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) 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?' or 'why did wellbeing change?'. 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. 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