Medallia
Customer experience platform that collects feedback from surveys, contact-centre conversations, reviews and digital interactions, analyses it and routes it to the teams that act on it.
Ownership
- Acquired by an investor group led by Blackstone · closed Aug 2026 · source · In the Martech Market Report
Medallia signed a recapitalization agreement with its lenders on 17 June 2026 and completed it on 3 August 2026, moving ownership from Thoma Bravo to an investor group led by Blackstone-managed funds, Apollo and FS KKR Capital Corp.
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Ranked by reviewed relationship first, then by the capabilities they share with Medallia.
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Medallia Pros & Cons
Key strengths and limitations to consider, drafted by an AI model from public sources
Strengths
- Supports enterprise-scale multichannel feedback programs
- Combines survey, digital, speech, and text signals
- Provides closed-loop workflows for service recovery
- Offers GraphQL, REST, import, and webhook APIs
- Supports customer, employee, patient, and citizen programs
Limitations
- Pricing and packaging are not publicly transparent
- Implementation commonly requires specialized services
- API access requires customer authorization and setup
- Product breadth can increase administrative complexity
- Best value generally requires mature CX operations
Ideal For
Who benefits most from Medallia, drafted by an AI model from public sources
Quick Analysis
Medallia competes in enterprise Voice of Customer, customer experience management, and experience intelligence software. Its core product combines feedback program administration, survey and digital intercept collection, speech and text analytics, experience reporting, alerts, and closed-loop workflows across customer, employee, patient, and citizen programs. It is more operationally broad than a survey tool and more feedback-centric than a general-purpose CDP or CRM.
Its strengths are enterprise-scale feedback orchestration, multichannel signal capture, role-based reporting, text and speech analytics, and workflows that route issues to frontline or operational teams. The best fit is a large, distributed organization with complex CX governance, multiple business units, and an established VoC program. Medallia is broader than Qualtrics in operational experience signals and service recovery, stronger than SurveyMonkey Enterprise for program governance and analytics, and more feedback-program-centric than InMoment, though those competitors may offer simpler deployments or stronger specialization in particular industries.
Buyers should evaluate Medallia when feedback must be tied to frontline action, contact-center interactions, digital behavior, and executive reporting across a global enterprise. Consider Qualtrics for broader research and employee-experience breadth, InMoment for focused CX and contact-center programs, and Sprinklr for social and digital engagement scale. Validate implementation effort, data ownership, API limits, speech and text model coverage, CRM and data-warehouse integration, identity matching, survey governance, and the total cost of professional services before committing.
Global retail chain tracking post-purchase feedback and store recovery actions
Airline analyzing contact-center calls alongside post-interaction surveys
Bank linking branch, mobile, and relationship-manager feedback to churn risk
Hospital system monitoring patient experience across facilities and departments
Enterprise software company routing detractor feedback to account teams
Franchise organization comparing location-level experience performance
Capabilities
Core Capabilities
Also Supports
Pricing
Model
custom
Reliability (from Medallia’s status page)
Not enough status history yet (3 of 180 days observed).
Based on Medallia’s own status page, last 180 days · coverage 2% · as of 17 Oct 2026. Self-reported by the vendor, not measured uptime. How this is worked out
Runs alongside, not instead of
5 tools that overlap Medallia on paper and were judged to do a different job in practice. Worth knowing before a consolidation exercise deletes one of them. These judgements were drafted by an AI model, and most were accepted on its confidence rather than checked one by one; the reason is recorded against each pair.
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