What is the RICE scoring model?
The RICE scoring model is a prioritization framework for product managers to determine the priority of features/new products etc on the basis of four factors — Reach, Impact, Confidence, and Effort.
Reach — This measures how many users/people will the new initiative reach in a given frame of time. Depending on the feature and it’s scope, reach could be any specific number — new customers in a month, the number of new sign-ups in a quarter because of the new initiative and so on. It helps in removing bias towards features.
Let’s say we are building a micro site that is expected to bring in 1500 new users to app download page in a month. Of these users, let’s say 20% of the users are expected to download the app , then the reach score is 20% of 1500 or 300 in a month.
Impact — This generally reflects a quantitative goal. And the impact can be measured on any given scale like 1–5, 1–10, 0–1 and so on. Measuring impact requires us to isolate the reason behind impact and hence making analyzing the impact of a new initiative in tandem with some measurable resulting events. For example, if more users are purchasing a subscription after the launch of a new feature, we will have to track and ensure that the increase is because of the new feature and not anything else, to measure the impact correctly.
Let’s say we are deliberating on three new features — adding a repeat order feature, building an recommendation engine to suggest purchases to the user and adding discount feature on the shopping cart. Each of these features are likely to have different impacts on the users that can be measured by seeing the increase in the number of purchases. However, for prioritization, we need to give an impact score to each of these features.
Confidence — A confidence score generally helps in weighing the pros and cons of new feature sets which are competing for go live. If there is data supporting the reach or impact analysis of a feature, that feature will get more confidence score. We can consider this as our data-based assessment of the likely success of a new feature launch.
Consider the example of adding three new features as stated above. In addition, to giving a reach and impact score, we need to give a confidence score depending on which feature is likely to prove better. This can be done based on a number of evaluation parameters
Effort — Reach, Impact and Confidence are numerations in RICE scoring equation. The effort is the denominator and represents the cost. It can be measured in terms of man-months effort needed to implement the features in contention.
If we consider the three new features above, we will estimate the effort needed to implement the same. And based on all scores, we will calculate a RICE score for each of the new features and finalize what to prioritize based on that.
References & Further Reading
About the Author
Arpit is a seasoned technologist with vast experience in leading large cross-functional and cross-geography teams. Arpit also consults clients on competitive market analysis, defining MVPs, product ideation, product monetisation and go live strategies.
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