Guide to Effective Submission Management

Online Engagement Platforms

Platforms such as Granicus (formerly GovDelivery and Bang the Table), Social Pinpoint, and Engagement HQ are purpose-built community engagement tools. They typically offer features such as interactive maps, idea boards, polls, discussion forums, comment walls, and story submissions. Their strengths lie in:

• Reaching broad, non-specialist audiences
• Generating awareness and publicising a consultation
• Facilitating informal, low-barrier participation
• Displaying real-time participation metrics and heat maps
• Hosting supporting materials like videos, FAQs, and documents alongside engagement activities

However, these strengths come with significant limitations when the subject matter is complex. Open comment walls and idea boards produce unstructured text that is difficult to categorise and compare systematically. The comments are usual short and ‘surface level’ or polarized positions, as the format itself does not encourage deeper deliberation. Polling features reduce nuanced positions to simple votes. The informal tone encouraged by these platforms is often poorly suited to professional stakeholders — such as industry groups, peak bodies, and subject matter experts — who need to make detailed, referenced submissions. Critically, engagement platforms do not ensure that respondents engage with the actual content of the document being reviewed.

Learn more: What Does Stakeholder Mean?

 

Structured Questionnaires

A structured questionnaire is a document or online form presenting a defined series of questions — including both closed (scaled or multiple choice) and open (free-text) questions — that directly map to the sections, proposals, or issues within the complex document under review. When well designed, a structured questionnaire:

• Guides respondents through the document in a logical sequence
• Ensures every submission addresses the same set of questions, enabling direct comparison
• Captures both quantitative sentiment data (agreement scales, ratings) and qualitative reasoning
• Provides a defensible and transparent analytical framework
• Is suitable for expert and professional stakeholders as well as general community members
• Produces data that can be systematically coded, tabulated, and reported

Why Structured Questionnaires Are More Suitable for Complex Documents

Ensures Substantive Engagement with the Content

Online engagement platforms present a persistent risk: participants may engage with the platform’s interactive features (placing pins, voting in polls, posting comments) without ever reading the underlying document. A structured questionnaire, particularly one that references specific sections, proposals, or criteria within the document, requires respondents to engage substantively with the material in order to answer meaningfully. This produces higher-quality submissions and a more reliable evidence base for decision-making.

 

Enables Systematic Comparative Analysis

When hundreds or thousands of submissions are received, the ability to compare responses across respondents is critical. Engagement platform comments are difficult to compare because respondents write to different prompts, at different lengths, on different topics. A questionnaire ensures every respondent addresses the same questions, meaning their responses can be directly tabulated, coded, and compared. Agreement-scale questions can be graphed and statistically summarised. Open-text responses to the same prompt can be thematically coded together.

 

Supports Proportionate Weighting and Disaggregation

Complex consultations frequently involve multiple distinct stakeholder groups — for example, industry proponents, environmental advocates, government agencies, and general community members — whose views may differ significantly and who may need to be reported on separately. A questionnaire can capture demographic and stakeholder classification data upfront, allowing analysis teams to disaggregate results by group and apply appropriate weighting. Engagement platform submissions are rarely structured in a way that makes such disaggregation straightforward.

 

Provides a Defensible and Auditable Process

For consultations with regulatory, legal, or political significance, the consultation process itself may be scrutinised. A structured questionnaire provides a clear, documented record of what was asked, in what order, and what responses were received. This audit trail supports transparent reporting and reduces the risk of the consultation being challenged on procedural grounds. Engagement platforms, with their mix of comments, reactions, and informal interactions, can be more difficult to defend as a rigorous process.

 

Accommodates Professional and Expert Respondents

Many complex documents require input from professional stakeholders: engineers, lawyers, planners, scientists, industry representatives, and government officials. These respondents typically expect a formal submission process. A structured questionnaire — particularly one made available as a downloadable document as well as an online form — meets professional expectations in a way that a social-media-style engagement platform does not. It signals that the organisation takes the consultation seriously and values the expertise of respondents.

 

Reduces Analysis Burden

Perhaps the most practical advantage is the reduction in post-submission analysis effort. Open-ended comments on an engagement platform require extensive manual reading, sorting, and categorisation before any analysis can begin. A questionnaire structures this work upfront: closed questions are pre-formatted for quantitative summary, and open questions are already grouped by topic. This makes it feasible to process large submission volumes within realistic timeframes and budgets.

