Same spend, reshaped to demand
Rebuilding an annual media budget for a seasonal British manufacturer from the ground up, allocating the same total spend against four independent sources of evidence instead of last year's pattern.
Speak with NicSeasonal British Manufacturer
Client name and figures withheld for confidentiality.
The problem on the table.
A manufacturer with strongly seasonal demand was planning its annual paid media budget the way most businesses do: by rolling the previous year's monthly pattern forward. It felt safe, but it baked in last year's mistakes.
That inherited shape over-invested in months that looked like peaks but converted poorly, and under-funded the genuine demand windows where the same money would have worked harder. The total was not the problem. The shape was quietly leaving return on the table.
What forensic looked like here.
The budget was rebuilt from the ground up against four deliberately layered inputs, so no single signal carried the whole decision: first-party analytics on paid performance, measured across volume, conversion quality and engagement depth; the same performance broken out by product line, to separate genuine seasonality from noise; independent external search-trend data as a second opinion; and the known trade-show intent spikes that demand data alone misses.
Every first-party input used a three-year average rather than any single year, to smooth out one-off distortions from launches, weather or supply. A clear efficiency ceiling in paid search was identified, the weekly spend beyond which cost-per-acquisition rose sharply, and budget was capped at that ceiling and redistributed to the months that could absorb it efficiently. A macro overlay across energy, rates, fuel and consumer confidence framed the risk around the plan.
- A four-input evidence model, layered so no single signal dominates
- Three-year first-party demand averages to remove single-year noise
- A paid-search efficiency-ceiling analysis
- A demand-weighted monthly allocation
- A macro-risk overlay with quarterly review checkpoints
What changed.
The same annual budget and the same channel split, reallocated against four independent sources of evidence rather than habit. Over-invested, low-conversion months were flexed down to their efficient ceiling; genuine demand windows were funded properly.
Just as important, the plan was built to be reviewed month by month, so spend follows return rather than the plan, pulling back quickly where the data turns instead of spending for the sake of it. Evidence, not inertia, now decides where the money goes.
- 4independent evidence inputs
- 3yrfirst-party demand averages
- Same spendreshaped to real demand
- Quarterlyreview checkpoints
Other engagements.
Your number is next.
A proper conversation with the person who would do the work. Tell me where you are and what you are weighing up, and you will get an honest, forensic read on what I would change, what I would leave alone, and where the real upside is.
Speak with Nic