If you haven’t come across the concept of Atomic Research, you might be scratching your head. No, it doesn’t mean reading up on neutrinos and quantum tunnelling.
Instead, “atomic” refers to the original Greek definition of “atom” i.e., component piece, or unit. Let’s examine what atomic research is, where it came from and what benefits adopting this methodology provides for your business.
What Exactly is Atomic Research?
Atomic Research (AR) is a new approach to information gathering, storage and usage within a developmental process. It is a key tool when developing a digital product strategy.
Previously, user research gathered within an organization would be scattered throughout that organization in the form of reports, interview transcripts, surveys, video interviews, which were then rarely accessed, even if they could be located.
By contrast, atomic research aims to create discrete units of insight, or “nuggets” which can be standardized in format, stored in a database, and retrieved at will, then used to build informational content. To summarize why this might be useful, here are some of the main drawbacks of traditional user research:
- Longform reports are rarely read, and key insights can be overlooked.
- Research materials are non-standardized, making them hard to combine.
- Reports and data are siloed in different physical and virtual locations.
- User Research can easily be forgotten or superseded.
- Insights are not readily sharable across the organization.
By building a database of standardized informational units, all a company’s research becomes readily accessible and searchable. Insights are highlighted by this process, trends are easier to spot, and evidence can be presented for shifts in digital product strategy.
Where did Atomic Research come from?
AR was the brainchild of former WeWork Head of User Experience, Tomer Sharon, together with fellow UX expert Daniel Pidcock. Frustrated by the variable quality of research product and how it was presented, they devised the Atomic Research concept.
As Sharon describes in a Medium article, “continuous research is key to having answers to all research questions at all times.”
AR promotes the motion that research is not something a company occasionally indulges in, but a continuous process of strategic re-evaluation, using readily available data sources and easy to digest nuggets of insight.
With a fully accessible repository of data insights, a company can make constant improvements. It is no longer reliant on any one particular data source, but can draw upon them all, simply by accessing an ever-increasing store of knowledge and customer experience.
Since customers are rarely shy about voicing their criticisms, it makes sense to aggregate and extract value from these experiences as often as possible.
How are UX Insights Categorized in Atomic Research?
In 2017, Sharon designed a database and categorization system called Polaris at WeWork, to systematize the process of producing and storing these nuggets.
The basic structure of a nugget is as follows:
- A single insight, gleaned from key facts.
- Facts, gleaned from research.
- Underlying this, the source of the data.
- Metatags to allow this insight to be located at will.
The foregrounding of the insight, rather than the research itself, is an indication that AR is action oriented. Rather than producing passively consumed reports, slide decks or dashboards containing a host of data, AR is a collection of inescapable conclusions, which can be used to make a case for change or reinforce an existing policy.
The atomic nature of these nuggets means they can easily be combined into longer presentations, allowing staff to draw upon the collective user research of the whole company each time they come to make a case for change.
They can also be shared individually, in internal communications, newsletters and intranet boards (“insight of the day”, perhaps).
How are Nuggets Categorized?
The abovementioned metatags are a key part of the taxonomic system for storing and retrieving nuggets. They allow the categorization of insights into various categories, including:
- Procedural – date, data source, data type
- Demographic – age, gender, location
- Experiential – magnitude, frequency, sentiment
- Productivity – revenue, product line, units sold
- Service Design – journey, act, scene, character
Those last tags refer to the terminology of Service Design, describing the user’s journey through a particular service. Here’s a useful Medium article to explain more.
The Benefits of Adopting AR
All these nuggets are stored in a “research repository”, a searchable database which allows the quick recall and assembly of nuggets into arguments for or against a particular proposition. In this way, a UX professional can both make a case for change and demonstrate the need to do so, at the same time.
Access to this database can be extended across the organization, making AR a very egalitarian methodology. For instance, a small research project developed in a customer service department might be drawn upon by an R&D team working on a new project.
AR results in a very streamlined process for using data. It proceeds as follows:
- Data is obtained from a range of different sources.
- Facts are extracted from the data – these are unbiased and unmotivated.
- Insights are gleaned from the facts presented. These are separated into individual units (nuggets) for ease of use, tagged and stored.
- Conclusions are formulated from the most useful insights, generating new courses of action (or promoting stasis).
It’s an easy-to-understand process of distillation of actions from raw data. Although this is only an elaboration of how research should always work, it’s easier to demonstrate when mining individual nuggets of insight.
Rather than trying to force a conclusion from data which may not support it, insights are presented as fragments to be combined into a meaningful whole.
Atomic Research respects the complexity of organizations, and of customer behavior. It works logically from user research to conclusions and only uses the nuggets of insight that provide clear directions for change.
It is a highly practical approach to UX research which can be integrated meaningfully within the digital product lifecycle. We have explored the process of developing a product strategy in greater depth in this article, and talked about the whole process of creating a digital product here.
Atomic UX Research can also provide huge insights when working on product design, especially in new iterations of existing products, or new products which aim to fill a market gap. Integrating AR into your digital product lifecycle means it should continually improve with each new release or iteration.