BrandScore measures open-market employer naming, favourability and direct employer narratives across six AI experiences. National and multinational employers can explore supported global markets and bespoke role and skill studies. Five selected competitors receive deeper analysis; separate employer-content benchmarking is an additional capability.
5additional bespoke scans monthly with Annual Monitor
Standard configuration: 117 questions × six experiences × two samples = 1,404 planned executions, not guaranteed successful answers. Bespoke studies have their own scope; evidence checks and analysis are additional.
DISCOVER · COMPARE · UNDERSTAND · ACT
What you will discover.
Market-wide employer naming and direct employer narratives are separate behaviours. Inspect the evidence behind each, with deeper comparisons for five selected employers.
01
DISCOVER
Are candidates finding you?
AI Visibility & Competitor Market Maps
Understand which employers candidates may hear about before reaching a careers site.
What it measures
Employer naming in open-market candidate answers across six AI experiences. Maps show the most visible employers; additional named employers remain in the wider analysis.
What you learn
Your observed presence in the selected market, not just against your five chosen employers. Naming is not endorsement.
Why it helps
Understand which employers candidates may hear about before reaching a careers site.
AI Answer Position Analysis
Inspect the context behind a presence figure, rather than treating every mention alike.
What it measures
Where your employer is mentioned within an answer: early, later or briefly. This is not an independent employer ranking.
What you learn
Whether a mention is prominent or incidental within the retained response.
Why it helps
Inspect the context behind a presence figure, rather than treating every mention alike.
Candidate-Priority Analysis
Connect employer intelligence to the questions your target talent may ask.
What it measures
Naming and descriptions across candidate priorities including growth, leadership, flexibility, wellbeing, pay, development and job security.
What you learn
The saved answer evidence for each priority, including associations not observed in the analysed answers.
Why it helps
Connect employer intelligence to the questions your target talent may ask.
02
COMPARE
How do you compare with talent competitors?
Competitor Intelligence
Give competitive discussions a wider talent-market context.
What it measures
Market-wide employer discovery alongside deeper comparison with five selected competing or aspirational employers.
What you learn
Who appears in the measured market and how your focused comparison group differs. These are observed outcomes, not deliberate replacements.
Why it helps
Give competitive discussions a wider talent-market context.
Head-to-Head Answer Presence
Inspect comparable examples instead of drawing conclusions from unrelated answers.
What it measures
Qualifying answers in which you and a selected competitor are both named, with observed presence compared in that shared population.
What you learn
What the saved shared answers show. Thin evidence is not a conclusive comparison; being named is not being endorsed.
Why it helps
Inspect comparable examples instead of drawing conclusions from unrelated answers.
AI Narrative Comparison vs Competitors
Understand the employer story candidates are being told, not merely how often a name appears.
What it measures
Themes, strengths, concerns and descriptions in direct employer questions, separately from open-market discovery.
What you learn
Differences between AI experiences and employers, potentially contradictory narratives and supporting saved excerpts.
Why it helps
Understand the employer story candidates are being told, not merely how often a name appears.
03
UNDERSTAND
What is AI telling candidates — and what supports it?
AI Favourability
Separate how an employer is described from how often it is named. A favourable tone is not automatically an endorsement.
What it measures
The tone of saved employer-specific statements where sufficient eligible, graded evidence is available.
What you learn
Whether descriptions lean favourable, mixed or cautious. Missing, incomplete or ungraded evidence is unavailable, not neutral.
Why it helps
Separate how an employer is described from how often it is named. A favourable tone is not automatically an endorsement.
Employer Voice vs AI Voice
Identify differences to investigate. A missing message does not prove your content is inadequate or explain the cause.
What it measures
Your published employer messaging alongside retained AI descriptions.
What you learn
Messages reflected, not observed or contradicted in the analysed answers; technical failures remain unavailable evidence.
Why it helps
Identify differences to investigate. A missing message does not prove your content is inadequate or explain the cause.
Employee Reviews vs AI Voice
Understand differences worth investigating without assuming AI is wrong or promising changes to its answers.
