Feedback Acknowledged, Suggestions Ignored?
There’s a familiar, slightly melancholic phrase echoing through the digital voids of online platforms, customer service portals, and even internal company suggestion boxes: “Thanks for submitting feedback. The suggestion has been automatically ignored.” Or perhaps a variation: “Thanks for submitting feedback the suggestion has been automatically ignored.” It’s a digital shrug, a sigh acknowledged but not acted upon. This common automated response, while perhaps technically accurate in its delivery of a message, often leaves users feeling unheard, frustrated, and skeptical about the true state of feedback loops within organizations.
The Comforting Lie of Acknowledgment
The initial “thank you” is, without question, a well-intentioned and often necessary part of user interface design. It provides immediate feedback, confirming that the system received your input. This brief moment of validation is psychologically important. It interrupts the silence that often follows submitting something potentially vulnerable or critical. However, the phrase “suggestion has been automatically ignored” appended to this gratitude introduces a layer of complexity and potential disillusionment.
For many users, this specific wording confirms a suspicion: their input wasn’t just unheeded, but processed through an automated filter designed to discard it without human intervention. It suggests a system so saturated with inputs, or perhaps one operating under strict constraints, that human review is deemed unnecessary or too costly for most submissions. The word “automatically” here is key. It implies a lack of human judgment involved in the assessment of the suggestion’s merit or relevance.
Consider the user experience. You’ve spent time identifying a problem, proposing a solution, or reporting an issue. You click “Submit.” A polite, automated message appears, acknowledging your effort but simultaneously informing you (or at least implying) that your contribution won’t be examined by a human. This immediate closure, however dismissive, can be jarring. It contrasts sharply with the potential impact of your feedback if it were actually considered.
Moreover, the specific wording “suggestion has been automatically ignored” carries a certain finality. It frames the action not just as a deferral (“not acted upon”) but as an active disregard. While technically true for the automated system’s function, it can feel like a pre-judgment. It subtly communicates that the system is designed to reject suggestions without further ado, which is often far from the case. Sometimes, a suggestion might be acknowledged but requires more information, or it’s being reviewed internally but hasn’t reached a certain stage yet. An automated “ignored” message doesn’t leave room for these nuances.
Why the Automation? The Corporate Calculus
Understanding why companies resort to such automated responses requires looking at the business pressures they face. Implementing robust feedback systems involves significant costs – personnel time, process development, data analysis, and resource allocation. Companies, particularly large ones or those with limited resources, must prioritize.
Cost Efficiency: Manually reviewing every single piece of feedback, suggestion, or reported issue is prohibitively expensive and time-consuming. An automated system can handle a vastly higher volume of submissions quickly and cheaply. This efficiency is crucial for companies managing thousands or even millions of interactions.
Risk Aversion: Companies are often risk-averse. Implementing a suggestion might require changing established processes, potentially exposing the company to unforeseen problems or complaints. Automated systems can filter out suggestions deemed too radical, vague, or potentially damaging, protecting the company from liability or operational disruption.
Volume Over Merit: In the face of overwhelming volume, systems might be designed to prioritize quantity over quality. An automated filter can quickly discard submissions that don’t meet basic criteria (e.g., relevance to the platform, clarity, completeness) without a detailed review. This ensures the feedback received for further analysis is potentially higher quality, but it also means many valid but perhaps less obvious suggestions are filtered out.
Limited Human Resources: Even if a company intends to review feedback, the sheer number of submissions might exceed the capacity of their dedicated team. An automated system acts as a triage mechanism, routing only the most clearly flagged or high-priority items to human reviewers, while acknowledging (automatically) the rest.
However, this focus on efficiency and risk can unfortunately overshadow the core purpose of soliciting feedback: genuine improvement and customer engagement. When feedback is consistently treated as data points to be filtered rather than valuable contributions to be acted upon, the system fails its primary function.
Consequences: Beyond the Feeling of Being Ignored
The experience of receiving “thanks for submitting feedback the suggestion has been automatically ignored” has tangible consequences that extend beyond simple frustration. It impacts user perception, engagement, and the overall health of the platform or service.
Erosion of Trust: Perhaps the most significant consequence is the damage to trust. Users invest effort into providing feedback, expecting it to be considered. When they receive an automated dismissal, it signals that their time and effort are not valued. This breeds cynicism and suspicion. Users may question the company’s commitment to improvement and wonder if any feedback is truly welcome. Trust is a fragile commodity, easily broken by perceived indifference.
Reduced Future Engagement: Frustrated users are less likely to engage again. If submitting feedback feels pointless or leads to disappointment, they will stop offering suggestions or reporting issues. This creates a feedback loop where the company loses valuable insights and the user feels increasingly alienated, reinforcing the negative perception.
Filter Bubble Effect: Users, becoming aware that certain types of feedback are automatically rejected, might learn to self-censor. They might avoid submitting suggestions that are deemed too critical, too innovative, or too likely to be filtered out. This results in a skewed dataset for the company and prevents them from hearing the complete picture.
Potential Missed Opportunities: While automation is efficient, it can also be inflexible. An automated system might miss nuanced suggestions, creative ideas, or complex problem reports that require human interpretation and context. A human reviewer might spot the underlying issue in a vague description or recognize the potential of an unconventional idea that an algorithm might flag as irrelevant. Consistently ignoring suggestions, even if efficiently, risks missing out on valuable opportunities for innovation and improvement.
Employee Morale (Internal Systems): If this applies to internal suggestion systems within a company, the effect can be even more damaging. Employees submitting feedback expecting it to contribute to better processes or products might feel disempowered and undervalued. This can negatively impact morale, engagement, and the company’s reputation as an employer committed to employee voice.
Strategies for Users: Navigating the Automated Landscape
Encountering “thanks for submitting feedback the suggestion has been automatically ignored” can feel disheartening, but users can adopt strategies to maximize the impact of their feedback:
Be Specific and Actionable: While automation might filter out vague or overly broad suggestions, be precise about the problem and propose clear, actionable solutions. Use concrete examples and avoid jargon. This increases the chance that even an automated system might recognize its potential value or route it to a human reviewer.
Check the Platform/Channel: Not all feedback channels are created equal. Some platforms might genuinely have more robust review processes than others. Tailor your submission strategy to the most appropriate channel. For example, reporting a critical bug in an app store review might reach different stakeholders than a general suggestion forum.
Understand the Goal: Clarify what you hope to achieve with your feedback. Are you reporting a problem for resolution, suggesting a feature for enhancement, or seeking information? Framing your feedback clearly can help the system categorize it more effectively, even if the initial review is automated.
Follow Up (If Possible): Some systems allow users to track the status of their feedback. If available, use this feature to follow up, especially if you believe your suggestion is valid and worthy of consideration. Persistence, combined with specificity, might increase visibility.
Seek Human Interaction: Look for direct contact methods offered by the company (e.g., dedicated email addresses, customer service lines, social media handles). While these might also be monitored, there’s a higher chance of human interaction. Clearly state the context of your feedback, mentioning the automated response you received to highlight the need for human review.
Provide Context and Evidence: Backing up your suggestion with data, user quotes, or specific instances can make it harder for an automated system to dismiss it outright. This demonstrates the problem’s prevalence and impact.
The Path Towards Genuine Feedback Loops
The phrase “thanks for submitting feedback the suggestion has been automatically ignored” represents a symptom of a larger issue: the gap between the stated intention to listen and the practical execution of feedback management. While automation offers undeniable benefits in terms of scale and efficiency, it cannot replace the nuanced understanding and genuine engagement that human review provides.
For feedback systems to be effective, companies must strive for a balance. They need to implement efficient