 

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Best Practice Questionnaire Design

Start with Clear Objectives

Before writing a single question, clearly articulate what decisions or outcomes the feedback will inform. Are you testing support for a specific policy option? Identifying concerns about a technical proposal? Gathering evidence for a regulatory impact assessment? Each question in the questionnaire should serve one or more of these objectives. Questions that do not connect to a specific decision or output should be removed.

 

Mirror the Structure of the Document

Organise the questionnaire to follow the structure of the document being reviewed. If the document has five chapters or sections, the questionnaire should have five corresponding sections. This helps respondents locate relevant passages as they work through the questionnaire and makes it easier to map responses back to specific parts of the document in the analysis phase. Include section references (e.g., “The following questions relate to Section 3: Proposed Zoning Changes”) to orient respondents.

 

Use a Mix of Question Types Purposefully

Effective questionnaires for complex documents combine several question types, each serving a distinct analytical purpose:

 

Agreement/Rating Scales

Likert-type scales (e.g., Strongly Agree — Agree — Neither — Disagree — Strongly Disagree) are ideal for measuring the level of support for specific proposals, values, or principles. Use a consistent scale throughout the questionnaire and always include a “Don’t know / No view” option for questions where respondents may genuinely lack a basis for a view. Five-point scales are generally preferred for capturing nuance without overwhelming respondents.

 

Multiple Choice and Ranking Questions

Use these to identify preferred options from a defined list, or to rank priorities. These are particularly useful when a document presents multiple alternative approaches and you need to understand relative preference. Ensure the options presented are exhaustive and mutually exclusive, and always include an “Other (please specify)” option to capture positions outside the defined list.

 

Open-Text Questions

Open-text questions are essential for capturing the reasoning, evidence, and nuance behind rated responses. Every significant rating or preference question should be followed by an open-text prompt: “Please provide any comments or reasons for your response above.” Open-text questions should also be used to invite respondents to raise issues, identify risks, or suggest alternatives that the questionnaire may not have anticipated. Avoid making open-text questions mandatory — this discourages completion — but clearly communicate their value.

 

Factual and Demographic Questions

Include questions to capture the respondent’s stakeholder category, professional background, geographic location, and any other classification variables that will be needed for disaggregation in the analysis. These are best placed at the beginning of the questionnaire (before fatigue sets in) or at the very end, with a brief explanation of why the information is being collected.

 

Write Clear, Unbiased Questions

Question wording has a profound effect on response quality. Follow these principles:

• Use plain language. Avoid jargon, acronyms, and technical terms that may not be understood by all respondents. If technical terms are unavoidable, provide brief definitions.
• Ask one thing at a time. Avoid double-barrelled questions (“Do you agree with the proposal’s objectives and its implementation approach?”). Each question should test a single proposition.
• Avoid leading questions. Phrasing such as “Do you agree that the proposed increase in green space will benefit the community?” signals the expected answer. Use neutral framing: “To what extent do you support the proposed increase in green space?”
• Avoid loaded or emotive language. Words like “controversial”, “radical”, or “excessive” introduce bias. Describe proposals factually.
• Ensure answer options are exhaustive and balanced. If using a scale, ensure it is symmetric — the same number of positive and negative response options.

 

Manage Length and Cognitive Load

Respondent fatigue is a significant risk in complex document consultations, where the subject matter is already demanding. To manage length:

• Limit the total number of questions to what is strictly necessary. As a rough guide, aim for no more than 40–50 questions for a highly complex document, and considerably fewer for shorter documents.
• Group related questions under clear section headings with brief introductory text.
• Use skip logic (branching) to show only relevant questions to each respondent. For example, questions about a specific technical proposal may only be relevant to industry stakeholders.
• Provide an estimated completion time at the start of the questionnaire.
• In online formats, show a progress indicator so respondents can gauge how much remains.

 

Make the Questionnaire Accessible

Accessibility is both an ethical obligation and a practical necessity for reaching a diverse respondent pool:

• Provide the questionnaire in multiple formats: an online form and a downloadable document (Word and/or PDF) that can be completed and returned by email for respondents who prefer or require this.
• Ensure online forms comply with WCAG 2.1 accessibility guidelines (sufficient colour contrast, keyboard navigation, screen reader compatibility).
• Offer assistance for respondents who need help completing the questionnaire (e.g., a contact phone number or email).
• Provide clear instructions for how to complete and submit the form. Include details of other ways to submit (for example print and email the form as well as submitting online)
• Translate the questionnaire for non-English speaking communities if the subject matter is likely to affect them.

