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Unlocking Efficient Comment Analysis Workflows with AI

July 19, 2021
10
minute read

Konveio is dedicated to creating tools that simplify the process of capturing and analyzing public comments. However, managing this feedback efficiently and effectively for any project size, phase, and type has always a challenge.

When a topic resonates, stakeholders and community members are quick to voice their opinions. In such instances, it's imperative to acknowledge their contributions and there is a responsibility to organize and process their feedback to make use of the input. Doing this well sustains momentum and fosters trust, ensuring the community feels genuinely listened to and valued.

Clients of Konveio have long praised the way our document engagement platform saves staff time by simplifying the process of analyzing public comments and adding clarity to the insights, primarily by the very nature of having shorter and more productive comments placed on drafted materials.

The past:

However, this noble aim was easier said than achieved as local government staff must juggle many responsibilities simultaneously. The process of categorizing and analyzing comments is notoriously demanding on staff time and requires manual attention. It typically takes a significant amount of time and resources just to assess if valuable direction and insights were even collected in the first place. 

The future is now:

At Konveio we've paid close attention to the technological landscape and waited patiently for the missing innovations required for us to build out our vision for even more efficient comment analysis workflows that can increase both the consistency and quality of reporting to ensure that all voices are heard and weighted appropriately. 

Before 2023 and the rise of powerful Large Language Models from the likes of OpenAI, machine learning, and AI simply weren't powerful enough to deliver a reliable and specific enough workflow tool to fulfill our local government and consulting clients' interest in auto-tagging and auto-theming.

But the time has finally come to introduce Konveio’s new AI-powered comment analysis tool for planning documents, featuring simple ways to automatically tag comments by topic and finding themes within topics: 

1: Auto-tagging Feature:
  • Automated Tagging: Automatically tags comments with relevant topic keywords, tailored by our users for each document. If project managers are collecting feedback on a housing study, add housing-related keywords; for a comprehensive land-use plan, prioritize land-use oriented topics.
  • One set of tags does not fit all: set specific topic keywords per document, granting flexibility in comment categorization and analysis across all your projects.
  • Human oversight: While the AI efficiently handles most of the categorization work, users can easily review and provide corrections. This dual approach ensures a high level of accuracy, with AI handling the heavy lifting and humans refining the outcomes.
2: Auto-theming Feature:
  • Thematic Analysis: Based on the comment tagging, the feature identifies overarching themes within the feedback. This allows users to understand the broader context of the comments and see how they pertain to specific sub-themes, for example, Strengthening Regulations, or Expanding Renewable Energy under the broad umbrella topic of Climate Change.
  • Sentiment Breakdown: For each theme, users can see a sentiment analysis. This provides insights into positive, negative, or neutral sentiments, assisting in gauging public or group feelings toward particular topics.
  • Contextual Feedback Review: Easily locate the source of the comments. If a comment references a specific policy, paragraph, or image, users can quickly jump to that section, making the feedback review process more seamless.
  • Time-saving Feedback Management: With AI doing the heavy lifting of initial summarization, project managers can download themes in MS Word format and focus on refining the feedback rather than having to start from a blank slate.

In summary, Konveio's AI-powered comment analysis tool streamlines the feedback process, making it more intuitive, efficient, and insightful. Whether you're seeking feedback in small workgroups or from the broader public, this tool ensures every comment is understood in its proper context.

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