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Description
Electric Twin is an innovative platform that utilizes AI to simulate synthetic audiences by constructing virtual populations based on actual data, enabling teams to swiftly forecast the thoughts, behaviors, and responses of target consumers concerning products, messages, campaigns, and strategic inquiries without the need for conventional surveys or focus groups. By integrating advanced language models, machine learning techniques, and insights from social science, it generates intricate synthetic personas that authentically reflect real-world demographics, allowing for rapid queries that yield insights with statistical accuracy akin to traditional research methods, often achieving results in mere seconds rather than the weeks typically required. This capability empowers organizations to evaluate marketing copy, product concepts, campaigns, and market hypotheses, facilitating quick iterations across various segments and enabling them to investigate responses from diverse demographic groups, ultimately expediting insights that would otherwise necessitate expensive and time-consuming field studies. Consequently, Electric Twin not only enhances decision-making efficiency but also reduces research costs, making it an invaluable tool for businesses aiming to stay ahead in a competitive landscape.
Description
Explore our extensive array of publications in Physical Sciences and Engineering, which encompass a wide variety of fields ranging from theoretical concepts to practical applications. Delve into our comprehensive collection of journal articles and book chapters in Life Sciences that showcase original studies, thoughtful critiques, and the latest theories. Stay informed about advancements in health and medicine that can drive research forward and enhance patient care. Browse through our books and journals that provide resources on education, reference materials, decision-making support, and other essential subjects. Additionally, uncover a vast selection of journals and books in social sciences and humanities that illuminate historical perspectives, contemporary issues, and emerging trends. Elsevier actively promotes the sharing of research data by authors upon manuscript submission, and this can include various forms of data such as raw and processed datasets, software, and algorithms. By fostering this practice, we aim to enhance transparency and collaboration within the scientific community.
API Access
Has API
No
API Access
Has API
No
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
Yes
Vendor Details
Company Name
Electric Twin
Founded
2023
Country
United Kingdom
Website
www.electrictwin.com
Vendor Details
Company Name
Elsevier
Country
Netherlands
Website
www.sciencedirect.com