What it measures
How closely each engine’s employer narrative matches collected employee reviews across Candidate Priorities, with Glassdoor and Indeed assessed separately. Compares meaning, themes and emphasis—not just whether descriptions are positive or negative.
What you learn
Where narratives closely match, partly match or materially differ, with insufficient evidence kept neutral—not treated as a poor match. Inspect original AI passages, supporting review excerpts, relevant review counts and actual date ranges.
Why it helps
Understand differences worth investigating without assuming AI is wrong or promising changes to its answers.
Sources, Citations & Evidence Checks
Inspect potential gaps or contradictions without treating a citation as proof of support or causal influence.
What it measures
Citations returned by an AI experience. Page readability and claim-support checks are separate, and apply only in eligible evidence and Readiness workflows.
What you learn
Which sources accompany answers and which relevant passages were checked, with unsupported or unverified material kept distinct. Not every citation is checked for claim support.
Why it helps
Inspect potential gaps or contradictions without treating a citation as proof of support or causal influence.
AI Readiness Assessment
Understand what could be verified and where evidence remains uncertain, rather than assuming every experience receives identical tests.
What it measures
Eligible AI answers and employer evidence retrieval, alongside separate technical accessibility and structure checks. GPT-5, Gemini and Perplexity are scored; Claude is contrast-only. Google experiences are excluded.
What you learn
Live-retrieval and memory-only behaviour are distinguished. A retained memory answer does not prove that a page was read live; failed checks do not prove absence.
Why it helps
Understand what could be verified and where evidence remains uncertain, rather than assuming every experience receives identical tests.
EVP Trust
Explore the support for employer promises without certifying every employee's experience. Not advertised as a standard one-off inclusion.
What it measures
Employer Value Proposition statements against the supporting evidence and eligible AI answers available in the relevant product.
What you learn
Statement-level evidence and differences between experiences, with scope and uncertainty retained.
Why it helps
Explore the support for employer promises without certifying every employee's experience. Not advertised as a standard one-off inclusion.
04
ACT
What should your team investigate next?
Findings & Next Steps
Use a single assessment as a starting point, not proof of a sustained trend or cause. Detailed advice depends on your package.
What it measures
Major observations alongside the retained report evidence and applicable limitations.
What you learn
What was observed, the supporting evidence, why it matters and what your team should investigate next.
Why it helps
Use a single assessment as a starting point, not proof of a sustained trend or cause. Detailed advice depends on your package.
From national employers to multinational organisations, BrandScore supports Global and country-specific employer intelligence within supported markets.
A bespoke Talent Market study focuses on one role family or skill group — optionally narrowed by location, priorities or competitor group. It addresses a particular talent challenge rather than replacing your general employer brand baseline.
Annual Monitor includes five additional bespoke studies per month, separate from its 26 scheduled assessments. Confirm the 90-day allowance in your programme scope.
Programme and annual pricing are enquiry-based. Confirm bespoke allowances, recommendations, Brandi access and separately scheduled employer-content benchmarking in your agreed package. Reinforcement and TalentXP are not standard Monitor inclusions.
Active monitoring
What active monitoring helps you understand
Active monitoring combines repeated measurement with analysis and findings; detailed recommendations depend on the package. It is more than a dashboard displaying changing numbers.
Visibility
Whether AI includes your organisation when candidates ask about employers without supplying your name.
Reputation
How AI describes your culture, careers, benefits and employee experience.
Competitor movement
Which employers are named in the measured market and how those appearances change.
Sources and evidence
Returned citations, plus separate readability and support checks in eligible evidence workflows. Not every citation is claim-verified.
Competitor learning
What other employers publish across careers sites, job ads and employer content, and which approaches deserve consideration.
Priorities
Where your team or agency should focus its next action.
From a starting assessment to ongoing intelligence
Establish the starting position. Follow movement through seven scans across 90 days. Compare five chosen competing or aspirational employers. Examine AI descriptions, sources and evidence differences. Review the patterns and receive prioritised recommendations after the full 90-day period, where included in your package.
Initial findings follow the first scan, with fortnightly updates after each scan. Consolidated recommendations come after the full 90 days (seven scans), not monthly or after every scan. In the 90-Day Programme, Monitor includes scan results; Discovery adds the final recommendations and advisory review.
