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Improve your customer experience by tackling challenges, enhancing your Net Promoter Score, and simplifying the collection of customer feedback with our state-of-the-art AI platform. Q°emotion acts as an innovative tool for semantic and emotional analysis, adept at accurately gauging the feelings of both your customers and employees. This revolutionary SaaS solution offers instant visual representations of customer feedback, enabling you to reclaim valuable time each week in processing comments while allowing you to concentrate on the most pressing actions that require attention. The AI-driven features of Q°emotion provide deeper insights into your audience, facilitating the customization of your services to better match their needs. With minimal effort, you can reveal various topics your customers are engaging with and obtain a thorough understanding of their sentiments. Additionally, you can rank your discoveries based on how often they are mentioned or the urgency of the concerns, ensuring your responses are both timely and applicable. By utilizing Q°emotion, you can convert customer feedback into practical insights that foster growth and enhance overall satisfaction. Ultimately, this leads to stronger relationships with your customers as their voices are acknowledged and acted upon.
What is Affect Lab?
A consumer insights platform centered on technology, designed specifically for Insights teams, facilitates the mapping of insights across a range of media, digital platforms, and shopper engagements, which in turn helps in crafting emotionally impactful customer experiences while refining the customer journey to increase conversions and collect data related to emotions, attention, engagement, and visibility. Additionally, it acts as a resource for usability testing and analytics for UX teams, allowing them to measure user focus, interaction, and emotional responses as users navigate their experiences, while also enabling the evaluation of prototypes, mockups, websites, applications, and chatbots to identify vital UI elements that capture consumer interest, ultimately resulting in user experiences that are emotionally refined and boost conversion rates. Moreover, the platform harnesses Emotion Insights to develop enhanced customer experiences, employing Facial Coding APIs to evaluate emotional reactions at scale, including single and multi-face emotion recognition in everyday environments, along with recorded video emotion assessments. It also supports the testing of various stimuli across multiple formats and channels, such as videos, print ads, planograms, packaging designs, websites, mobile apps, and chatbots, ensuring an exhaustive analysis of emotional feedback. By employing this comprehensive method, brands can effectively establish a profound emotional connection with their audience, which is essential for nurturing loyalty and sustaining long-term engagement. This innovative approach not only captures vital consumer behavior insights but also drives strategic improvements in marketing and product development.
Integrations Supported
Additional information not provided
Integrations Supported
Additional information not provided
API Availability
API Availability
Has API
Pricing Information
Pricing not provided
Pricing Information
Pricing not provided
Supported Platforms
SaaS
Supported Platforms
SaaS
Customer Service / Support
Standard Support
Web-Based Support
Customer Service / Support
Standard Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Training Options
Documentation Hub
Online Training
Company Facts
Organization Name
Qemotion
Company Location
France
Company Website
www.qemotion.com
Company Facts
Organization Name
Affect Lab
Date Founded
2016
Company Location
India
Company Website
affectlab.io
Categories and Features
Customer Experience
Analytics
Customer Segmentation
Dashboard
Knowledge Management
Sentiment Analysis
Survey Management
Text Analysis
Trend Analysis
NPS
Not specified
Categories and Features
Emotion Recognition
Not specified
Planogram
Not specified
Usability Testing
Not specified
User Research
Not specified