 

Pilot Test Before Launch

Always pilot test the questionnaire before releasing it publicly. Recruit a small group of internal and external testers representing different stakeholder types. Ask them to complete the questionnaire and provide feedback on clarity, length, technical issues, and any questions they found confusing or ambiguous. Pilot testing consistently identifies problems that are invisible to the people who wrote the questions.

 

 

Key Considerations for Analysing Submissions

 Establishing an Analysis Framework Before Data Collection

The analysis framework should be developed before the questionnaire is finalised — ideally at the same time as the questions are being written. The framework should specify: what outputs are required (e.g., a summary report, a detailed submission register, a cabinet briefing), what level of disaggregation is needed, what decisions the analysis will inform, and what analytical methods will be applied to closed and open questions respectively. Building the framework before data collection prevents the common problem of realising mid-analysis that critical classification variables were not captured.

 

Quantitative Analysis of Closed Questions

Closed questions (rating scales, multiple choice, ranking) lend themselves to straightforward quantitative summary. The key outputs typically include:

• Frequency distributions showing the number and percentage of respondents selecting each response option
• Mean scores and measures of spread for rating scale questions
• Cross-tabulations showing how responses differ across stakeholder groups, geographic areas, or other classification variables
• Statistical tests of significance where sample sizes permit and where testing group differences is analytically important

Be transparent about sample sizes and response rates when reporting quantitative results. A result showing that 70% of respondents support a proposal means something very different if it is based on 15 responses versus 1,500. Also note the non-random nature of most consultation samples: respondents self-select, meaning results should not be extrapolated as representative of broader population views.

 

Qualitative Analysis of Open-Text Responses

Open-text responses are often the most analytically valuable part of a questionnaire-based consultation, providing the reasoning, evidence, and contextual knowledge that closed questions cannot capture. However, they also require the most analytical skill and effort. The following approaches represent current best practice.

Thematic Coding

Thematic coding is the foundational method for analysing open-text responses. It involves reading through responses and assigning each response (or relevant portion of a response) one or more codes that describe its content. Codes are grouped into themes — higher-order categories that represent distinct types of feedback. For example, responses about traffic impacts, noise, and dust might all be coded under a “Construction Impacts” theme, while responses about economic benefits, job creation, and supply chain effects might be grouped under “Economic Outcomes”.

Develop the initial coding framework based on the structure of the questionnaire and the document, then refine it as coding progresses — adding new codes as novel themes emerge. Use a codebook to document each code’s definition and inclusion/exclusion criteria, ensuring consistency across coders. For large submission volumes, divide coding between multiple analysts and conduct inter-rater reliability checks (comparing codes assigned by different coders to the same responses) to ensure consistency.

Sentiment Analysis Within Themes

For each identified theme, record not just what respondents said but their evaluative stance: is the comment broadly positive (supportive), negative (concerned or opposed), neutral (informational or factual), or mixed? This allows reporting to convey both the substance of feedback and its directional character — for example, “The majority of comments on traffic management expressed concern, particularly regarding peak-hour congestion near the proposed access road.”

Identifying Representative and Outlier Responses

Select a set of verbatim quotes that best illustrate each major theme. Choose quotes that are representative of the mainstream view within that theme, but also note and document outlier responses — views that are held by a small number of respondents but represent a distinct and important perspective. Outliers are often particularly important in professional and expert consultations, as a single well-reasoned submission from a subject matter expert may warrant more consideration than many brief responses expressing a similar general view.

Noting the Weight of Evidence vs. Volume of Responses

A crucial and often misunderstood principle of qualitative consultation analysis is that the number of submissions expressing a particular view does not, on its own, determine the weight that view should carry in decision-making. A well-evidenced, technically detailed submission from a specialist may deserve more analytical weight than fifty brief form responses expressing the same general opinion. Equally, an organised campaign that generates large numbers of identical or near-identical responses should be identified as such and reported transparently, rather than being counted as independent evidence. Analysis reports should be explicit about these distinctions.

