Content Production Growth Model
Work backward from revenue to the content inputs required for growth.
- Difficulty
- Advanced
- Time to result
- ~months to results
- Steps
- 6
- Confidence
- 99%
The Content Production Growth Model begins with the revenue or traffic result required over a 12- to 24-month horizon and works backward to controllable production inputs. Teams forecast baseline channel growth, measure how many assets each writer can produce, divide that capacity between new publishing and historical optimization, and cohort the traffic generated by each type over time. They then model how changes in writer count, asset performance, optimization practices, or outsourcing alter the final output. Scenario comparisons—such as five million versus ten million visits—reveal the staffing and performance gap between possible targets. The method turns content from an open-ended creative activity into a managed system while preserving creativity inside repeatable processes.
Origin
Kieran Flanagan explains the content models HubSpot used to forecast traffic growth and determine how many writers were needed to reach multi-million-visit targets.
Core principles
- 01Start with the desired business result and work backward.
- 02Content growth becomes forecastable when its controllable inputs are explicit.
- 03New publishing and historical optimization produce different traffic cohorts.
- 04Creativity scales more reliably when housed inside strong processes.
How to run it
- 1
Set the required outcome
Define the revenue, customer, or traffic target and the period in which the business must achieve it.
Pro tip Model both a committed target and a more aggressive scenario.
Watch out A production target without a business outcome can optimize volume rather than value.
- 2
Forecast existing channels
Estimate what current channels will contribute based on historical trends and planned improvements.
Pro tip Separate baseline growth from the incremental effect of new initiatives.
Watch out Overly optimistic baseline assumptions understate the required content investment.
- 3
Quantify production inputs
Measure how many assets each producer can create and how that capacity divides between new work and historical optimization.
Pro tip Use sustainable output rather than a one-time sprint rate.
Watch out Counting assets alone ignores differences in quality and expected demand.
- 4
Cohort content performance
Track the traffic and conversions generated by each producer or content cohort over a 12- to 24-month period.
Pro tip Model new and historically optimized assets separately.
Watch out Short observation windows can underestimate the compounding effect of organic content.
- 5
Solve for resources
Calculate the number of writers, freelancers, optimizers, or process improvements required to close the gap to the target.
Pro tip Test combinations of higher output, better asset performance, and additional headcount.
Watch out Adding people before the production system is repeatable can multiply waste.
- 6
Reforecast with actuals
Compare real cohort performance with assumptions and revise investment and timing regularly.
Pro tip Update the model when ranking behavior or conversion paths change.
Watch out A static model becomes unreliable as the channel and competitive environment evolve.
In the wild
HubSpot estimated how many posts each writer could produce, divided those posts between new content and historical optimization, and examined the traffic generated by writer cohorts over 12 to 24 months. The team then compared scenarios such as reaching five million versus ten million visits and solved for traffic per post and writers required.
→ Leadership could connect an ambitious traffic target to explicit hiring and content-performance assumptions.
Common mistakes
Ignoring historical optimization
At scale, updating existing posts can acquire more traffic than publishing new posts, so excluding it distorts capacity planning.
Hiring from the target alone
Headcount should be derived from proven throughput and cohort performance, not from an arbitrary desire to publish more.
Treating creativity as the system
Creative quality matters, but predictable scale requires processes that repeatedly turn production inputs into measurable outcomes.
Is it for you?
Best for
Content teams with repeatable production workflows and enough historical data to estimate cohort performance.
Not ideal for
Early-stage channels that have not yet demonstrated a repeatable relationship between production inputs and business outcomes.
From the transcript
“I think this all comes down to you need a growth model because you need to be able to start with the result you want.”
“Those X amount of posts are spread between X-Men and U and X-Men of historical optimization. And that equates to a certain amount of traffic.…”
From the episode
How do you build an organic marketing engine for your business? (#197)