Your market changes – your ATU should change, too

At Fulcrum Research, we transform your ATU into an adaptive learning system. This system maintains the stability of the core KPIs you track over time, ensuring the longitudinal integrity of your data. At the same time, it increases the relevance of your insights-gathering capabilities for everything outside core KPIs. Utilizing AI technology and competitive intelligence capabilities, the system rapidly addresses emerging questions and ensures your ATU adapts to the needs of your changing marketplace. 

Keep the core – create room to learn

At the core of all ATUs is a set of stable KPIs that companies track and trend over time. We preserve this core but create flexible modules that can change from wave to wave. A brand might use that space to understand the detailed implications of a competitor launch, investigate a new barrier to adoption, explore different patient types, assess new messaging or respond to an emerging strategic question. 

For example, a 30-minute survey might devote roughly 20 minutes to core tracking measures and 10 minutes to an adaptive module. The precise balance will vary by program and wave, but the principle is simple: protect what you need to measure consistently while creating space for what you need to learn now. 

That flexibility can also reduce the need to commission a separate study every time an important new question emerges. 

Transforming your ATU into an adaptive learning system 

An adaptative learning system doesn’t stop with the core questionnaire. Instead, we can transform your ATU into the centre of a broader learning system, using different sources of market intelligence to understand what sits behind movements in the data. 

The two main sources of this insight involve advances in AI technology and competitive intelligence: 

Using the latest AI to create a learning system. Synthetic Users won’t replace primary research or the validated longitudinal measurement of the ATU. Instead, they give research teams a fast way to explore new questions that arise from market changes, pressure-test hypotheses, and inform the development of the right way to ask questions before committing valuable survey time or commissioning additional research.

Synthetic Users add a rapid exploration layer around the core tracker KPIs. These AI-generated research participants designed to represent a defined audience or stakeholder. Synthetic Users demonstrate over 90% correspondence with findings of human interviews.  

Utilizing AI stakeholders as a rapid exploration layer we can: 

• Replicate nearly any respondent type (e.g., HCPs, KOLs, patients, and caregivers), 

• Address any disease area – even rare and ultra-rare diseases  

• Conduct interviews in any language and region of the world 

• Deliver results in days, not months 

Imagine a competitor releases significant new data halfway through the quarter. Rather than waiting for the next ATU wave to begin exploring its potential implications, we can conduct Synthetic User interviews with target respondent types. This can help the team generate hypotheses, identify questions worth investigating, and shape the adaptive module for the next wave. After fieldwork, they can also help explore possible explanations for an unexpected result and determine whether it warrants deeper human qualitative research. 

In addition, Synthetic Users can review a proposed questionnaire from the perspective of the target audience: Is the language clear to a neurologist? Are important response options missing? Does a new product profile raise questions the research team hasn’t anticipated? Can a patient understand this language? This can help refine new modules and make better use of limited questionnaire space before fieldwork begins. 

Social listening

The same principle can extend to AI perception monitoring and social and digital listening. These sources can identify emerging narratives – what AI tools are saying about a condition or treatment, for example, or concerns gaining traction among patients or HCPs online – which can then be tested and validated through future ATU waves. 

And when an important finding demands deeper human understanding, targeted qualitative research can investigate why. 

The ATU remains the validated measurement layer throughout. But around it, these additional tools create a continuous learning loop: measure what is changing, explore why, bring in the relevant market context, and use what you learn to make the next wave smarter. 

Competitive Intelligence insights

Competitive Intelligence (CI) plays a different but complementary role: it helps put movement in the ATU into context. 

A tracker might show that consideration has fallen among a particular physician segment, competitor perceptions have improved, or switching intent has suddenly changed. The numbers tell us what moved. But the explanation may sit outside the survey. 

Did a competitor publish important new clinical data? Was there a label change or new indication? Has competitive messaging shifted? Did a competitor expand its field force or change its targeting? Was there a major congress or other market event between waves? 

Bringing the right level of CI into the program creates a timeline around the ATU data, helping teams connect changes in perception and behavior with changes in the market. The objective isn’t to bolt a large competitive intelligence project onto every wave. It’s to bring in the context needed to make the tracker more interpretable and actionable. 

From tracking performance to informing decisions

Ultimately, an ATU shouldn’t exist simply because a brand has always run one. 

It should help teams understand what is changing, why it may be changing, and what they should do about it. 

That requires a different mindset: not a tracker that is periodically refreshed when it becomes outdated, but one designed to evolve continuously alongside the brand. 

Your market isn’t standing still. Your ATU shouldn’t either.