Explorance MLY Reviews & Product Details

- What is Explorance MLY: Explorance MLY, pronounced [mi-lee], is an award-winning AI-powered feedback analytics platform that transforms open-ended comments from any source into clear, actionable insights. Using Explorance’s pre-built machine learning models, MLY categorizes qualitative feedback into relevant topics, detects sentiment, redacts sensitive content, highlights recommendations, and flags critical issues—all with exceptional speed and accuracy. With MLY, you can leverage three purpose-built models: Student Experience Intelligence, Employee Experience Intelligence, or Employee Learning Intelligence. Each model is equipped with relevant topics that provide contextualized, nuanced insights that you can action quickly. Developed in-house and continuously refined, MLY reflects years of feedback expertise, thoughtful design, and a shared commitment to helping organizations amplify the voices of their people. - Key benefits: 1. Contextual Categorization: Comments are automatically analyzed and organized according to specific topics relevant to student experience, employee experience, and employee learning programs, making it extract meaningful insights specific to each context. 2. Sentiment Analysis: Analyze feedback to surface the most positive and negative topics, break down results by demographics, and receive prioritized recommendations organized by key themes to highlight strengths, identify growth opportunities, and drive effective action. 3. Targeted Recommendations: Receive prioritized recommendations organized by key topics to focus attention on the most important issues and support effective action. 4. Sensitive Content Redaction: Use custom keyword filters to automatically redact non-constructive or harmful feedback, protecting individuals from exposure to disruptive language while keeping valuable insights intact. 5. Custom Models: Define a personalized category structure and map institution-specific terminology to get a more accurate and comprehensive analysis. 6. Alerts on Pressing Topics: Automatically flag inappropriate content, identify emerging issues, and prioritize critical topics, allowing for timely, proactive responses to maintain a safe and responsive feedback culture. 7. Proprietary Models: Leverage Proprietary Models that is continuously trained and improved on relevant feedback and enhanced by expert reviews to deliver accurate, high-quality insights that adapt to emerging themes and provide prioritized recommendations for effective, focused action. 8. Scalable Comment Analysis: Upload large amounts of comments and receive fast, accurate, and scalable analysis in minutes. 9. Insight Dashboards: Use fully customizable dashboards to segment feedback by demographics with powerful widgets. Easily collaborate with stakeholders to monitor sentiment, highlight key areas for improvement, and drive informed decisions across your organization. 10. Multilingual Analysis: Capture input from all participants regardless of language — including Arabic, Bulgarian, Chinese (simplified), Chinese (traditional), Czech, Danish, Dutch, English (American), English (British), Estonian, Finnish, French, German, Greek, Hungarian, Indonesian, Italian, Japanese, Korean, Latvian, Lithuanian, Norwegian Bokmål, Polish, Portuguese, Portuguese (Brazilian), Romanian, Russian, Slovak, Slovenian, Spanish, Swedish, Turkish, Ukrainian —ensuring inclusive and representative insights across diverse populations.

Seller

Explorance

Discussions

Explorance MLY Community

Languages Supported

English, French

Overview by

Ian Ehninger

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Explorance MLY Integrations

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EH

Ellie H.

Data Analyst

Higher Education

Enterprise (> 1000 emp.)

9/15/2026

"Turning Thousands of Comments into Actionable Insights"

5/5

What do you like best about Explorance MLY?

I like how straightforward it is to use. The workflow is simple: I can upload a CSV of open-text survey comments, choose the right model, and select the fields I want to analyse, without needing any complex setup.

That makes it much easier to turn large volumes of qualitative survey feedback into something actionable. In particular, the sentiment analysis and recommendation extraction help me identify key themes, issues, and suggested improvements that would otherwise take a significant amount of time to review manually.

For me, the main benefit is that MLY makes open-text analysis far more efficient, while still giving me control over what’s being analysed. Review collected by and hosted on G2.com.

What do you dislike about Explorance MLY?

One area I think could be improved is topic categorisation. There are certain specific themes I’d like to be able to identify more easily (such as comments relating to dissertations) but there isn’t currently a dedicated category for this.

I’ve also found that the model can occasionally miss fairly straightforward categorisations. As a result, I still do a quick manual review before presenting the results to stakeholders. The outputs are very useful for speeding up the analysis process, but I’d feel more confident relying on them directly if the topic coverage were broader and the categorisation more consistent. Review collected by and hosted on G2.com.

What problems is Explorance MLY solving and how is that benefiting you?