Why ongoing measurement matters
Your employer brand visibility can move without your content changing
Google rankings and paid search positions have always changed. Employers could still control the message published through their adverts and destination pages.
AI adds another source of change. Answers include employers and generate a description for the question being asked. Your website can remain unchanged while your visibility, the sources cited and the competitors appearing beside you change.
An audit establishes your position during the assessment. Active monitoring helps you follow what happens afterwards and decide when to respond.
An average eight-day gap. Visibility movement of 7.6 percentage points.
Across 134 repeat comparisons covering 22 employers, BrandScore recorded average visibility movement of 7.6 percentage points between measurements averaging eight days apart. 22% of comparisons moved by at least 10 percentage points.
Observed movement can reflect changes to AI systems, available evidence, competitors or answer variation. These results do not establish what caused each change. This is a historical four-engine repeated-measurement subset, not the full employer sample or a current six-experience study.
AI findings and content benchmarking, examined side by side
AI analysis
Measures answer presence, descriptions, favourability, competitors and cited sources across six AI experiences. Being named is not the same as being endorsed.
Separate content benchmarking
Examines careers sites, job adverts and other employer-controlled content across the selected employers, highlighting approaches worth considering.
A competitor’s published content does not, by itself, establish why AI includes that employer. Examining both views supports better decisions about your team’s next action.
Active monitoring describes the measurement approach. Monitor and Monitor + Reinforce remain distinct packages: Reinforcement is a separate part of the offer, not a promise of improved visibility or proof that your activity caused a change.
Specialist analytics for your team and your agency.
Built exclusively for Talent Acquisition and Employer Brand teams and the agencies that support them.
Created by former in-house Talent Acquisition and Employer Brand leaders.
BrandScore works alongside employers and employer brand agencies, providing specialist analytics to guide employer brand strategy. Use findings for priorities, content discussions and leadership briefings; an existing agency relationship does not need to change.
AI findings and public-content benchmarks remain distinct. Inspect careers sites, job adverts and employer content for useful examples, without treating those examples as proof of why AI names a competitor.
Candidates can now ask AI platforms which employers to consider, what working for a named organisation may be like, and how employers compare. That creates an employer reputation channel beyond careers sites, job boards and review platforms.
BrandScore separates two different behaviours: open-market questions show whether an employer is named, while direct employer questions reveal the narrative each engine gives candidates. This distinction keeps AI employer visibility monitoring separate from employer narrative analysis.
Different from traditional brand tracking
Traditional employer brand tracking focuses on awareness, campaigns, careers-site engagement and reviews. AI Answer Presence observes whether an employer appears when candidates ask open questions, then benchmarks that answer presence against employers competing for the same talent.
Direct-perception analysis then examines tone, recurring associations and supporting evidence without treating a mention as an endorsement.
Evidence influences what AI can say
AI answers can draw on careers content, reviews, third-party publications, structured data and other publicly available sources. BrandScore examines the citations and evidence visible in those answers so teams can distinguish an intended employer narrative from what external sources reinforce.
Evidence work can improve clarity, consistency and accessibility of public information. Subsequent answers are observations, not proof that a particular content change caused an improvement.
Why ongoing measurement matters
AI-generated answers can vary by engine, prompt, market and date. Ongoing monitoring reveals changes and persistent patterns that a one-off check can miss, while talent competitor benchmarking gives each observation useful market context.
Technical AI Readiness complements this measurement by assessing whether the employer information available online is accessible and structured for machine interpretation.
Where included in your package, Brandi is a conversation with your employer intelligence. Brandi helps you understand the findings, explore the evidence and turn your report into a briefing for your team, leadership or agency.
Make sense of your results
Ask about AI Answer Presence, employer narratives and talent competitors, with explanations grounded in your report.
Brief your stakeholders
Create a bespoke briefing for your head of marketing, HR leadership or executive team, with figures checked against your report.
Take the evidence with you
Download report-based Word documents and CSV files for your team to review and share.
Your results, explained by Brandi
90-Day, Monitor and Monitor + Reinforcement subscribers receive a narrated overview with each report. This example uses fictional data.
