What are the right tools to conduct good Atomic Research in 2024? [Part 2]

Welcome to this new article dedicated to Atomic Research, a revolutionary approach to UX design and research, inspired by Atomic Design and theorized by Daniel Pidcock. This innovative method divides research knowledge into atomic (key) elements such as experiments, facts, insights, and conclusions.

In this exploration, we will dive into the world of essential tools for successful Atomic Research. We will see here:

  • CHow can we effectively share results with stakeholders?
  • How to encourage consultation of your Repository by your teams?
  • How is the role of User Researchers impacted by AI? 

What is a Repository?  

As part of Atomic Research, the UX repository (ou user experience repository) positions itself as an essential asset. It is a centralized reserve, that is to say a real digital safe, where all the learning from different user research. Imagine it as a digital library gathering the observations (facts/facts), encrypted data (Hotjar or Contentsquare), emerging trends (studies of behavior in certain markets), learning (insights) Et les Recommendations (recommendations) arising from experiments

Concretely, it is a centralized platform where the experiences (experiments), facts, learnings (insights), and recommendations (recommendations) arising from different user searches. Its main objective is to provide consolidated and accessible reference, allowing teams to revisit as well as take advantage of accumulated knowledge throughout the process of working on a project. This Repository thus acts as the collective memory of the team. promotes the collaboration, Coherence, and the amelioration keeps going projects based on solid and validated data. For each Repository, there must be one or more lead UX designers which will keep the database alive over time. 

 

Tools to build your Repository 

When it comes to setting up a UX Repository within the framework of Atomic Research, several tools stand out. This is done based on their functionalities and their ability to facilitate the management of knowledge from user research. In the first group of tools, platforms like Notion et Tail provide flexibility in creating and organizing content. These tools help structure information efficiently using table features, cross-page links, and real-time collaborations. The clarity of the interface and the ability to integrate various media types contribute to intuitive data visualization. 

In the second group, more specialized solutions such as airtable et dove tail stand out for their ability to manage complex data in more depth. These tools provide advanced features for classifying, filtering and analyzing information. They thus offer a more in-depth approach to extract relevant insights. 

Group 1 – Flexibility and Collaboration:

When it comes to creating a UX Repository in the context of Atomic Research, various tools stand out for their functionality and their adaptability to managing knowledge from user research.

🔗 Concept:

Strong points : flexibility in creating and organizing content, real-time collaboration, integration of various media types.

Weak points : Some advanced features may require initial learning how to work, such as making inter-page (data) links to connect information. Problems tagging content to better filter it.

🔗 Code:

Strong points : high flexibility and customization, integration of interactive documents, real-time collaboration.

Weak points : clearning curve to maximize usage, some features may require more advanced configuration.

🔗 Glean.ly:

Strong points : intuitive interface, ability to create and organize content quickly, user-friendly sharing features. Tool specifically designed for the method with an indicator of the quality and quantity of an Insight. 

Weak points : fewer advanced features compared to other tools, usage-based pricing and not very pleasant to use for non-UXers.

Group 2 – Advanced Data Management:

🔗 Airtable:

Strong points : advanced data management with classification and filtering features, adaptability for specific needs. Ability to share data with different views to non-UX users. Possibility of creating a dashboard summarizing in data form what the Repository contains and the number of recommendations completed/made. 

Weak points : possibility of increased complexity with larger databases, learning curve for advanced features.

🔗 Dovetail:

Strong points : in-depth data analysis, advanced features to extract relevant insights. 

Weak points : pmore focused on analysis than on creation, potential cost for advanced features. 

In summary, the first group stands out for its ease of use and flexibility, which is why certain companies like the Accor Group use Notion or France Info which uses Coda. While the second group stands out for its more advanced features, which are ideal for in-depth knowledge management in Atomic Research. We can notably cite the L'Occitane Group which uses Airtable, a very widespread tool in large companies.

How to share analysis results with non-designers? 

Ensuring effective dissemination of Atomic Research results to key stakeholders, such as Product Owners, UX/UI Designers, Dev and Business teams, is crucial for shared understanding. One-Pagers, with a scoring system, make it possible to clearly visualize the potential impact of each recommendation, facilitating the transmission of essential lessons and aligning teams towards improvements in the user experience. Actively promote these results and the tool used, via initiatives evangelization and One-to-One or group training, encourages wider adoption. The training sessions that you can run offer other teams an opportunity to master your Repository tool and help them understand the Atomic Research methodology. At the same time, the regular publication of results on channels dedicated to UX/UI, such as internal channels, makes it possible to raise awareness throughout the company of the efforts deployed by User Research. These are the numbers that will speak for themselves in the eyes of other teams. You should not hesitate to quantify information in UX and carry out ROTI to collect feedback from colleagues and improve your evangelization process.

 

What impact does AI have on the Research Design Industry?

By listening to the podcast “#92 Impact of AI on the design industry with Jakob Nielsen”, an important question arises in relation to the evolution of the profession of User Researcher, particularly within the current technological landscape. We also question the idea of ​​integrating AI into the process. Jakob Nielsen explores in depth the impact of AI on the Design Industry, raising significant questions about its influence.

It is important to highlight Mr. Nielsen's point of view, which highlights that, despite advances in AI improving certain aspects of design, it cannot replace the central role of a human UX Designer in the context of user research. The complex nuances of human emotion, creativity and empathy remain essential elements in creating truly captivating user experiences. However, by integrating AI as as assistant, tangible benefits such as improving efficiency, optimized time management, and enriching data with market insights could be realized. Thus, the balanced collaboration between human intuition and AI could not only preserve human expertise, but also enhance added value in the user research process.

 

Conclusion

In summary, Atomic Research offers an in-depth vision of the essential tools in 2024, highlighting the crucial role of the UX Repository as a collective memory to promote collaboration and continuous improvement. The choice between flexibility and advanced data management depends on specific needs. Airtable and Dovetail are recommended for efficiently building a UX Repository. Communicating results is highlighted as a key element to influence strategy. Regarding AI, its role as a complementary assistant and not as a replacement for human intuition is highlighted. It indeed opens the way to a future where research evolves with increased efficiency and an unparalleled wealth of data (but be careful, AI must be able to source its information to avoid misleading analyzes and laws on data protection).

 

Did you miss part 1? Find it by clicking here!

 

 

Anton Blondeau, Product Designer Consultant at UX-Republic