Semantic architecture
Entities, intentions, taxonomies, cornerstone pages and internal relationships.
DOSSIER 301
Algorithmic influence
Being found is no longer enough. You must be understood, selected, cited and accurately represented by algorithmic systems.
Operational briefSEOdiscovery
SXOexperience
LLMOAI citation
Operational brief
Build authority machines can read.
Visibility now spans classical search, generative answers, entity graphs, platforms and conversational interfaces. The goal is not to manipulate rankings, but to organise a coherent, useful and verifiable presence.
AR / DOSSIER 301INDEPENDENT ANALYSIS
MEASUREMENT WORKSHOP
Being cited and being cited accurately are separate measures
Count answers citing the target domain separately from references whose contents support the claim. One answer can contain several links, so the two rates have different denominators.
AI-generated illustration
Fictional example · no measurement of this site or a client
| Indicator | Calculation or threshold | What the result establishes |
|---|---|---|
| Presence in answers | 12 / 40 × 100 = 30 % | 12 of 40 answers cite the domain: 30% presence in this sample. |
| Support among checked references | 15 / 20 × 100 = 75 % | 15 of 20 references support the claim: 75% of checked references. This says nothing about unchecked references. |
From observation to decision
Fix the panel
Keep questions, language, service, mode, dates and repetitions. Include answers with no citation.
Open each reference
Match the exact passage to the claim; record inaccessible links and citations that do not support it.
Compare a constant scope
A change requires the same panel and protocol. Publish counts and exclusions too.
One hundred and twenty answers are not one hundred and twenty questions
Each of 40 questions is repeated three times. There are 36 cited answers and 20 questions cited at least once.
| Observed unit | Fictional data |
|---|---|
| Questions × repeats | 40 × 3 = 120 |
| Cited answers | 36 / 120 = 30 % |
| Questions cited at least once | 20 / 40 = 50 % |
Can the 120 answers be treated as 120 independent questions?
No: retain question and repeat identifiers. 30% describes answers and 50% questions reached at least once. Uncertainty estimation must account for repeated-measure design.
References and method
- Google Search Central · AI features
- Google — Generative AI performance report (Search)
- Bing — AI Performance
Documentation consulted on .
VISIBILITY ARCHITECTURE
Be understood before being recommended.
Entities, evidence, answers, links and structured data must describe the same reality. Consistency improves discovery, experience, recall and the ability of generative systems to cite a source accurately.
Glass panels crossed by red lines of light. Illustrative scene.
02 / Intervention areas
Intervention areas
Reference content
Precise answers, evidence, authors, sources and quotable formats.
SXO performance
Speed, comprehension, journeys, trust and conversion.
Generative presence
Observe AI answers, representation gaps and improve public signals.
Answer-share measurement
Structured observation of presence in generative answers, search, snippets and conversational environments.
Editorial governance
Roles, validation criteria, update cycles and evidence rules that maintain authority.
03 / FIELD NOTES
Tipping points
Algorithmic influence becomes strategic when an entity’s representation no longer matches reality or objectives.
01ABSENCE
Become visible
Content exists but the entity remains absent from decisive queries, answers and comparisons.
02CONFUSION
Clarify the entity
Namesakes, obsolete information or weak sources blur algorithmic understanding.
03AUTHORITY
Become the reference
An actor has genuine expertise but lacks the structured evidence systems expect.
04CONVERSION
Connect visibility to action
Traffic grows without producing understanding, trust or qualified contact.
04 / OUTPUTS
Authority assets
The strategy produces a coherent set of pages, data and evidence reusable by humans and machines.
Intent map
Questions, audiences, decision stages and expected formats.
Entity graph
People, organisations, services, places, subjects and explicit relationships.
Editorial architecture
Cornerstone pages, clusters, navigation and coverage depth.
Reference corpus
Definitions, answers, studies, evidence, authors and dates.
Structured-data plan
Relevant schemas, property consistency and controls.
AI observatory
Query panel, captured answers, citations, errors and change.
WORKING RECORDS
Make the dossier verifiable
Three practical records connecting diagnosis to a traceable decision.
Intent–entity matrix
Minimum content : Connect each real question to the expected entity, answer page, evidence and useful next action.
Check : Does the page answer a complete question rather than an isolated keyword?
Representation log
Minimum content : Record query, interface, date, answer, citation, possible confusion and likely source.
Check : Does the gap recur in a comparable sample?
Correction plan
Minimum content : Separate content, access, identity, interface and measurement issues; assign an owner and retest.
Check : Can a public change be verified without promising rank?
05 / Method
From query to reputation
Keywords remain useful, but sit inside a system of entities, evidence and experience.
- 01Intent mapping
- 02Public entity audit
- 03Content architecture
- 04Evidence and structured data
- 05Search and AI measurement
- 06Editorial iteration
- 07Link every claim to evidence
- 08Update decisive content
DECISION CHECKS
Decisions to document
Two checks that change the next decision.
A narrative appears dominant
Sample several query phrasings, languages and interfaces before drawing a conclusion. Record answers and dates: one screenshot does not measure reach.
