Managing Keywords - Brand variations and keyword management
Written By Ashish Mishra
Last updated 6 months ago
You can add variation of keywords like
‘Compare best customer support software solutions’
‘Top 10 customer support software in {{location}}’
‘Ways to support customer interactions"‘
Mention Detection
Continuous Scanning: 24/7 monitoring across all platforms
Natural Language Processing: Advanced NLP to understand context
Entity Recognition: Precise brand identification in conversations
Confidence Scoring: Quality assessment of each mention
Detection Methods
Direct Mentions:
"I recommend [Brand Name] for this use case"
Indirect References:
"The software from [Company] works well"
Competitive Comparisons:
"[Brand A] vs [Brand B] - here's my analysis"
Contextual Mentions:
"For CRM solutions, consider [Brand Name]" Quality Filters
Relevance Scoring: Filters out tangential mentions
Context Analysis: Ensures mentions are meaningful
Spam Detection: Removes artificial or manipulated content
Duplicate Removal: Prevents counting same mention multiple times
3. Data Collection & Analysis
Mention Metadata
Each mention captures:
Core Data:
- Timestamp of mention
- AI platform source
- Full conversation context
- User query that triggered mention
- AI response containing brand
Analysis Data:
- Sentiment score (0-100%)
- Confidence level (0-100%)
- Relevance score (0-100%)
- Competitive context
- Geographic indicators (when available)
Performance Data:
- Response ranking position
- Mention prominence in response
- Associated recommendations
- User follow-up questions Advanced Analytics
Trend Analysis: Historical patterns and forecasting
Sentiment Evolution: How perception changes over time
Competitive Intelligence: Share of voice vs competitors
Topic Clustering: Common themes in brand mentions
Platform Performance: Effectiveness across different AI systems