Top AI Prompts for Managing Your Online Reputation

List 5 actionable approaches to boost positive feedback, inspired by the latest customer sentiment reports.

Use Case: Accelerates reputation enhancement by leveraging existing feedback trends.

ClickUp Brain Behaviour: Analyzes linked documents summarizing customer opinions to suggest targeted improvement tactics.

What are the most common complaints and praises in recent reviews for mid-sized companies?

Use Case: Supports focused reputation management by highlighting key customer sentiments.

ClickUp Brain Behaviour: Synthesizes data from internal review summaries; Brain Max can incorporate external public feedback if accessible.

Create a customer-friendly reply template addressing common complaints, referencing tone guidelines in ‘ResponseTone.pdf’.

Use Case: Ensures consistent, empathetic communication across support teams.

ClickUp Brain Behaviour: Extracts tone and style cues from linked documents to generate polished response drafts.

Compare online reputation strategies of top competitors using the ‘Reputation Q2’ report.

Use Case: Enables benchmarking without manual research.

ClickUp Brain Behaviour: Pulls key insights and tactics from internal reports and presents a clear comparative summary.

Identify top review sites and social channels shaping public opinion, referencing analytics dashboards.

Use Case: Guides prioritization of monitoring efforts.

ClickUp Brain Behaviour: Extracts platform data and engagement metrics from linked analytics to inform focus areas.

From the ‘Monitoring Protocol’ doc, produce a step-by-step task list for reputation tracking.

Use Case: Streamlines daily monitoring routines.

ClickUp Brain Behaviour: Transforms documented procedures into an actionable checklist within tasks or docs.

Highlight 3 key themes from recent feedback and social listening reports.

Use Case: Keeps teams informed on evolving customer perceptions.

ClickUp Brain Behaviour: Identifies recurring topics and sentiments from linked research and notes.

Summarize insights from the ‘Market Demographics Q1’ report on reputation drivers.

Use Case: Aligns messaging strategies with audience expectations.

ClickUp Brain Behaviour: Reads survey data and extracts prevalent themes influencing reputation.

Write brief, friendly responses for common queries using style guidelines in ‘BrandVoice.pdf’.

Use Case: Accelerates social engagement with consistent tone.

ClickUp Brain Behaviour: References tone documents to suggest varied reply options.

Outline key updates in platform guidelines and their implications for reply protocols.

Use Case: Ensures compliance and adapts communication approaches.

ClickUp Brain Behaviour: Extracts and condenses policy documents; Brain Max can add public updates if available.

Create placement and messaging rules for regional review platforms, referencing compliance docs.

Use Case: Supports tailored reputation efforts per market.

ClickUp Brain Behaviour: Compiles regional requirements and best practices into a clear checklist.

From incident reports and PR docs, build a structured task list for managing reputation crises.

Use Case: Prepares teams for rapid, organized response.

ClickUp Brain Behaviour: Identifies critical steps and groups tasks by urgency and impact area.

Analyze how leading brands communicate environmental efforts using competitive intelligence docs.

Use Case: Informs messaging refinement and differentiation.

ClickUp Brain Behaviour: Summarizes comparative data into digestible formats like briefs or tables.

Highlight new challenges and sentiment shifts from recent social listening reports.

Use Case: Equips teams to proactively address potential issues.

ClickUp Brain Behaviour: Synthesizes trend data from internal notes and uploaded analytics.

Extract key pain points from Southeast Asia feedback folders focusing on service interactions.

Use Case: Drives targeted improvements in support quality.

ClickUp Brain Behaviour: Prioritizes common issues from survey responses, feedback notes, and tagged tickets.

Specify the online reputation context

Vague prompts yield broad answers. Include details like industry (e.g., “hospitality services” or “tech startups”), reputation challenges (e.g., “negative reviews” or “social media backlash”), or target audience (e.g., “millennials” or “enterprise clients”).

Example: “Generate strategies to improve Google reviews for a boutique hotel facing recent negative feedback.”

Ask for side-by-side analysis

AI excels at contrasting options. Use prompts like “compare X vs Y” to weigh different reputation management tactics, competitor responses, or platform effectiveness.

Example: “Compare the impact of proactive social media engagement versus paid reputation repair services for a small business.”

Frame prompts around goals

Treat your prompt as a mission for AI. Instead of “Suggest reputation ideas,” focus on what you want to achieve:

Example: “Outline a crisis communication plan for a restaurant experiencing a viral negative review.”

Request structured responses

Need a step-by-step plan, message templates, or monitoring checklist? Be explicit. AI delivers better when output format is clear.

Example: “Provide a bullet list of five key actions to respond to negative Yelp reviews effectively.”