An attribution looks wrong
Separate mistaken identity, out-of-context citation and missing source. Correct the verifiable reference page first, then observe changes in answers without promising them.
Two approaches to distinguish
Two approaches to distinguish
The right method depends on the question and the decision it must inform.
Technical discoverability
An accessible, indexable and linked page can enter a search system’s scope. Check crawl, canonical, visible content and links before measuring presence.
Selection in an answer
Citation or display depends on query, context, source and system. Measure accuracy and consistency across a panel without equating citation with business impact.
Proposed work plan
Adapt this outline to the agreed scope. It describes a proposed method, not a completed mission, measured result or guaranteed schedule. Record your observations and decisions as checks proceed.
AI-generated illustration
Prepare before starting
Entities, messages and journeys under study, a bounded public corpus and observed interfaces. Separate desired visibility from established results.
Scope the work
Map source pages, repetitions and discovery paths. Identify dependencies before counting channel diversity.
Apply the method
Compare visible messages with documented facts. Correct identity, date or scope inconsistencies on controlled pages.
Verify and hand over
Repeat a recorded search panel after correction. Describe observed differences without automatically attributing every variation to the intervention.
Pause or revision conditions
Do not infer causality from a single before/after comparison. An unobservable channel remains outside the stated measurement.
06 / FAQ
Frequently asked questions
Clear answers on scope, limits, methods and engagement conditions.
Does he guarantee a ranking?
No. Nobody controls search engines. The work improves signals, quality and the probability of being understood and selected.
Does GEO replace SEO?
No. It extends it to generative systems and citation patterns.
Does he work on existing content?
Yes: preserve, merge, rewrite or remove according to actual value.
What is LLMO?
Optimising presence in large-language-model systems: understanding, retrieval, citation and representation.
How long before effects appear?
It depends on indexing, existing authority and competition. Early signals often precede durable effects.
Must a large volume of content be produced?
No. The right questions need distinctive, evidenced and maintained answers.
How does he measure AI assistants?
Using a stable query panel, dated captures and analysis of cited sources, errors and variation.
Methodological references
Official documents explaining methods, review criteria and their limits. These references do not certify the service or guarantee search rankings.
08 / CONTACT
Open a private channel
State the context and objective. You will receive a clear initial reading.
Turn a need into a defined assignment
A few interventions relevant to this topic. Each amount covers the stated reference scope; the quote confirms priorities and overlapping tasks.
Semantic strategy & search intent
User needs mapping and content architecture.
Topic cluster : 1 · 8 h
From 640 € excl. VAT / 768 € incl. VAT
Preparation and delivery checks
- What to prepare
- Offer, audiences, customer questions, existing pages and business priorities.
- Suggested process
- Review the agreed sample, separate observations from hypotheses and prioritise fixes.
- Delivery to agree
- Needs grouped by intent, target pages and topics to merge or distinguish.
- Review for this service
- Map each selected need to an intent, target page and duplication risk.
- Scope boundaries
- Delivery is reviewed against agreed work and checks, without a ranking guarantee.
Indicative working scope, to confirm in the quotation.
Document corpus structuring
Organisation, provenance and assistant-ready documents.
Corpus to scope : 1 · 12 h
From 960 € excl. VAT / 1,152 € incl. VAT
Preparation and delivery checks
- What to prepare
- Authorised documents, owners, dates, versions and corpus access rules.
- Suggested process
- Keep the protocol, record answers and check each citation before comparison.
- Delivery to agree
- Document organisation, claim provenance and update rules.
- Review for this service
- Map selected claims to sources, dates, owners and update rules.
- Scope boundaries
- Results remain tied to test conditions; future citations are not guaranteed.
Indicative working scope, to confirm in the quotation.
AI citation tracking protocol
Query panel, log and comparison method.
Protocol : 1 · 6 h
From 480 € excl. VAT / 576 € incl. VAT
Preparation and delivery checks
- What to prepare
- Question panel, planned repetitions, surfaces and definition of a valid citation.
- Suggested process
- Keep the protocol, record answers and check each citation before comparison.
- Delivery to agree
- Repeatable protocol, observation log and citation comparison rules.
- Review for this service
- Check each cited link and distinguish relevant, unrelated and inaccessible references.
- Scope boundaries
- Results remain tied to test conditions; future citations are not guaranteed.
Indicative working scope, to confirm in the quotation.
Related checks
DEEPER READING / PRACTICE
Connecting Digital Presence and Understanding
An organisation appears on several surfaces, but its descriptions differ. Influence work begins with a consistent expression of activity, responsible people and reference information.
Updated on .
Priority checks
Compare entrance pages, public presentations and observed answers for the same set of questions. Identify the contradictions before increasing the volume of publication.
Interpretation pitfalls
Additional mention does not guarantee no understanding or confidence. The absence on a surface may also come from the observation scope, the language or the time of the test.
Working record to retain
A presence card combines surface, tested question, displayed information and discreet discreet. Correction focuses first on the sources that the organization can effectively maintain.