Growth engineering runs on experimentation.

But experimentation without structure quickly becomes chaotic. Ideas pile up, priorities shift, and teams start debating opinions instead of learning from results.

That's where experimentation frameworks come in.

These frameworks are not rigid processes. They are mental models that help growth engineers think clearly about a few important things:

Many growth teams are familiar with frameworks like ICE and RICE, which score ideas based on factors like impact, confidence, reach, and effort.

Those models are still useful. But as growth engineering has matured, newer frameworks have emerged that better reflect how modern teams run experiments across product, GTM, marketing, and engineering systems.

Below are three frameworks that capture different parts of the experimentation process.

BRASS is a useful framework for evaluating growth and acquisition experiments, particularly those related to marketing technology, distribution, and growth loops.

A Simple BRASS Scoring Method

To make BRASS practical, many growth teams score each factor from 1 to 5.

Then calculate the final score:

BRASS Score = Blink + Relevance + Availability + Scalability

Maximum score: 20

This creates a quick prioritization model:

The goal isn't mathematical precision.

The goal is to create a structured way to compare ideas quickly so growth teams can prioritize experiments without long debates.

Where ICE focuses on impact and effort, BRASS adds a layer of growth realism.

BRASS encourages teams to ask questions like:

For growth engineers working on acquisition systems, BRASS works well for evaluating:

The key idea is simple:

Prioritize experiments that can scale if they work.

HIPE was developed by teams at Pinterest to prioritize product-led growth experiments.

While frameworks like ICE focus mostly on scoring impact, HIPE pushes teams to think more deeply about product experience and historical signals.

HIPE shifts experimentation conversations toward questions like:

For growth engineers, HIPE works particularly well when evaluating:

It's a reminder that not every experiment is about growth hacks. Many of the most impactful experiments improve the core user journey.

BRASS and HIPE help evaluate individual ideas.

G.R.O.W.S helps teams manage the entire experimentation pipeline, not just individual experiments.

Developed by Growth Tribe, this framework treats experimentation as an operational loop.

This model helps teams visualize where experimentation actually happens.

Many organizations assume experimentation mostly happens during the coding phase.

In reality, most of the work happens in:

For growth engineers, G.R.O.W.S provides a mental model for building an experimentation pipeline, not just individual tests.

Experimentation frameworks are most useful when combined.

A typical system might look like:

The frameworks themselves are not the goal.

The goal is to build an experimentation culture that consistently produces learning.

Over time, that learning compounds.

Experimentation frameworks are not meant to replace judgment.

They exist to help teams:

For growth engineers, these frameworks become part of the organization’s operating system for experimentation.

When implemented well, experimentation stops feeling random.

It starts to feel systematic.

It becomes a structured system that compounds learning over time.

An experimentation framework is a structured method for prioritizing and managing experiments so teams can test ideas consistently and learn from results.

Yes. ICE and RICE are still widely used for experiment prioritization, but newer frameworks like BRASS and HIPE often provide more context for modern growth engineering teams.

Different frameworks solve different problems. Some help prioritize experiments, while others help manage the experimentation pipeline or evaluate product changes.

No. Frameworks simply improve decision-making and experimentation quality. Growth still depends on strong hypotheses, good measurement, and disciplined execution.