Brand Monitoring

Lesson 3 of 4

Configuring Sentiment Analysis

Estimated time: 7 minutes

Configuring Sentiment Analysis

Raw mentions are useful, but volume alone doesn't tell you what matters. A hundred positive tweets and one viral negative Reddit post have very different urgency levels. In this lesson, you'll configure OpenClaw to analyze sentiment, score urgency, and prioritize what needs your attention.

How Sentiment Analysis Works

For every mention OpenClaw collects, the AI evaluates:

  Incoming Mention          AI Analysis              Scored Output
  ┌──────────────┐        ┌──────────────────┐     ┌───────────────────┐
  │ "Broke out   │───────>│ Sentiment: 😡    │────>│ Score: -0.8       │
  │  after using │        │ Negative, strong │     │ Urgency: HIGH     │
  │  GlowUp"    │        │                  │     │ Reach: 67 upvotes │
  └──────────────┘        │ Topics: product  │     │ Topic: product    │
                          │ defect, skin     │     │ Action: respond   │
                          │ reaction         │     │ within 1 hour     │
                          └──────────────────┘     └───────────────────┘

Configure sentiment scoring

Set up OpenClaw's sentiment analysis parameters:

openclaw chat "Configure brand sentiment analysis:

Score each mention on a scale from -1.0 (very negative)
to +1.0 (very positive). Use these guidelines:

Positive signals:
- Recommending to others, repurchase intent
- Praise for specific product attributes
- Comparison wins against competitors

Negative signals:
- Skin reactions, allergic responses (HIGHEST PRIORITY)
- Product quality issues (packaging, texture, smell)
- Price complaints
- Customer service complaints

Neutral:
- Questions about the product
- Unboxing without opinion
- Brand mention in a list without commentary

Also classify each mention by topic:
product-quality, customer-service, pricing,
comparison, recommendation, complaint, question"
✅ Sentiment analysis configured

  Scale: -1.0 to +1.0
  Topics: 7 categories defined
  Priority: Skin reactions flagged as highest urgency

Set urgency levels

Not all negative mentions are equally urgent. Configure urgency tiers:

openclaw chat "Set urgency levels for brand mentions:

🔴 CRITICAL — Respond within 1 hour:
- Health or safety concerns (skin reactions, allergies)
- Viral potential (post growing fast, 100+ engagements)
- Media coverage (journalist or publication mention)
- Influencer mention with negative sentiment (10K+ followers)

🟡 HIGH — Respond within 4 hours:
- Direct complaints on public platforms
- Negative review on Amazon or Trustpilot
- Competitor comparison where we lose
- Feature request from multiple users

🔵 MONITOR — Include in daily digest:
- Neutral mentions and questions
- Positive mentions (celebrate internally)
- Industry trend mentions
- Competitor activity

⚪ LOW — Weekly summary only:
- Generic brand mentions with no sentiment
- Old content resurfacing
- Spam or bot activity"

Set up the daily sentiment digest

Create a scheduled digest that summarizes your brand health:

openclaw cron add \
  --name "Brand Sentiment Digest" \
  --cron "0 9 * * *" \
  --tz "America/New_York" \
  --session isolated \
  --message "Generate my daily brand monitoring digest:

1. Sentiment summary: overall score for the last 24 hours
   compared to the 7-day average. Show trend arrow.

2. Mention volume: total mentions by source
   (Twitter, Reddit, News, Reviews)

3. Top mentions: 5 most impactful mentions (by engagement)
   with sentiment score and one-line summary

4. Alerts: any CRITICAL or HIGH urgency items still unresolved

5. Competitor watch: notable competitor mentions or launches

6. Topic breakdown: what people are talking about most

Keep it scannable — I should get the full picture in 2 minutes." \
  --announce \
  --channel slack \
  --to "#brand-monitoring"

Here's what the digest looks like:

📊 Brand Digest — Tuesday, Mar 25

Overall Sentiment: 0.72 (↑ from 0.68 7-day avg)
Total Mentions: 31 | Twitter: 18, Reddit: 8, News: 3, Reviews: 2

🔴 CRITICAL (1)
  Reddit r/SkincareAddiction — "Broke out after using GlowUp
  Moisturizer" — ↑ 234, 47 comments — Sentiment: -0.8
  ⚠️ Growing fast. Suggested response drafted.

📈 Top Mentions:
1. @beautyblogger (142K followers): "Best moisturizer of 2025"
   Sentiment: +0.9 | Engagement: 3.2K
2. Byrdie article: "Top 10 Vegan Moisturizers" — listed #4
   Sentiment: +0.6 | Est. reach: 50K
3. r/SkincareAddiction: breakout report (see CRITICAL above)
4. @skincarejunkie: product comparison with RadiantSkin
   Sentiment: +0.3 | Engagement: 890
5. TikTok mention by @glowguru: morning routine feature
   Sentiment: +0.7 | Views: 12K

🏷️ Topics: product-quality (40%), recommendation (25%),
   comparison (15%), complaint (12%), question (8%)

👀 Competitor: RadiantSkin launched a new SPF yesterday.
   Early reception is mixed (sentiment: 0.45).

Track sentiment trends over time

Ask OpenClaw for trend analysis:

30-day trend
openclaw chat "Show me our brand sentiment trend for the past 30 days"
📈 GlowUp Sentiment — 30 Day Trend

Week 1 (Feb 24-Mar 2):  ████████████████░░░░  0.71
Week 2 (Mar 3-9):       █████████████████░░░  0.74
Week 3 (Mar 10-16):     ██████████████░░░░░░  0.62  ↓ Reddit incident
Week 4 (Mar 17-23):     ████████████████░░░░  0.69  ↑ Recovery

Average: 0.69 | High: 0.81 (Mar 7) | Low: 0.54 (Mar 13)

Notable events:
  Mar 7:  Byrdie feature drove +0.1 sentiment spike
  Mar 13: Reddit breakout post caused -0.17 dip
  Mar 14: Our response + replacement offer → recovery began
  Mar 20: @beautyblogger review pushed sentiment back up

Correlate with actions

Sentiment trends are most useful when correlated with your actions. Did a product launch improve sentiment? Did a PR response work? Tracking over time shows you what moves the needle.

Compare against competitors

Monitor competitors alongside your brand:

Competitor comparison
openclaw chat "Compare our sentiment against RadiantSkin and DewDrop Beauty for the past 7 days"
📊 Competitive Sentiment — Last 7 Days

               Mentions  Sentiment  Trend
  GlowUp         31       0.72      ↑
  RadiantSkin     24       0.45      ↓ (new SPF backlash)
  DewDrop         12       0.68      →

Key differences:
  • GlowUp leads in "recommendation" mentions
  • RadiantSkin has 3x more "pricing complaint" mentions
  • DewDrop has strong sentiment but low volume

For industry-specific sentiment, fine-tune OpenClaw's analysis:

openclaw chat "In skincare context, adjust sentiment rules:
- 'Purging' is neutral/positive (expected skin reaction)
- 'Breaking out' is negative (unexpected reaction)
- 'Holy grail' is very positive (+0.9)
- 'Repurchase' is positive (+0.7)
- 'Dupe' is neutral (comparison, not negative)"

Industry jargon matters. A generic sentiment model might flag "purging" as negative, but skincare enthusiasts know it's a normal part of introducing active ingredients.

Break down sentiment per product:

openclaw chat "Show sentiment breakdown by product
for the past 30 days"

This helps identify which products are driving positive or negative sentiment, informing product development decisions.

Knowledge Check

Why would a brand monitoring system classify 'purging' differently from 'breaking out' in a skincare context?

Narwhalexpert
0

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