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Rethinking Atomic Research by introducing the RICE product prioritization framework

An inside look at how France TV, the French public broadcaster, developed their product strategy through Atomic Research
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, Team Lead Designer, and I, , Product Ops Manager, are commissioned to introduce user-centric and data-informed approaches at France TV. France TV is a big media company that consists of 8 digital products and 100+ people in the product organization (VP of Product, Heads of Product & Design, Product Managers, Product Owners, Product Designers, UX Researchers, QA and SEO experts).
The first step for us was to collect data: we needed to collect good quality data in the most efficient way. We immersed ourselves into the design and product teams. We started a lean approach by experimenting and testing Design Thinking workshops, Product Discovery methodologies, strategic framings and prioritization tools in order to find out our (perfect) product framework. Very quickly, we were able to build our own model, and fully integrate the Product Discovery approach and user-centric mindset into our product organization.
OK cool. So far so good right?

Problems and questions

This was only the beginning of a great adventure before we obtained any actionable insights for the product teams:
With 8 products and 30+ UX Researchers and Product Managers, we received a large number of user insights in a very short time. As the VP of Product, a Product Manager or a Developer, how to find the right information I need, as quickly as possible?
Insights came from our 8 different products and from different people. Sometimes it came in the form of a simple message sent to someone in the company. How do we maintain this log of insights? How do we create consistency in the documentation so that each product can use the data in the same way?
User research is expensive. We estimate that 20% of user research for one specific product could be used to solve the problems of another one. How do we turn an individual initiative into a solution shared among other products? How can we be sure that we don't already know the needs of the user?
Our users are looking for a unified and fluid experience when they navigate between our 8 products. They don't need to feel that in reality each product has its own organization and dedicated teams. How do we ensure the structure of our organization is not perceptible in the various user journeys of our products?


We didn’t believe it at first, but we came across one solution that worked. It’s called “Atomic Research”, and then it grew so big in our teams that it quickly became Product Atomic Research”.
This approach allows teams to better analyze, share and act on the knowledge generated by your user research. You can read great articles from and to better understand the Atomic Research model. To sum it up in one sentence:
“The concept is breaking UX knowledge down into its constituent parts:
Experiments “We did this…”
Facts “…and we found out this…”
Insights “…which makes us think this…”
Recommendations “…so we’ll do that.”

By breaking knowledge down like this, it allows for some extraordinary possibilities.”
And today, I can confirm this is true!
First of all, we had to adapt the initial Atomic Research model to our needs as an organization. We believe the “Product Atomic Research” method creates synergy with your teams and saves considerable time as you go through the Product Discovery process.
At France TV, Product Managers and UX Researchers work together on strategy and product roadmapping according to user research and Product Discovery results. It was not always the case, and we know several products in the market still work separately and do not work well together. It was therefore essential to change the last “Atomic Research” step, called “Recommendation”, to ““ in order to directly integrate our prioritization methods to completely finalize the product thinking before moving on to
and planning phases in our roadmaps.
Most of our Product Managers use the to prioritize. The framework was widely approved by several people internally, so we decided to formalize it more concretely within our Coda doc in the page.


We were able to accomplish a lot in just a few months for all 8 of France TV’s products. Thanks to Product Atomic Research and this Coda doc, we are sharing with great excitement, the benefits to our product organization:


transversality of knowledge vertically and horizontally, between products and within products
We break all the silos that could exist between product and design teams (Heads of Product & Design, Product Managers, Product Owners, Product Designers and UX Researchers).


standardizing our ways of working when relevant
We collect all the knowledge in the same place and through the same framework for every member and every team.


traceability of each action from end to end in the product chain
We organize all the data so that everyone can find the information they need as quickly as possible and can go back to the source of the data—thanks to good tags—and multiple ways of referencing information consistently.

