MLY or BTA which is right for me?
This article helps you decide whether Blue Text Analytics (BTA) or MLY is the best tool for analyzing qualitative feedback in your organization. Both solutions analyze open-ended comments, but they differ in how they categorize feedback, the types of insights they generate, and the flexibility they provide.
BTA
Blue Text Analytics (BTA) analyzes comments using predefined dictionaries. These dictionaries contain themes and keywords that categorize feedback into topics relevant to teaching and learning. When comments are processed, BTA assigns them to the matching themes, allowing institutions to quantify and report on qualitative feedback. For more information, take a look at the Dictionaries .
MLY
MLY’s primary strengths are its specialized categorization and actionable insights. Built to understand the student and employee experience, the analysis results in more targeted and relevant insights with themes and terminology specific to the topic. Additionally, MLY enables the actionability of the insights through its Recommendations and Alerts models, providing a starting point for the most critical themes that arise from the data.
MLY uses Neural Networks (computer systems with interconnected nodes that work much like neurons in the human brain) that analyze qualitative data (feedback collected in the form of free-form text comments from employees and students) and summarizes that data into:
- quantitative feedback (such as the total percentage of positive and negative comments and,
- insights such as sentiments, recommendations, alerts, and topics.
Using Natural Language Processing (NPL), MLY can recognize hidden patterns and correlations in the data, cluster and classify them, and by processing more and more data continuously learn and improve.
Analysis options
| Abilities | BTA | MLY |
|---|---|---|
| Identify sentiments (positive, negative, etc) | Yes | Yes |
| Identify recommendations (do more, do less, etc) | No | Yes |
| Identify alerts (concerning feedback) | Yes | Yes |
| Categorize Student Teaching and Learning | Yes | Yes |
| Categorize the overall Student Experience | Yes (limited) | Yes |
| Categorize Employee Learning | No | Yes |
| Categorize the Employee Experience | No | Yes |
| Enter unique terms and phrases | No | Yes |
| Reorganize analysis categories | No | Yes |
| Import custom dictionaries | Yes | No |
| Integrate with Blue | Yes | Yes |
| Integrate with MTM | No | Yes |
| Analyze feedback from any source/platform | No | Yes |
| Redact feedback | No | Yes |
| Analyze feedback from various languages | No | Yes |
| Retain ownership of your data | Yes | Yes |
| Export analysis | Yes | Yes |
| Exclude short non-explicit feedback | No | Yes |
Static Reporting and visualization options
| Features | BTA | MLY |
|---|---|---|
| Frequency analysis | Yes | Yes |
| Theme/word cloud | Yes | Yes |
| Cross tabulation with demographics | Yes | Yes |
| Cross tabulation with quantitative feedback | Yes | Yes |
| Gap analysis | Yes | No |
| Comments filtered on alert thresholds | No | Yes |
| Filter topics by sentiment | No | Yes |
Interactive reporting and visualization options
| Features | BTA | MLY |
|---|---|---|
| Most alerts | - | Yes |
| Most frequent topics | - | Yes |
| All sentiments | - | Yes |
| Most positive topics | - | Yes |
| Categorized recommendations | - | Yes |
| All recommendations | - | Yes |
| Prioritized recommendations | - | Yes |
| Improvement opportunities | - | Yes |
| Share analysis with collaborators | - | Yes |
| Share analysis with guests | - | Yes |
| Filter drilldowns (by sentiment, by recommendation type, by alerts, etc) | - | Yes |