MLY helps us analyse thousands of open-text survey comments that would otherwise be extremely time-consuming to review manually and, in some cases, might not be analysed in depth at all.

It can process large volumes of comments far more quickly than is feasible through manual analysis, while also identifying sentiment, themes, and recommendations across the dataset. This turns unstructured feedback into actionable insights that we can share with stakeholders much sooner.

The main benefit is that we can make better use of the qualitative feedback we collect by spotting recurring issues and areas for improvement, and doing so at a scale and speed that would be difficult to achieve manually. Review collected by and hosted on G2.com.

Current UserValidated ReviewerSource: Organic

RC

Richard C.

Business Intelligence Analyst

Enterprise (> 1000 emp.)

9/15/2026

"MLY Quickly Captures Student Voice and Guides Targeted Improvements"

4.5/5

What do you like best about Explorance MLY?

MLY helps us understand our students’ voices quickly, easily, and in a targeted way. With that understanding, we can make informed decisions to improve our students’ experiences, and MLY even recommends where and how to make those improvements. The performance is excellent: even with thousands of comments, it takes minutes to process rather than hours or days of human effort. It also feels like good value for money when it comes to price. Review collected by and hosted on G2.com.

What do you dislike about Explorance MLY?

From the free-text analysis results, we sometimes get answers we don’t agree with, or cases where the topic category feels obvious but isn’t picked up. We’ve also experienced delays when onboarding new MLY versions. Some UI features in MLY are limited from tab to tab and from user to user, although this has been improving with each release. We’re integrating with Power BI as well, but only indirectly via a CSV file export and Excel. Review collected by and hosted on G2.com.

What problems is Explorance MLY solving and how is that benefiting you?

I have always maintained that running surveys and collecting feedback is of limited value if nothing is done with the results. One of the main problems I’ve seen is that analysts and academic leads often don’t know where to start when it comes to student feedback. With MLY, that issue is addressed through targeted, bespoke outputs, built on sector-driven machine learning developed over many years. Once that clarity is in place, meaningful actions can be taken so the university can benefit and, ultimately, students benefit too. The secondary problem faced is the from the increasing number of surveys conducted, and potentially more comments to analyse. This would have potentially meant resourcing of time and effort from a person or team to process manually. With MLY, this resource burden is significantly reduced. Review collected by and hosted on G2.com.

Current UserValidated ReviewerSource: Organic

RT

Rose T.

Senior Data Analyst (Team Lead)

Enterprise (> 1000 emp.)

9/15/2026

"Explorance MLY: Fast & Effective Free Text Analysis | Rapid Results Turnover"

4.5/5

What do you like best about Explorance MLY?

I think that the Explorance MLY product has a highly effective user interface, it is easy to use, largely self explanatory, easy to understand and makes navigating to the various different levels of analysis quite intuitive. I also find that MLY fills an incredibly niche gap in the market - Free text analysis is considered very important in understanding the student and staff experience, however there are few mechanisms available that allow analysts to process the free text information quickly and effectively - MLY fills this gap. It is an impressive product. Review collected by and hosted on G2.com.

What do you dislike about Explorance MLY?

I wouldn't necessarily say that there is anything I particularly dislike about the product. I think there is space for refining and upgrading the product - but I think it's a good thing that there is this space for development. One area of refinement would be allowing the Employee Insights platform slightly more flexibility around the context of the survey - It seems like it processes general staff surveys very well - but struggles to allocate coding / categories to highly contextual surveys eg. a Pulse survey around staff communications. Review collected by and hosted on G2.com.

What problems is Explorance MLY solving and how is that benefiting you?

One of the pain points around Surveys in the institution is the time it takes to turn over the results, and subsequently the time it takes to address the issues raised. MLY allows us to rapidly turn over results to local leadership - which allows us to very quickly communicate with our community and establish action plans off the back of the results. Review collected by and hosted on G2.com.

Current UserValidated ReviewerSource: Organic

RR

Rahul R.

Business systems Analyst senior

Enterprise (> 1000 emp.)

6/17/2026

"Great Sentiment Categorization, Could Be More Focused on statistics"

4/5

What do you like best about Explorance MLY?

I really like how it categorises comments into multiple categories based on sentiment, and I also appreciate being able to add additional categories and map them to preset themes. It also doesn’t hallucinate too much, which makes the results feel more reliable. Review collected by and hosted on G2.com.

What do you dislike about Explorance MLY?

I feel like it has too many features, and I’d really like it to focus more on the insights. Right now, it feels like the categories are being attached in a way that isn’t based on statistical significance. Review collected by and hosted on G2.com.