DeepBench is a primary insights platform that connects businesses with hard-to-reach specialist B2B and healthcare research participants. Founded in 2016 by MIT Sloan students, DeepBench leverages proprietary software tools, including AI and machine learning capabilities, to enhance the efficiency and effectiveness of the expert matching process. This enables innovation teams in product, design, and strategy functions to gain a deeper understanding of their buyers, users, and stakeholders, thereby facilitating the development of superior products and services.
Key Features and Functionality:
- Expert Matching: Utilizes advanced AI and machine learning algorithms to connect clients with relevant experts efficiently.
- Flexible Pricing Models: Offers transparent and adaptable pricing structures, including a la carte and subscription options, ensuring clients pay only for the services they use.
- Client Anonymity: Maintains client confidentiality by default, with the option to share information to improve match quality.
- Diverse Expert Network: Provides access to a wide range of professionals across various industries and geographies, facilitating comprehensive insights.
Primary Value and Problem Solved:
DeepBench addresses the challenge of accessing specialized knowledge by streamlining the process of connecting businesses with industry experts. By reducing the time and cost associated with traditional expert networks, DeepBench empowers organizations to make informed decisions, enhance innovation, and develop products and services that better meet the needs of their target markets.