Glassdoor Competitive Hiring Intel

Task

Use @Glassdoor/Search CompaniesName it "Glassdoor/Search Companies" and call it with @Glassdoor/Search Companies to find multiple competitors, then @Glassdoor/Get Company OverviewName it "Glassdoor/Get Company Overview" and call it with @Glassdoor/Get Company Overview to pull ratings for each, and @Glassdoor/Get Company ReviewsName it "Glassdoor/Get Company Reviews" and call it with @Glassdoor/Get Company Reviews to understand what employees at each company love and hate. Combine with @LinkedIn/Get Company InsightsName it "LinkedIn/Get Company Insights" and call it with @LinkedIn/Get Company Insights for headcount data, @LinkedIn/Search Jobs by CompanyName it "LinkedIn/Search Jobs by Company" and call it with @LinkedIn/Search Jobs by Company for open roles, and @google_jobsName it "google_jobs" and call it with @google_jobs for salary ranges. Produce a competitive hiring intelligence report.

Example: Compare Snowflake, Databricks, and Fivetran from a talent perspective — who has happier employees, who is hiring more aggressively, and who pays better?

Input

The user will provide 2-5 company names to compare.

Example: "Compare hiring competitiveness of Figma vs. Canva vs. Miro" or "Who wins the talent war: Cloudflare, Fastly, or Akamai?"

Context

What to Compare

Employee satisfaction:

• Overall Glassdoor rating and review count for each company
• Category ratings: culture, compensation, work-life balance, career opportunities
• CEO approval and recommend-to-friend percentages
• Common themes in pros and cons

Hiring activity:

• Current headcount and growth rate from LinkedIn
• Number and types of open roles
• Which departments are hiring hardest (engineering, sales, etc.)

Compensation signals:

• Glassdoor compensation rating for each company
• Salary data from job postings where available
• Compensation-related mentions in reviews (positive or negative)

Analysis Strategy

1. Search Glassdoor for each company and collect IDs
2. Pull company overview for all competitors in parallel
3. Pull 10-15 reviews for each company focusing on recent feedback
4. Get LinkedIn insights for headcount and growth rates
5. Search for open roles at each company
6. Build a side-by-side comparison matrix

What Counts as a Valid Result

• Compare the same data points across all companies — no cherry-picking
• Note when review counts are vastly different (statistical significance matters)
• Flag any companies with suspiciously high or uniform ratings
• Include actual numbers and ratings, not just subjective assessments
• If a company has fewer than 50 reviews, flag the small sample size

Output

Competitive Overview: | Company | Glassdoor Rating | Reviews | CEO Approval | Recommend | Headcount | Growth | |---------|-----------------|---------|--------------|-----------|-----------|--------| | [Company 1] | X/5 | N | X% | X% | N | +X% |

Category Comparison: | Category | Company 1 | Company 2 | Company 3 | Winner | |----------|-----------|-----------|-----------|--------| | Culture | X/5 | X/5 | X/5 | — | | Compensation | X/5 | X/5 | X/5 | — | | Work-Life Balance | X/5 | X/5 | X/5 | — | | Career Growth | X/5 | X/5 | X/5 | — | | Management | X/5 | X/5 | X/5 | — |

Hiring Intensity: Which companies have the most open roles, and in which departments?

Employee Sentiment Summary: For each company, 2-3 sentences capturing what employees consistently say — the good and the bad.

Talent War Verdict: Who is best positioned to attract and retain talent? Who is vulnerable? What would you tell a candidate choosing between these companies?