value or sales capacity is still undefined, which means spend cannot be connected to a stated business outcome with a defensible assumption.
  • Nobody can decide on cash timing, margin, or capacity, so the budget owner and finance sign-off must be settled before a range can be approved.
  • Optmyzr

    runs the three scenarios against real projected spend before any budget actually moves

  • TrafficGuard

    checks whether the spend and conversion history feeding the forecast is even clean

  • Looker Studio

    the pacing view the budget owner checks between the scheduled reforecasts

Bring us your economics, paid-search history, and capacity. We'll build a scenario model the budget owner can question line by line.
Plan PPC budget with Zeo

Why do you show three scenarios instead of one forecast?

One number hides how sensitive it is to demand, cost, conversion, quality, capacity, and measurement. Conservative, base, and upside scenarios show what has to be true for each case, and what would make us stop.

Are platform simulator estimates used as the forecast?

No. They are useful directional evidence, but they depend on historical data, settings, and current market conditions. We reconcile them with your economics, observed quality, and capacity before they inform a decision.

How often do you move budget between campaigns or engines?

We watch pacing and risk constantly, but we only move budget when the next unit has a genuinely stronger case after weighing quality, confidence, lag, saturation, and capacity. Leaving it alone is often the right call.

Can an AI agent approve a bigger budget?

No. Agents can audit inputs, calculate the approved scenarios, and triage variance. A named human owner approves every assumption, scenario choice, exception, and change to the live budget.