Testing physical prototypes delayed evaluations by weeks. Now, researchers use AI consumer personas to simulate product trials in hours.
A global consumer goods giant operates in a highly competitive sector where the speed of product market introduction is a decisive competitive factor.
Evaluating new market ideas required time-consuming physical test series that took weeks to generate meaningful consumer insights. This slow research...
“Reckitt Benckiser setzt radikal auf künstliche Intelligenz, um die Entwicklung neuer Produkte zu beschleunigen.”
Reckitt's Product concept testing is part of this use case:
Global manufacturer of health, hygiene, and nutrition consumer brands.
Provides the BASES AI Screener, which uses AI-powered personas to simulate consumer behavior and accelerate product research.
Related implementations across industries and use cases
Manual media analysis and ad localization bottlenecked campaigns. Now, AI drafts insights and localizes assets for human refinement.
Manually coding product packages took four minutes each. Now, AI extracts and validates details, scaling globally without local staff.
Robotic voices limited trust. Natural AI moderators now conduct tens of thousands of conversations with human-like flow.
Manual media analysis and ad localization bottlenecked campaigns. Now, AI drafts insights and localizes assets for human refinement.
Sifting 100k weekly logs took months. Now, AI personas simulate customer dialogue to test hypotheses in days for negligible cost.
Routine queries burdened HR. Now, an AI WhatsApp agent instantly answers remote factory workers, escalating complex issues to HR.
Disparate tools slowed 320,000 employees. Unifying on Teams and Copilot connected the workforce and embedded AI into daily habits.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.
Testing physical prototypes delayed evaluations by weeks. Now, researchers use AI consumer personas to simulate product trials in hours.
A global consumer goods giant operates in a highly competitive sector where the speed of product market introduction is a decisive competitive factor.
Evaluating new market ideas required time-consuming physical test series that took weeks to generate meaningful consumer insights. This slow research...
“Reckitt Benckiser setzt radikal auf künstliche Intelligenz, um die Entwicklung neuer Produkte zu beschleunigen.”
Reckitt's Product concept testing is part of this use case:
Global manufacturer of health, hygiene, and nutrition consumer brands.
Provides the BASES AI Screener, which uses AI-powered personas to simulate consumer behavior and accelerate product research.
Related implementations across industries and use cases
Manual media analysis and ad localization bottlenecked campaigns. Now, AI drafts insights and localizes assets for human refinement.
Manually coding product packages took four minutes each. Now, AI extracts and validates details, scaling globally without local staff.
Robotic voices limited trust. Natural AI moderators now conduct tens of thousands of conversations with human-like flow.
Manual media analysis and ad localization bottlenecked campaigns. Now, AI drafts insights and localizes assets for human refinement.
Sifting 100k weekly logs took months. Now, AI personas simulate customer dialogue to test hypotheses in days for negligible cost.
Routine queries burdened HR. Now, an AI WhatsApp agent instantly answers remote factory workers, escalating complex issues to HR.
Disparate tools slowed 320,000 employees. Unifying on Teams and Copilot connected the workforce and embedded AI into daily habits.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.