Handling Organised Campaigns and Form Letters

Consultations on high-profile topics frequently attract coordinated campaigns in which large numbers of people submit identical or near-identical responses, often facilitated by advocacy organisations. These should be identified through comparison of response text and reported separately from independent submissions. The existence of a campaign is itself analytically relevant — it demonstrates the mobilisation capacity of particular groups and may indicate the salience of an issue — but it should not be presented in a way that artificially inflates the apparent breadth of independent concern.

Using Software to Support Qualitative Analysis

For large volumes of open-text responses, qualitative data analysis software (QDAS) can significantly improve efficiency and rigour. Tools such as NVivo, ATLAS.ti, Dedoose, and MAXQDA support the management of large text datasets, systematic application of codes, retrieval of coded segments, and generation of summary reports. However these tools are very complex to use as they were primarily designed for an academic context. For more more real-world application, Simply Stakeholders provides the ideal mix of rigour and ease-of-use, with built in AI-assist for analysing issues, sentiment and triggering response workflows. For very large datasets, natural language processing (NLP) tools can assist with initial categorisation and sentiment analysis, though human review and validation of algorithmically generated codes remains essential for accuracy and defensibility.

Integrating Quantitative and Qualitative Findings

The strongest analysis reports integrate quantitative and qualitative findings to tell a coherent story about the range and nature of feedback received. Quantitative data provides the headline picture (“Three-quarters of respondents supported the proposed rezoning”), while qualitative data provides depth and nuance (“However, a substantial minority raised concerns about the adequacy of infrastructure to support increased density, with several engineering and planning professionals providing detailed technical arguments for a staged approach”). Neither type of data is sufficient on its own for complex document consultations.

Documenting and Reporting Analysis Transparently

Analysis reports should document the methodology clearly enough that a reader could understand and evaluate how conclusions were reached. This includes: the total number of submissions received, the breakdown by stakeholder type, the response rate (if the questionnaire was sent to a defined population), a description of the coding approach and who conducted the analysis, acknowledgement of any limitations or potential biases in the sample, and clear attribution of quantitative data to specific questions. Providing a full submission register (anonymised where appropriate) as an appendix is good practice and supports the transparency of the process.

 

Case Studies: Success and Failure in Submission Analysis

The following case studies illustrate how the quality of submission processes and analysis can shape — and sometimes distort — decision-making on complex projects and policies. They are drawn from publicly documented consultations and are intended to highlight both good practice and cautionary lessons. Where specific organisations or processes are referenced, these are based on publicly reported accounts.

Success: Infrastructure Analysis Saves a Major Transport Project

 

 

Success: Community Feedback Overturn of a Planning Decision

 

 

Failure: Poor Analysis Process Leads to a Flawed Decision — and a Legal Challenge

 

 

Failure: Volume Mistaken for Consensus — Poor Outcome for a Community

 

 

Success: Expert Submissions Prevent a Poor Environmental Decision

 

 

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Evaluation of a Submissions Management Process

How do you evaluate or judge the success or failure of a submissions management process? Is it the number of submissions you receive or some other metric?

Here are our recommendations for best metrics to use when evaluating your submissions process, based on key principles for good stakeholder engagement, such as The Brisbane Declaration – United Nations standards for Community Engagement which our founder helped develop:

• Quality of submissions
  • Did the submissions depict confusion or uncertainty about key aspects of the proposal which could’ve been addressed earlier and with better communication from the proponent?
  • Did the submissions indicate engagement with the content of the proposal – indicating deeper engagement and deliberation?
• Diversity of repondents – did you obtain submissions from a diverse group of stakeholders (look at role of stakeholders, geographic distribution, demographic details as well as stakeholder mapping details such as stakeholders with high levels of impact or interest. Also give specific consideration to the participation of poor and marginalised communities and Indigenous communities.)
• Did the submissions process offer the opportunity for participants to influence the proposal? Was that opportunity realised?
• How were the results of the submissions process communicated to the respondents and the broader stakeholders, especially in relation to the impact the submissions had on the proposal?

How Simply Stakeholders Streamlines Submissions Analysis and Reporting

Simply Stakeholders is a stakeholder relationship management platform used by government agencies and businesses to manage engagement, track interactions, and analyse submissions and feedback. Its built-in survey and forms function, combined with purpose-built analytical and reporting tools, makes it particularly well suited to the submissions analysis workflows described in this guide. The following explains how key Simply Stakeholders features directly address the challenges of managing and analysing structured questionnaire responses at scale.

