Growth Method scores every new campaign idea automatically, in real time, so you can prioritise without manual effort.
Why automated scoring
We looked at the established prioritisation frameworks (RICE, ICE, PIE, PXL, WSJF, and the rest) and found they don’t work well for marketing teams:
- Goals change through the year, and teams want to reprioritise ideas against the current goal.
- Factors like impact, potential, and confidence are highly subjective, and often genuine unknowns. Teams want to remove that guesswork.
- Manual prioritisation is slow. In practice, teams are poor at predicting user behaviour and the impact of a change. The only reliable way to know a test’s impact is to run it, which is why A/B testing exists in the first place.
Real-time scoring
Because the hypothesis builder gives every idea a consistent structure, each one has enough detail to be scored automatically. When you create an idea, our AI-powered scoring runs in the background and returns a score from 1 to 10, with an explanation, usually in about three seconds.
Scoring currently weighs two factors:
| Factor | What it measures | Range |
|---|---|---|
| Ease | How easy the idea is to implement (simpler scores higher) | 1-5 |
| Relevance | How relevant the idea is to your active goal | 1-5 |
| Total | Ease and relevance combined | 1-10 |
Hover over the score in the app to see the explanation, for example: “This campaign is relatively complex (3/5) to set up as it involves crafting messages, identifying audiences, and tracking metrics on LinkedIn. Relevance is high (4/5) as outbound lead generation aligns well with the current goal of increasing leads.”
What’s next
Scoring is built to improve over time with real-world data. Factors we may add include previous-version success, team comments and likes, idea age, and historical win rates by individual or channel.