Industry
Technology
Use Case
Business Strategy
The Challenge
Google NBU faced multiple hurdles, including accurately predicting market share for competitive products, responding to competitors’ strategies, and optimizing complex product lines. Additionally, they sought to understand consumer psychographics to better target emerging user groups. Traditional methods were insufficient for these nuanced and strategic needs.
The Solution
Sawtooth Software’s suite of conjoint analysis tools provided robust solutions:
- ACBC enabled precise individual-level data collection, leading to accurate market share predictions.
- Game theory modeling simulated competitive dynamics, guiding strategic decisions.
- Genetic algorithms optimized entire product portfolios, reducing unnecessary complexity.
- Profile-based CBC identified psychographic segments, helping tailor user profiles and better understand audience needs.
The Outcome
Through these methods, Google NBU achieved the following:
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Enhanced Market Prediction: ACBC estimated a product’s market share within 1.6% of its actual performance.
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Competitive Advantage: Game theory modeling informed timely feature launches, boosting product competitiveness.
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Portfolio Simplification: Genetic algorithms recommended reducing products by 60%, without sacrificing market share.
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Psychographic Insights: Profile CBC segmented users into six actionable groups, aligning engineering and design priorities.
Sawtooth Software empowered Google NBU to transition from reactive decision-making to proactive strategy, achieving measurable business success while paving the way for future innovation. Learn more about how it all happened.