The RICE score is one of a number of prioritisation frameworks used by growth marketers to identify high impact marketing experiments. Our article on prioritisation frameworks goes into why these frameworks are needed, and the challenges they solve.
There are a number of prioritisation frameworks, or scoring frameworks, all centred around the same theme. These include:
- RICE Score
- ICE framework
The frameworks include a number of factors that combine to produce a numeric score – the higher the score, the higher priority, and the earlier the experiment should be done. The end result for growth marketers and growth marketing teams being a prioritised to-do list of the best opportunities to test.
“Growth is a function of maintaining a cadence of testing, and keeping the team focused on the best opportunities for that testing”Sean Ellis
Introducing the RICE score
The RICE framework was first introduced by Sean McBride, a former product manager at Intercom. The framework adds an additional ‘Reach’ factor to the traditional ICE framework. Scoring is therefore based on Reach, Impact, Confidence and Effort.
R = Reach
I = Impact
C = Confidence
E = Effort
Score = (R x I x C) / E
|Reach||How many people will this affect within a given period? Depending on your team or company goal, this could be the number of new visitors per month, or subscribers per quarter, or quote requests per year.|
|Impact||How much impact will this have on individual users? For example, how much could this change impact the quote request conversion rate? This is measured on a multiple choice scale:|
massive impact = 3x
high impact = 2x
medium impact = 1x
low impact = 0.5x
minimal impact = 0.25x
|Confidence||What level of confidence do you have in your estimates? Do you have data to backup your prediction? Have you done something similar before, or know someone else that has? |
high confidence = 100%
medium confidence = 80%
low confidence = 50%
|Effort||The total amount of time (typically in days) a project will require to make live. This should include any other teams that may need to be involved before it is launched – development, engineering, product marketing, product management etc.|
Calculating RICE Score
The final RICE score is calculated using the following formula:
(Reach * Impact * Confidence) / Effort
A RICE framework example
As an example, let’s apply the RICE framework to this article. Based on AHREFS data, the term ‘rice score’ receives about 300 searches/month in the UK, and over 3000 globally.
It’s a middle-of-funnel term for us, as people searching for it are likely growth marketers that are looking into prioritisation models.
We can see the top search results, with traffic ranging for 15 to over 300 views per month on page 1, although clearly many of these domains have far higher domain authority than us.
Using the RICE framework the team scored this idea as follows:
- Reach – we estimate 100 people within our 6 week experiment cycle. We’re a new site at this point, so unlikely to outrank the likes of Intercom.
- Impact – 1, or medium. It’s a bottom-of-funnel term.
- Confidence – 80% (or medium. We have a reasonable amount of SEO and ranking experience, hence are reasonably confident of the above.
- Effort – 0.5, as this will take well under a month, probably more like a day
So, we end up with 50x1x0.8% / 0.5, which gives us a RICE score of 20.
Looking for more?
The 2 best articles on the RICE framework are RICE: Simple prioritization for product managers by Intercom, and a prioritisation framework for estimating the value of ideas by Roadmunk.
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