PerceptionX

Employer brand attribute scorecard (Culture, Leadership, Compensation, Career Opportunities, Wellbeing & Balance, …) for the latest measured quarter(s): % of answers discussing each attribute, positive-sentiment %, share of all themes, change in points vs the previous measured period, and the top themes behind each. Use for deep-dive employer brand analysis. For a market-filtered view or example quotes use get_attribute_themes. Results carry _meta.periods (every measured quarter in the window) and lead with percentages; raw counts are under sample_size and are context only.

get_attribute_breakdown

How each tracked AI platform (ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, and Claude from September 2026) perceives the company in the latest measured quarter(s): visibility % and positive-sentiment % per platform. Useful for 'which platform mentions us least / is least favorable'. Results carry _meta.periods (every measured quarter in the window) and lead with percentages; raw counts are under sample_size and are context only.

get_model_breakdown

Recurring themes extracted from AI answers in the latest measured quarter(s): each theme with the % of answers mentioning it, its positive-sentiment %, the attributes it belongs to and which AI platforms raised it — plus an attribute summary (% of answers discussing each attribute, sentiment %, change vs the previous measured period). For a market-specific view prefer get_attribute_themes. Results carry _meta.periods (every measured quarter in the window) and lead with percentages; raw counts are under sample_size and are context only.

get_themes

Use for questions like 'what's our culture like in India?', 'how is our compensation perceived in Germany?', 'how does AI describe us for finance roles?' or 'why did wellbeing change?'. Filter by market (location) and/or job function (job_function); set by_job_function=true to see which functions hear an attribute most. Returns, per employer-brand attribute and per measured quarter: the % of answers discussing the attribute, its positive-sentiment %, its share of all themes, and the change in points vs the previous measured period. When a single attribute is requested it also returns real example themes with quote snippets and which AI platform said them, plus the sources cited in the answers that discuss that attribute (% of those answers citing each domain, with top_pages — the most-cited page URLs to link — association, not cause). Numbers match the PerceptionX dashboard. Attribute ids: mission-purpose-impact, compensation, company-culture, leadership, job-security, career-opportunities, wellbeing-balance, inclusion, innovation, application-communication, candidate-feedback, interview-experience, onboarding-experience (common aliases like 'pay', 'culture' or 'work-life balance' also resolve). Results carry _meta.periods (every measured quarter in the window) and lead with percentages; raw counts are under sample_size and are context only. Quote _meta.period_range and the matched market spellings when precision matters.

get_attribute_themes

Series by measured quarter for one metric — 'visibility' (% of answers mentioning the company), 'sentiment' (positive-sentiment %), or 'citations' (citations per answer) — optionally filtered by market and/or job function. Returns the series plus change in points vs the previous measured period and since the first. Every listed period is a complete collection wave; a period is marked '(in progress)' only while its wave is still being collected. Use for 'is our sentiment in Germany improving?', 'visibility trend this year'. Results carry _meta.periods (every measured quarter in the window) and lead with percentages; raw counts are under sample_size and are context only.

get_trends

Competitors AI platforms bring up when answering about the company, in the latest measured quarter(s): % of answers naming each competitor and % naming them alongside the company. Brand scope by default. For a market or attribute lens ('who is our top competitor for pay?') use get_competitor_landscape. Results carry _meta.periods (every measured quarter in the window) and lead with percentages; raw counts are under sample_size and are context only.

get_competitors

Compare scorecards (EPS, sentiment %, visibility %, relevance) side by side for 2–10 individual profiles — markets, subsidiaries, or brands within the organization. Each profile is reported at ITS OWN latest measured period and labeled with it; the coverage note says when periods differ.

compare_companies

Just the scorecard for the latest measured quarter: EPS, positive-sentiment %, visibility %, relevance, change in points vs the previous measured period, and sample sizes. EPS = 50% sentiment + 30% visibility + 20% relevance. Numbers match the dashboard (brand scope by default).

get_company_metrics

The dashboard's default view in one call: for the LATEST measured quarter of the brand scope — EPS, positive-sentiment %, visibility %, relevance, and change in points vs the previous measured period — plus the top attributes by % of answers discussing them, top themes, top competitors and top sources (each as % of answers). Use this as your default first tool when a user asks how a company is doing. For history use get_trends; for a market use the market-aware tools. Results carry _meta.periods (every measured quarter in the window) and lead with percentages; raw counts are under sample_size and are context only.

get_company_overview

List all companies/market profiles in the user's organization. Always call this first if you don't already know the company IDs. Returns id, name, country, industries, latest_period (the profile's most recent measured quarter), measured_periods (how many quarters have data) and total_responses (a size cue for choosing a profile). Same-name profiles are one brand measured per market; the other tools aggregate them like the dashboard.

list_companies