Simalto Framework: Adapting Conjoint Analysis for Qualitative Research

Janhvi was one of three people at Trinity who built the Simalto framework, an adaptation of conjoint analysis designed for qualitative interviews. The problem the team was solving was a real gap in the research toolkit: standard conjoint works well in surveys, but in live interviews, it is too time-consuming and does not allow for the kind of probing that makes qualitative data valuable.

The team wanted a method that could surface patient preferences across product attributes, such as efficacy, safety, dosing, convenience, and insurance coverage, while also letting the interviewer dig into the reasoning behind each choice. The Simalto exercise gives respondents a set number of points per round and asks them to allocate those points across attributes, revealing what they prioritize and how their priorities shift as the exercise progresses.

Building and Testing the Framework

The build process was iterative. Janhvi and her two colleagues ran the exercise internally first, using a car-attributes scenario to test how many rounds, how many points, and how many levels of movement produced clean, interpretable data. They ran multiple internal trials before the framework was considered ready for client work.

One of the key learnings from the build phase was how to handle messy outputs. Patient preferences do not always resolve cleanly: sometimes the data splits 50/50 between two segments with different priorities, and sometimes the rounds produce a gradual shift rather than a clear winner. Janhvi learned to analyze the data round by round, tracking how preferences evolved across the exercise rather than reading only the final state.

Applying It to the HIV Study

A year after the framework was built, Janhvi applied it to a live HIV patient preference study. The study included 100 patients and 25 HCPs, with the sample deliberately skewed toward patients because prior research had already established that HCPs were largely satisfied with current treatment options. The patient perspective was where the real signal sat.

The Simalto exercise confirmed the dosing-frequency insight: patients consistently prioritized reducing how often they needed to take or receive treatment, even when it meant accepting trade-offs on other attributes. That finding fed directly into the strategic recommendation on where the HIV market had room to innovate.