Where 16 Weeks Actually Goes in a Conjoint Study
Conjoint research in financial services isn't slow because the statistical methods are hard — it's slow because the mechanical work is enormous. Workshop emails document attribute-level decisions made in committee. Sawtooth Software CBC/HB model review threads contain the rationale for design choices that took hours to arrive at. Programming the CBC survey, generating the attribute-level design, and staging partworth utility tables for review each require skilled time that isn't available on demand. When a study costs $80k–$300k and runs on a quarterly product planning calendar, a 16-week cycle means you're always one quarter behind.
An Agent That Handles the Programming, Not the Thinking
An AI Labor Company agent is trained on your conjoint design workshop emails and Sawtooth Software CBC/HB model review threads — institutional knowledge that would otherwise leave with a senior research analyst. The agent generates experimental attribute-level designs, programs CBC surveys directly in Sawtooth Software, and presents partworth utility tables formatted for your strategic review before any findings go to product or pricing. You and your team approve each scenario before anything moves to a CFO-level discussion. The research cycle from design to insights drops from 16 weeks to approximately 7 in scenarios like this. The agent is typically live within 8 weeks of engagement.
The Strategic Value of Faster Research Cycles
This is fundamentally a competitive timing advantage. Financial services product and pricing decisions move on cycles — rate changes, feature launches, package redesigns — and research that arrives after the window closes has no value regardless of its quality. An agent that compresses conjoint cycles by 45–63% illustratively doesn't just save analyst hours; it gives product and pricing leadership access to willingness-to-pay data before decisions are made rather than after. That shift from reactive to proactive research is difficult to put a precise number on, but for a firm managing pricing decisions across product lines, the directional upside is significant.
Can the agent actually program a Sawtooth Software CBC survey, or does it just generate design specs that a human then programs?
The agent programs the CBC survey in Sawtooth Software directly, not just design documentation. It handles attribute-level design generation and survey programming — the work that currently sits in a queue waiting for a skilled research programmer.
Does SVP-level review still happen at every stage, or does the agent make decisions autonomously?
Every pricing scenario and partworth utility table goes through your review before any output moves forward. The agent handles generation and programming; strategic sign-off stays with you. Think of it as a highly capable research analyst who does the mechanical work and surfaces the analysis — you still decide what it means.
What research inputs does the agent need to get started?
Workshop emails documenting attribute-level design decisions and Sawtooth Software model review threads are the primary training inputs. If your team has prior CBC study archives, those accelerate the calibration significantly. The 8-week timeline to first production output assumes reasonable availability of existing research documentation.