Content Portfolio Engine
Content does not pay back evenly — a few winners carry the whole library while most pieces barely move. Enter how much you publish, what it costs, and how often a piece lands, and the engine models content the way it actually behaves: as a power-law portfolio.
Content returns follow a power law: a small share of pieces produces most of the value, and that value compounds as winners keep earning long after publication. The engine multiplies how much you publish by your hit rate and the value of a winner, then accumulates it over two years to show run-rate value, net return, ROI and the true cost per winner. Crucially, it tells you whether your bigger lever is publishing more or raising the share of pieces that actually land — and for most libraries, hit rate wins.
Content Portfolio Engine inputs and result
How to use this calculator
- Enter how much you publishPieces per month at a pace you can actually sustain — not a one-off content sprint.
- Add fully-loaded cost per pieceInclude writing, editing, design and promotion, not just the writer’s fee. Honest cost makes the cost-per-winner number meaningful.
- Set your hit rateThe share of pieces that become real winners. Most libraries sit in the low teens; be honest, because this is the lever the engine watches hardest.
- Estimate the value of a winnerThe recurring monthly value a winning piece produces — leads, revenue or pipeline it keeps generating.
- Read the verdictThe engine compares publishing 50% more, raising the hit rate, lifting winner value, and cutting cost, then names the move that adds the most net value over two years.
RGM Expert Says
We built this engine because content budgets are almost always argued on volume — ‘publish more’ — when the math says otherwise. Content is a power-law portfolio: a handful of winners carry the library, and the misses cost real money. When we run a client’s true numbers, the lever that adds the most net value is usually raising the hit rate, not raising the volume.
The number that reframes the conversation is the true cost per winner. Divide fully-loaded cost by the hit rate and a $800 piece at a 12% hit rate is really costing about $6,700 per winner. Seen that way, a few points of hit-rate improvement — better topic selection, stronger briefs, real distribution — is worth more than cranking out more pieces that mostly miss.
We are not against volume; at a healthy hit rate, more pieces compound beautifully. But when the portfolio comes back underwater — winners can’t cover the misses — the only fix is to publish better before publishing more. The engine makes that trade-off explicit so the budget goes to the lever that actually pays.
How it works
The model treats each month’s winners as recurring value that accumulates over 24 months (a triangular sum, since winners stack), nets out production cost, and computes ROI and the true cost per winner. It then re-runs the model under four what-ifs to find the biggest lever.
- Pieces — published per month.
- Hit rate — share that become winners (the lever that compounds).
- Value per winner — recurring monthly value a winner generates.
- Cost per piece — fully-loaded production cost.
- Triangular sum — winners stack month over month, so cumulative value grows faster than linearly.
The power-law shape of content returns is widely observed; the cumulative model here is RGM analysis, designed to compare levers rather than predict an exact dollar figure for your account.
Content is a power law, not a conveyor belt
The default content plan treats output like a factory line: more pieces, more results. But content returns are wildly uneven — a small share of pieces earns the overwhelming majority of the value, and those winners keep compounding while the rest fade. Modeling content as a portfolio, rather than a queue, changes which lever you fund: at a low hit rate, publishing more mostly multiplies the misses.
The hidden number is the true cost per winner: fully-loaded cost divided by hit rate. It exposes why volume can be a trap. Doubling output at a 12% hit rate doubles your spend and your misses while adding only a few winners. Lifting the hit rate — sharper topic selection, better briefs, genuine distribution — lowers the cost of every future winner, which is why the engine so often points there first.
There is a floor case the engine watches for: when winners cannot cover the cost of the misses, the portfolio is underwater and runs at a loss. No amount of extra volume fixes that — it deepens it. The only repair is a higher hit rate, which is why the verdict refuses to recommend ‘publish more’ until the library is at least breaking even.
Reference points for content portfolios
Sanity checks, not rules. They show why the hit rate dominates the verdict.
| Input | Typical range | Why it matters |
|---|---|---|
| Hit rate | 8-20% | A few winners carry the library |
| True cost per winner | 5-10x cost/piece | The real price of content at your hit rate |
| Value per winner | Wide | Recurring leads, revenue or pipeline |
| Pieces per month | Sustainable pace | Volume only pays at a healthy hit rate |
What content leaders say
Most content fails. A few pieces carry everything. Plan for the power law and invest in being worth finding, not just being published.
The cheapest content is the piece that wins. The most expensive is the one nobody reads — and you make a lot of those.