foglight.ai technology is fast and easy to implement
The foglight.ai is easy to evaluate and implement by inserting a plug-in into the survey screen. The foglight.ai ‘black box’ runs on the cloud, sees only survey response data, and pushes the results to an API and reporting engine.
The survey taker experience is identical
Customer gets the enhanced survey results through an API
foglight.ai provides performance reporting
developed in biometric labs, refined through consulting, productised and democratized through software
BIOMETRIC LABS
BIONAVI™
laboratory to measure, filter,
and understand brain activity
and biometrics on human
behavior:
- brain waves (EEG)
- galvanic skin response (GSR)
- eye-tracking (ET)
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Customers:
- scientific and academic research labs
- marketing agencies for ad and concept validation
- content creators, including hollywood, to measure audience response
CONSULTING
NEUROHM™
combination of neuroscience and psychology tools to understand explicit declarations with implicit emotions
- consulting to improve quality of survey results and remove bias
- ‘behind the scenes’ customer and employee experience improvement
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Customers:
- high-end survey and focus group providers
- most high end consultancies
- agencies looking for research
- brands that are looking to increase customer and employee outcomes
SOFTWARE
FOGLIGHT.AI
leveraging emotion analytics into responses for digital interactions using AI in scalable and embeddable software
- combine what customers say and feel for more accurate business decisions
- add emotional metrics that predict behavior
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Customers:
- application providers in the customer and employee experience space
- digital survey providers
- brands that are building their own customer and employee experiences
backed by research
Lee, A.Y., Wang,J., Böckenholt, U., Lee, L., Ohme, R., Reykowska, D. & Yeung, C. (2022). The Enthusiasts and the Reluctants of COVID-19 Vaccine Uptake: A Cluster Analysis. Journal of the Association for Consumer Research. Healthcare and Medical Decision Making, 7(2), pp 222-234
Ohme, R., Matukin, M., & Wicher, P. (2020). Merging Explicit Declarations With Implicit Response Time to Better Predict Behavior. In V. Chkoniya, A. O. Madsen, & P. Bukhrashvili (Eds.), Anthropological Approaches to Understanding Consumption Patterns and Consumer Behavior (pp. 427–448). IGI Global
Chkoniya, V., Reykowska, D., Ohme, R., Côrte-Real, A. (2022). What Changed in One Year of a Pandemic and What the Portuguese are not Willing to Admit: Consumer Neuroscience and Predictive Analytic Contributes to Communication Strategy. In: Reis, J.L., López, E.P., Moutinho, L., Santos, J.P.M.d. (eds), Marketing and Smart Technologies. Smart Innovation, Systems and Technologies (Vol 279, pp 419-429). Springer, Singapore
emotional insights
speed and simplicity of foglight.ai binary scale
User Experience improvement with binary scale enhanced with foglight.ai: reduce speed and complexity of surveys.