AI Monitors Your Brand
Your brand is being discussed online right now — in reviews, social media, forums, news articles, and competitor comparisons. AI monitors all of it continuously, surfaces what matters, and alerts you before small issues become reputation crises.
The Full Coverage Map
Review platforms
G2, Capterra, Trustpilot, App Store, Google My Business, and industry-specific review sites. AI processes every new review: sentiment classification (positive, neutral, negative), topic extraction (what aspect of the product or service is being discussed), trend identification (is negative sentiment increasing in a specific category?), and comparison mentions (what competitors are mentioned alongside your brand?).
Social media mentions
Twitter/X, LinkedIn, Instagram, Facebook, and TikTok mentions of your brand name, product names, and key personnel. AI distinguishes between: genuine customer experience mentions (high priority — respond), industry discussions where your brand is mentioned (medium priority — engage when appropriate), automated or bot mentions (filter out), and influencer mentions (flag for relationship management).
News and media coverage
News articles, blog posts, and industry publications mentioning your brand. AI classifies coverage: positive feature or case study (amplify), neutral mention (monitor), negative coverage (urgent response evaluation), and competitor comparison (analyse for positioning implications). Weekly media coverage digest with sentiment summary and recommended actions.
Forums and community discussion
Reddit, Product Hunt, Hacker News, Quora, and industry-specific forums where your brand or product category is discussed. Often where genuine unfiltered user sentiment lives — the criticism that does not appear in official reviews because users do not expect you to be reading. AI surfaces this intelligence without requiring manual monitoring of dozens of communities.
Make.com and AI Integration
Set up mention monitoring sources
Use Google Alerts for news and blog mentions (free, immediate). For social media, use Mention.com or Brand24 (paid, more comprehensive). For review platforms, use platform APIs where available or web scraping via Make.com for platforms without APIs. Configure each source to push new mentions to your Make.com monitoring scenario.
Build the AI classification workflow
In Make.com, route each new mention to a Claude analysis module. Prompt: Classify this brand mention. Brand: [your brand]. Mention text: [mention]. Classify: (1) Sentiment (positive, neutral, negative, mixed). (2) Topic (product quality, customer service, pricing, feature request, competitor comparison, other). (3) Priority (urgent — requires response within 2 hours, standard — respond within 24 hours, monitor — no action required). (4) Recommended action (respond publicly, respond privately, engage positively, escalate to leadership, no action). Return as structured JSON.
Route based on classification
Urgent negative mentions route to a Slack channel with immediate notification to the social media manager or customer success lead. Standard mentions route to a daily digest. Positive mentions route to a database for use in marketing (case studies, testimonials, social proof). Competitor mentions route to the competitive intelligence channel. Every mention is handled appropriately without manual triage.
Generate weekly brand health reports
At the end of each week, a scheduled Make.com workflow aggregates all mention data and passes to Claude: Generate a weekly brand health report from this mention data. Include: overall sentiment trend, top positive themes mentioned, top negative themes mentioned, most mentioned competitors, any emerging issues that need attention, and 3 recommended actions for next week. Deliver to the marketing leadership team every Monday morning.
The Escalation Framework
Brand crises escalate fastest when they are not detected early. AI identifies crisis signals: sudden increase in negative mention volume, a specific complaint being amplified by high-follower accounts, coordinated negative posting patterns, or a negative article being shared extensively. When these patterns are detected, the system alerts leadership immediately rather than waiting for the weekly digest.
When a crisis is identified, AI generates the initial response framework: a factual summary of what is being said, the key stakeholders involved, recommended communication stance (acknowledge and investigate, factual correction, proactive apology), draft holding statement, and escalation recommendations. The response team receives a structured brief rather than having to assemble the picture from raw mentions.
How is AI brand monitoring different from Google Alerts?
Google Alerts monitors news and indexed web content only, with significant delays and gaps in coverage. AI brand monitoring via Make.com and Claude adds: real-time social media tracking, review platform monitoring, sentiment analysis, topic classification, and automated routing and action recommendations. Google Alerts tells you what was published; AI brand monitoring tells you what it means and what to do about it.
Can AI respond to negative reviews automatically?
AI can draft responses to negative reviews for human review and posting — not for automatic posting without human approval. Automated responses to negative reviews risk making situations worse if the AI misunderstands the context, applies an inappropriate tone, or commits to actions the business cannot fulfil. AI generates the draft; a human approves and posts. This combines the speed of AI with the judgment and accountability of a human.
Want Brand Monitoring and Reputation Automation Built?
SA Solutions builds Make.com brand monitoring systems that track mentions across all channels, classify by sentiment and priority, and deliver weekly brand health reports — automatically.