Built-In Survey and Forms Tool

Simply Stakeholders includes a native forms and survey builder that allows teams to construct structured questionnaires directly within the platform. Forms support flexible question types — including scaled rating questions, multiple choice, ranking, and open-text fields — and can incorporate skip logic to route respondents through only the questions relevant to their stakeholder category or role. This means the questionnaire design best practices described in Section 4 can be implemented directly in the platform without relying on a separate survey tool.

Completed form responses flow automatically into the stakeholder records system, linking each submission to the relevant stakeholder profile. This eliminates the manual data entry step that consumes significant time when questionnaire responses are received via separate survey platforms and must then be matched to stakeholder records for classification and disaggregation.

Automatic Issues Detection and AI-Assisted Sentiment Analysis

One of the most time-intensive steps in analysing open-text submissions is the initial read-through to identify the issues and themes each response raises. Simply Stakeholders automates this step through its proprietary AI models, which automatically detect issues and analyse sentiment each time a new interaction — including a survey or form response — is added to the system.

Teams configure a set of issues categories relevant to their project or consultation in advance (for example: “Traffic and Access”, “Environmental Impacts”, “Economic Benefits”, “Implementation Timeline”). As submissions arrive, the system automatically highlights which issues are detected in each response and assesses whether the sentiment is positive, negative, or neutral. This provides an immediate at-a-glance view of the emerging patterns in the submission base before manual coding has begun, significantly reducing the time required for initial triage.

Critically, Simply Stakeholders AI analysis is “strictly controlled” with algorithms specifically designed for stakeholder engagement contexts, rather than general-purpose sentiment models. This is important for complex document submissions, where nuanced professional language and technical terminology can mislead general-purpose sentiment classifiers.

Qualitative Analysis Tools

Beyond automated issue detection, Simply Stakeholders provides tools for manual qualitative analysis that complement the AI-assisted layer. Analysts can annotate individual responses with comments, tag specific quotes for inclusion in reports, and apply additional codes beyond those detected automatically. This supports the thematic coding workflows described in Section 5.3, allowing teams to build a structured, searchable coding layer across the full submission dataset.

The ability to pull annotated quotes directly into reports is a particularly valuable feature for the submissions analysis context — it streamlines the process of selecting illustrative verbatim examples for each theme, which is otherwise a slow manual task involving cross-referencing spreadsheets and documents.

Stakeholder Segmentation and Disaggregation

Simply Stakeholders maintains a central stakeholder register that records each contact’s organisation, role, sector, geographic location, and any other classification attributes the team configures. When submissions are received via the built-in forms tool, responses are automatically linked to existing stakeholder profiles or new profiles are created. This means that disaggregated analysis — breaking down responses by stakeholder type, sector, or geography — can be performed directly within the platform without manual cross-referencing.

The platform also supports multidimensional stakeholder mapping, including influence, interest, and impact dimensions. This allows analysis teams to weight or contextualise submissions not just by stakeholder type, but by the relative influence and stake of each organisation — supporting the “weight of evidence” analysis approach described in Section 5.3.

Reporting and Dashboard Tools

Producing a submissions analysis report is typically one of the most time-consuming phases of a consultation process. Simply Stakeholders includes custom reporting dashboards that can be configured to display the key metrics and visualisations needed for a consultation report — including sentiment distributions, issue frequency charts, submission volumes by stakeholder group, and trends over the consultation period.

Reports can be saved, exported, and scheduled for regular distribution, making it straightforward to provide progress updates to project teams during the consultation period as well as producing the final analysis report. The platform’s AI Summaries feature can generate narrative summaries of the data, which analysts can then refine and expand — accelerating the drafting process without replacing the judgement and interpretation that a skilled analyst brings.

Centralised Record and Audit Trail

As the case studies in Section 6 illustrate, the defensibility of a consultation process depends heavily on the existence of a complete and auditable record. Simply Stakeholders maintains a full interaction history for every stakeholder — recording every submission, email, meeting, and event linked to the consultation. This creates a single source of truth that can support responses to freedom of information requests, judicial review proceedings, or internal audit requirements.

