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Enterprise Layer Intelligence
Categories/Data Analytics/Morphii
Morphii

Morphii

Founded 2013

Capture emotional sentiment and user feedback through visual interactive scales

You can use Morphii to collect detailed sentiment and emotional feedback from customers and employees. Instead of relying on traditional numbered ratings or text questions, it provides visual expressions that let respondents show exact emotions and their intensity. This interactive approach helps companies increase survey response rates, gather richer open-ended text comments, and overcome cross-cultural language barriers. You can also connect emotional reactions to actual consumer behaviors, identify negative sentiments before they escalate, and understand what drives overall customer satisfaction across various touchpoints.

What Morphii does

Add visual emotion selection widgets to existing customer surveysTrack the intensity of user dissatisfaction to prevent customer churnGather qualitative text feedback from previously disengaged survey takersConduct multilingual research using non-text facial expressionsAnalyze emotional response data alongside standard business metricsRun employee engagement pulses with visual feeling scalesInteractive visual emotion scales instead of numeric rating scalesMeasurement of emotional intensity to gauge respondent feelingsNon-verbal feedback mechanisms that bridge language and cultural gapsChild-friendly expressive options for youth and student researchPredictive analysis linking emotional reactions to customer behaviorsIncreased open-text response collection from silent survey participantsSurvey integration compatibility with external research tools

Frequently asked

RavenCSI, Qualtrics (via API), Salesforce (via API), Zapier, Custom Webhooks, REST API, JavaScript SDK

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Morphii, Customer Feedback and Survey, sentiment analysis, emotion tracking, survey completion rates, customer experience, employee engagement, visual feedback, experience data, user research, cross-cultural surveys, qualitative feedback, CX analytics, voice of customer, sentiment capture