Weighted Scoring for Product Prioritization (With a Template)

Sometimes the standard frameworks don't quite fit. Your priorities might hinge on revenue, or retention, or a strategic push into a new segment — factors a one-size formula doesn't weigh the way you would. Weighted scoring solves this by letting you define your own criteria and how much each matters. It's the most customizable prioritization method, and with a simple template it's not hard to run.

How weighted scoring works

The idea is straightforward: score each feature against several criteria, multiply by how important each criterion is (its weight), and total it up. The highest total wins.

There are three steps:

1. Choose your criteria. Pick the 3–5 factors that actually drive your decisions — for example: user demand, revenue impact, retention impact, strategic fit, and effort (as a negative).
2. Assign weights. Decide how much each matters, as a percentage that sums to 100%. If revenue is your focus this quarter, weight it heavily.
3. Score each feature on each criterion (say, 1–5), multiply by the weights, and sum.

A simple template

Criterion	Weight	Feature A	Feature B
User demand	30%	5	3
Revenue impact	30%	2	5
Retention impact	20%	4	3
Strategic fit	20%	3	4
Weighted total		3.5	3.8

Feature A's total: (5×0.3)+(2×0.3)+(4×0.2)+(3×0.2) = 3.5. Feature B: (3×0.3)+(5×0.3)+(3×0.2)+(4×0.2) = 3.8. Feature B wins — its revenue and strategic strength outweigh A's popularity, because you decided revenue matters most this quarter. That's the whole point: the model reflects your priorities, not a generic formula's.

Where the scores come from

Weighted scoring is only as trustworthy as its inputs. "User demand" shouldn't be a guess — pull it from vote counts on a feature request board. Effort should come from the people who'll build it. The more your scores reflect real data, the more the model earns its authority. FeatureRequest gives you the demand signal directly.

Weighted scoring vs RICE

RICE is essentially a fixed weighted-scoring model with four preset criteria. Weighted scoring is the flexible version: use it when RICE's factors don't capture what matters to you, and you want to bake in revenue, strategy, or anything else. The trade-off is setup time — you're defining the model yourself. See our overview of frameworks for when each fits.

The one caution

Weighted scoring produces confident-looking numbers from subjective scores, so treat close totals as ties and use the model to inform judgment, not replace it. Revisit your weights each planning cycle, since your priorities shift.

Start with real demand

The demand criterion is the one users decide. Create a free feedback board on FeatureRequest, gather votes, and feed a weighted scoring model that reflects both your users and your strategy.