The platform also supports integration with external systems — including online engagement platforms such as those described in Section 2.1 — via API and integrations including Zapier. This means organisations that use both an engagement platform for community awareness and a Simply Stakeholders questionnaire for structured submissions can consolidate all consultation data into a single record, preventing the fragmentation of evidence that has contributed to the failures described in the case studies.

Automated Workflows for Risk and Escalation

For large-scale consultations where submissions may raise issues requiring immediate action — for example, a submission that identifies a safety risk, a legal compliance concern, or a significant reputational issue — Simply Stakeholders supports automated workflows that trigger notifications or tasks when specific issue categories or sentiment thresholds are detected. This ensures that high-priority submissions are routed to the right team member promptly, rather than being buried in a large submission queue awaiting the end of the consultation period.

 

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Practical Considerations for Administration

Consultation Period

The consultation period should be long enough for respondents to read the document and prepare a considered response. For complex technical documents, a minimum of four to six weeks is generally appropriate. Shorter periods disadvantage professional stakeholders who may need to seek internal approval before submitting. Avoid scheduling the close date during public holidays or periods of peak workload for target stakeholder groups.

Promotion and Distribution

A structured questionnaire only generates useful data if it reaches the relevant stakeholders. A targeted distribution strategy is essential, including direct notification to known stakeholders via email, publication on the organisation’s website and social media channels, and engagement with peak bodies and representative organisations who can distribute to their members. Consider whether an online engagement platform might usefully complement the questionnaire by directing a broader audience to it — this hybrid approach captures the audience reach of platforms while preserving the analytical rigour of the questionnaire.

Confidentiality and Privacy

Be clear with respondents about how their information will be used, whether responses will be published, and whether identifying information will be removed. Many professional stakeholders actively want their submissions attributed to their organisation, while individuals may prefer anonymity. Design the questionnaire to accommodate both, with explicit questions about publication preferences. Ensure the process complies with applicable privacy legislation.

Combining with Targeted Interviews or Workshops

For very complex documents or consultations where deep expertise is essential, consider supplementing the questionnaire with targeted interviews or workshops with key stakeholders. This allows for exploration of issues in greater depth than a questionnaire permits and can generate insights that inform both the questionnaire design (if conducted beforehand) and the interpretation of questionnaire results (if conducted alongside or after).

Summary

Structured questionnaires are the most effective tool for gathering and analysing feedback on complex documents. They ensure respondents engage with the content, produce data that can be systematically compared and analysed, accommodate both professional and community respondents, and provide a transparent and auditable process. The case studies in this guide illustrate vividly what is at stake: well-designed structured processes have saved projects from costly design errors and enabled technically important concerns to reach decision-makers; poorly designed or inadequately analysed processes have produced misleading reports, overturned decisions, and in at least one case, legal challenge.

When supported by a purpose-built platform like Simply Stakeholders, the submissions analysis process becomes significantly more efficient and rigorous. Automatic issues detection and sentiment analysis accelerate the initial triage of responses; qualitative annotation and reporting tools streamline the production of analysis reports; stakeholder segmentation enables disaggregation by type and influence; and a complete auditable record protects the organisation against future challenge. Together, these capabilities address the core risks identified in the failure case studies — poor campaign identification, inadequate expert submission weighting, and indefensible reporting methodology.

Online engagement platforms remain valuable for awareness-raising, community engagement, and reaching broad audiences. Where both are used together, the questionnaire should be the authoritative source of analysable submission data, with the engagement platform serving to drive participation and public awareness, and Simply Stakeholders providing the analytical backbone that turns raw responses into defensible, decision-ready insights.

Simply Stakeholders is a smart (but simple) stakeholder relationship management tool that makes it easier than ever to analyze your stakeholders and visually map them based on 6 different criteria, as well as your stakeholder relationships.

Not only that, but our built-in AI-powered sentiment analysis enables up-to-date insights on your stakeholders throughout the entire project.

Interested in learning more? Take a look at our other features or contact us to request a demo.

Book a Personalized Demo Interested in seeing what you can do with Simply Stakeholders? We’re here to help! Get a Demo

 

Simply Stakeholders is a smart (but simple) stakeholder relationship management tool that makes it easier than ever to analyze your stakeholders and visually map them based on 6 different criteria, as well as your stakeholder relationships.

Not only that, but our built-in AI-powered sentiment analysis enables up-to-date insights on your stakeholders throughout the entire project.

Interested in learning more? Take a look at our other features or contact us to request a demo.