VALUEntina methodology
VALUEntina, the AI value proposition assistant developed by Gotoclient, follows four rules: sourced data only, one module at a time, explicit validation before advancing, and a final read tested against real competitors.
What data does VALUEntina use?
VALUEntina uses only top-tier sources: public institutions such as Eurostat, the OECD, the World Bank and national statistics institutes; leading universities and business schools such as Harvard or MIT Sloan; proprietary research published by major companies; and research firms such as Gartner, Forrester, McKinsey or Kantar. Every data point is stated with its source name and year, and VALUEntina does not invent figures.
Why does VALUEntina require validation at every step?
Each module depends on the one before it. A pain point ranking built on an unverified persona produces a value proposition nobody can defend, so VALUEntina stops after every module and asks the user to confirm, correct or extend the output before continuing.
How does VALUEntina prioritize pain points?
Pain points are collected by category, cross-referenced with cited sources, and then scored from 1 to 3 on urgency and on business consequence. The resulting ranking decides which problems the value proposition must address first.
How does VALUEntina test differentiation?
VALUEntina identifies real competitors, scores them on the positioning dimensions the user actually competes on, maps benefits against every prioritized pain point, and closes with a differentiation conclusion that names both the differential space and its limits.
What problem does VALUEntina solve?
Most positioning work fails because the persona is assumed rather than researched and the value proposition is written before the pain points are ranked. VALUEntina solves that by forcing the order and citing the evidence. See how VALUEntina works, the FAQ or the VALUEntina homepage. VALUEntina is developed by Gotoclient.