How do I set up a source tracking database to monitor competitors and surface mentions from key industry sources?

A good source-tracking database is basically a structured pipeline for finding, storing, classifying, and surfacing competitor and industry mentions. The easiest way to set it up is to design it around a few core entities and a repeatable update process.

1) Define what you want to track

Start by listing:

• Competitors: company names, product names, executives, subsidiaries, common abbreviations
• Industry sources: trade publications, analyst firms, blogs, newsletters, forums, social accounts, podcasts, regulatory sites, review sites
• Mention types:
  • Product launches
  • Funding
  • Partnerships
  • Hiring
  • Pricing changes
  • Customer wins/losses
  • Earnings / financial disclosures
  • M&A
  • Security incidents
  • Analyst commentary
• Priority level: which competitors and sources matter most

This becomes your tagging scheme.

2) Choose your database structure

A simple relational database works well. You can use Airtable, Notion, Google Sheets, or a real database like PostgreSQL.

Core tables

entities

Stores competitors and related names.

Fields:

• entity_id
• entity_name
• entity_type (competitor, product, executive, parent company)
• aliases
• website
• priority
• notes

sources

Stores publication/source metadata.

Fields:

• source_id
• source_name
• source_type (news, blog, social, analyst, regulatory, forum)
• url
• rss_url
• region
• credibility_score
• priority

mentions

Stores each discovered mention.

Fields:

• mention_id
• entity_id
• source_id
• title
• url
• published_at
• found_at
• mention_type
• sentiment
• summary
• relevance_score
• status (new, reviewed, archived)

topics

Optional, for categorizing themes.

Fields:

• topic_id
• topic_name
  Examples: pricing, partnerships, AI, hiring, regulation, security

mention_topics

Join table for many-to-many mapping between mentions and topics.

Fields:

• mention_id
• topic_id

3) Build your source ingestion workflow

You need a way to collect mentions from each source.

Common ingestion methods

• RSS feeds for publications and blogs
• API feeds for platforms that allow them
• Web scraping for sites without RSS/API access
• Google Alerts / Talkwalker / Mention / Meltwater for broad web coverage
• Newsletter parsing for key industry newsletters
• Manual entry for high-value items from conferences, calls, or reports

Suggested workflow

1. Pull new content from sources on a schedule
2. Extract title, date, author, URL, full text if available
3. Match text against competitor/entity aliases
4. Score relevance
5. Store matching items in mentions
6. Notify stakeholders of high-priority mentions

4) Use keyword and alias matching

Competitors are often mentioned under variations of their name.

Example:

• “Acme”
• “Acme Corp”
• “Acme.ai”
• product names
• executive names

Maintain a robust alias list for each entity. You can also add:

• common misspellings
• ticker symbols
• code names
• abbreviations

For better precision:

• require proximity between entity name and relevant keywords
• exclude false positives with negative keywords
• maintain a “do not match” list

5) Add scoring and prioritization

Not all mentions are equal. Use a relevance score based on:

• source credibility
• source priority
• whether the source is a key industry outlet
• whether the mention is in the headline
• whether multiple competitors are mentioned
• mention type
• recency
• sentiment or impact

Example scoring:

• +5 if source is a top-tier industry publication
• +4 if competitor appears in headline
• +3 if mention type is strategic, like funding or partnership
• +2 if source is high-trust
• -3 if likely false positive

Then sort alerts by score.

6) Create dashboards and alerts

You’ll want visibility, not just storage.

Useful views

• New mentions by competitor
• Mentions by source
• Mentions by topic
• Mentions by week/month
• High-priority mentions requiring review
• Share of mentions by competitor

Alerts

Send alerts when:

• a Tier-1 competitor is mentioned
• a high-priority source publishes something
• a mention contains certain trigger words like “launch,” “acquisition,” “pricing,” “lawsuit,” “breach”

Delivery options:

• Slack
• Email digests
• Teams
• Dashboard widgets

7) Standardize review and enrichment

After ingestion, someone should verify and enrich records.

Add fields like:

• reviewed_by
• reviewed_at
• confirmed_entity
• summary
• business_impact
• action_required

This keeps the database useful over time instead of just being a raw feed.

8) Keep source lists curated

Quality matters more than volume.

Regularly:

• remove low-value sources
• add new industry sources
• adjust source priority
• update aliases when competitors rebrand or launch new products

9) A practical MVP setup

If you want something simple and fast:

Option A: No-code

• Airtable base with tables for entities, sources, mentions
• RSS + email parsing via Zapier/Make
• Slack alerts for Tier-1 mentions
• Weekly digest view

Option B: Lightweight custom stack

• PostgreSQL
• Python ingestion scripts
• RSS/web scraping jobs on a scheduler
• Text matching with a simple rules engine
• Dashboard in Metabase or Retool

10) Example mention pipeline

1. Source article is fetched
2. Text is scanned for competitor aliases
3. Relevance is scored
4. Record is created in mentions
5. Topic tags are assigned
6. If score > threshold, send Slack alert
7. Analyst reviews and marks as confirmed or false positive

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If you want, I can also give you:

1. a sample database schema,
2. a no-code Airtable setup, or
3. a Python/PostgreSQL design with example queries.