Best practices

Sharing with you below some very quick best practices from our experience:
This repository is a database, and like all databases, it requires to be extremely rigorous and to create and respect some guidelines for a healthy and exploitable database.
First of all:
Manage your Product Atomic Research like a product, with a community of users (Product Managers, Product Owners, UX Researchers...): test, learn, evolve continuously
If you have any technical issue, is here for you
Create nomenclature and respect it
Fill in rigorously all the data (areas, tags, devices, user feeling...)
The objective of a tag is to be able to access as quickly as possible to a data from the Atomic Research, via the search tools available to all (Product Managers, Product Owners, Designers...)
An insight can evolve over time when corroborating observations gradually qualify the insight
An insight can be broken down when, as learning progresses, observations multiply and reveal several levels of granularity

What’s an “Experimentation”?

An experiment is the context in which we were able to observe user behavior.
It can be of several types: qualitative or quantitative (user test, path analysis, survey, performance analysis...).
It is linked to the observations that have been collected to ensure traceability.

What’s a “Fact”?

An observation is the statement of a user behavior that could be observed.
It can be collected in several forms, either via an observation of the user's usage, or directly via a verbatim.

What’s an “Insight”?

An insight is a verified teaching, an observation or an identified truth based on the motivations or difficulties encountered by our users.
It is derived from the analysis and synthesis of observations.
It must be usable. A team must be able to use it to make the best decisions and feed the roadmap (it opens the field of solutions).
It must be clear, concise and must trigger an action.

What’s the difference between “Fact” and “Insight”?

Fact = affirmation of something I have observed
Insight = affirmation of something I have verified (an absolute truth)

How to check your facts and insights are correctly written?

Fact ✅
We have observed that...
“The user returns to the navigation several times and moves from page to page”
Insight ✅
Which makes us think that...
"The search field is not visible"

What’s a good tag?

It must be designed to facilitate the search.
It must be part of a list of 50 max (all products or teams included).
Ask yourself if this tag will be the best word to find this insight/observation.
Ask yourself if it doesn't already exist in another form.
It should not be too micro.
It should not contain any syntax or spelling errors.
Beware of synonymous tags.

Let’s start

There are 3 main pages in this Coda doc
Consult and browse all the user research for each product.
Search for specific user feedback thanks to the search engine and its multiple available filters.
Reference all the and created by all the teams
Qualify facts into needs: the
according to business objectives.

How Product Atomic Research is structured

"We did this..."
These are experiments that have been done to identify, analyze and/or understand a user need. Experiments can be based on quantitative or qualitative data.
"...and we found out this..."
Here, experiments are attached to user observations. These are raw findings/observations that were found in the experiments mentioned above.
“…which makes us think this…”
Here, observations are linked to user insights. It is the qualification of one or more user observations.
"…so we’ll do that."
Here, insights are prioritized according to Reach and Impact for achieving business objectives, level of Confidence in the need, and technical Effort. The RICE methodology helps in this process (Reach, Impact, Confidence, Effort).

Tips to make the most of it

The main strength of this Coda doc is the fact you can filter on the top of every page according to your product or team. It allows you to break silos between teams and benefit from the results of other teams.
Let’s test
Select product(s)
No results from filter

All products or teams use the same doc. This ensures consistency between all products and knowledge. To find what you need, you can choose the filters adapted to your needs.
Evolving your own Coda Product Atomic Research template
The good news is that Coda is a full-fledged product: it has a "front" interface presenting data that has been previously entered in a "
" space for resources. This means that the tool evolves according to the needs of your product and design teams as a real product.
Let’s test
To do so, you or your team just have to send a request by clicking this button
present throughout the template. Then, you can view and manage all feedback here: . At France TV, we also connect this button to our Coda Slack channels
Slack new logo Vector Logo - Download Free SVG Icon | Worldvectorlogo
#coda-community in order to receive automatic notifications for the admin team and internal Coda/product communities.

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And as we apply lean and iterative methods to ourselves, we would be happy to get your feedback ideas. Please take a few minutes to share your input with us 🙏
This is V.1. Congrats early bird! 🐣
This document evolves on a day-to-day basis, stay tuned for any updates.
Published on 06.21.2021 by , as a Product Ops Manager and , as a Team Lead Designer and the contribution of all our fabulous teams at France TV.
Special thanks to , Codans and the .
Illustrations courtesy of and .

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