Follow how often AI names your organisation, how it describes your employer brand and which sources it cites. Seven fortnightly scans across 90 days put your position alongside five chosen employers, combining repeated measurement with evidence analysis, competitor learning and consolidated recommendations where included.
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 repeated observation adds.
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
Follow which employer appearances persist or change in comparable markets.
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
Examine whether answer placement persists across repeated samples and assessments.
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
Distinguish recurring priority associations from isolated answers.
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
Follow changes in employer naming while keeping market and question scope consistent.
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
Check whether shared-answer patterns recur when sufficient qualifying evidence exists.
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
Follow which descriptions persist, change or differ between experiences.
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
Compare tone only where evidence thresholds and measurement scope remain compatible.
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
Examine which messages are reflected consistently across comparable assessments.
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
Planned fortnightly AI comparisons use the latest saved review evidence; monthly review refreshes and quarterly full re-checks update that evidence separately. Automatic comparisons and refreshes are not yet connected.
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
Follow changes in the cited source mix without assuming a source caused an answer.
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
Review comparable evidence findings and per-service coverage; scores require at least 90% combined usable coverage across scored services.
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.
04
ACT
What should your team investigate next?
Findings & Next Steps
Discovery adds consolidated recommendations, advisory review and leadership reporting after all seven assessments; Monitor retains its scan-results scope.
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.
Use the findings with your team and agency.
Specialist employer analytics supports your strategy rather than replacing it. Compare a starting assessment with subsequent observations, inspect competitor examples and discuss evidence gaps with the people responsible for your employer brand.
Candidates increasingly ask AI platforms which employers to consider before they reach a careers site. Whether an employer is named in those answers is a different question from what an engine says when asked about that employer directly.
Being named is not the same as being endorsed. BrandScore reports observed answer presence as a visibility signal, and keeps employer narrative analysis as a separate view.
What ongoing monitoring adds
AI answers vary by engine, prompt wording, market and date. Repeated measurement across a consistent prompt set helps your team examine movement and persistent patterns, without assuming what caused a change.
Each measurement is placed alongside talent competitor benchmarking, so an observed position always carries market context.
How visibility connects to evidence
Inspect the sources returned alongside AI answers and the relevant passages checked in eligible evidence workflows. A recorded citation is not automatically a readable page or support for a claim; neither establishes causal influence.
Visibility monitoring sits alongside Technical AI Readiness, which assesses whether public employer information is accessible, structured and supported by evidence AI systems can interpret.
GPT-5, Gemini and Perplexity contribute to scored AI Readiness; Claude provides contrast, and the two Google experiences are excluded. Memory-only answers and verified live retrieval remain distinct.
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.
