AEO/GEO audit and monitoring for large B2C organisations
Custom AI development, consumer-business knowledge and search expertise connected to practical decisions.
HolistiCRM examines how AI search answers describe your brand, products, offers and locations. We investigate which sources support those answers, whether the information is accurate, and which content or technical changes deserve attention. You receive management reporting, offer-level findings, actionable content briefs and a defined monitoring plan.
Our proprietary agent, already developed through the GINOP marketing-agent programme, is configured for your products, audiences and reporting needs. Selected external tool outputs are connected through our own evaluation process and expert review.
Discuss your AI-search priorities, or explore the DUMMY report.
What are AEO and GEO?
AEO, or Answer Engine Optimization, focuses on visibility in answer-based search. GEO, or Generative Engine Optimization, examines how generative AI answers mention, recommend, cite and interpret a brand. We use GEO in this sense.
For a consumer business, appearing in an answer is only the start. Is the suggested offer suitable for the customer? Does the answer explain important conditions? Is the cited information current? Does it distinguish an online offer from a local store or branch? We connect these questions to your existing SEO, product-content and customer-journey work.
| Industry | Customer decision | What the audit needs to check |
|---|---|---|
| Insurance | Which cover fits my situation? | Eligibility, exclusions, coverage explanations and official sources. |
| Retail | Which product and location meet my need? | Product fit, store information and online/local availability distinctions. |
| Ecommerce | Is this the right item to order? | Variants, compatibility, delivery, returns and the next purchase step. |
| Banking | Which account or financial product fits my situation? | Product conditions, exceptions, source validity and application guidance. |
The approach can also be adapted to telecom, travel and utilities: plan eligibility, booking conditions, service areas and other sector-specific facts need their own reviewers and sources. This describes an adaptable method, rather than an assertion that every industry integration is already deployed.
Explore the B2C guide and the modules for insurance, retail, ecommerce and banking.
Start with people and decisions
We organise questions around needs, situations and decision stages. A parent comparing cover needs different information from a shopper collecting a product locally or a customer checking whether a device is compatible. Discovery, comparison and the next action should each have useful answers.
| Business persona | Question the work supports | Practical output |
|---|---|---|
| Marketing or brand manager | How are we described, and which content should we prioritise? | Brand/topic reporting and a source-linked content plan. |
| Product, category or offer owner | Are suitability, conditions and exceptions accurate? | Claim checks and reviewable product briefs. |
| Ecommerce or local-network lead | Does the answer lead to the right channel or location? | Journey and online/store findings. |
| Procurement or analytics reviewer | What can we verify and receive? | Defined measures, evidence and acceptance criteria. |
This makes the question set a decision tool rather than a disconnected list of prompts.
Why HolistiCRM?
We develop AI, as well as use it
Our competence extends to custom AI-model development. Alongside applying large language models, we undertake task-specific fine-tuning and build AI/ML solutions around business questions. Our team draws on 21+ years of expert AI-development experience and a background spanning 136+ varied AI/ML models. These figures describe expert history and different modelling solutions, not the company’s age or 136 proprietary foundation LLMs.
This depth helps us examine model behaviour, differences between answers, measurement limitations and appropriate controls. Its value is demonstrated through concrete work and verifiable methods.
We connect the whole consumer journey
Search visibility is evaluated together with offer information, acquisition, customer journeys and measurement. A recommendation should explain what needs changing, who owns the work and what evidence would demonstrate progress. Through GlobAI.ly, we also examine international AI practices and assess their relevance to the assignment.
Our competence pyramid
| Level | Capability | Contribution to the work |
|---|---|---|
| 1. AI user | Uses existing applications. | Collects and interprets answers. |
| 2. AI automation specialist | Automates repeated workflows. | Runs and stores measurements consistently. |
| 3. AI application developer | Builds model-based applications. | Creates evaluation, data flows and reports. |
| 4. Model fine-tuning specialist | Further trains and validates existing models. | Understands adaptation, training data and evaluation. |
| 5. Custom model developer | Designs and develops AI/ML models. | Examines behaviour and controls at development level. |
HolistiCRM’s capabilities reach the fifth level. This is our explanatory framework, not an external certification. A successful assignment also needs industry knowledge and search expertise.
From evidence to an implementation plan
- Define the decisions. Agree audiences, topics, offers, locations, languages and the competitor context. Separate branded and unbranded questions.
- Capture a baseline. Use documented surfaces and conditions with repeated runs. Preserve raw answers, citations and run statuses.
- Validate the claims. Distinguish mentions, recommendations and citations. Compare offer claims with current approved sources.
- Investigate the gaps. Review missing information, confusing journeys, inaccessible content and technical findings.
- Prepare the work. Produce reports and briefs with priorities, owners, approval and acceptance criteria.
- Remeasure. Evaluate approved changes using comparable questions and conditions; disclose material differences.
A consumer search interface and a model API can return different answers. They are not automatically treated as equivalent measurements. Actual access, adapters and usage conditions are validated for each assignment.
| Deliverable | What it contains | Decision supported |
|---|---|---|
| Management summary | Findings, business significance and first actions. | Sponsor priorities. |
| Brand and topic report | Defined mentions, recommendations and citations. | Marketing focus. |
| Offer and source report | Checked claims, evidence, gaps and review status. | Product approval. |
| Content briefs | Audience, page, missing answer, sources and structure. | Editorial implementation. |
| Technical and journey backlog | Reproducible issues and acceptance checks. | Web/channel improvements. |
| Monitoring configuration | Questions, modes, repeats, definitions and views. | Comparable follow-up. |
A content brief specifies the work required; it does not bypass your publication or product-approval process. Delivery formats and justified data access are agreed at the start.
DUMMY — fictional illustration; no client result.
| Customer situation | DUMMY finding | Approved evidence to check | Proposed content task |
|---|---|---|---|
| Insurance comparison | An exclusion is omitted. | Applicable policy information. | Explain cover and exclusions together. |
| Local retail choice | Online availability is mistaken for store availability. | Authorised local information. | Distinguish delivery, collection and local availability. |
| Ecommerce purchase | A product variant is recommended without a compatibility check. | Product specifications. | Add a variant and compatibility guide. |
| Banking application | An eligibility condition is unclear. | Official product facts. | Present conditions, exceptions and next steps. |
The DUMMY report shows how observations, evidence and briefs connect. It does not demonstrate a live client uplift or establish that every adapter is operational.
Keep visibility and business outcomes separate
A mention is not a citation; a citation is not a website visit; a visit is not a purchase or application. Ecommerce orders, store visits, insurance enquiries and banking applications require different measurement plans. Online and offline outcomes should retain their own definitions and attribution limits.
Where agreed analytics are available, we compare AI-related referral observations with relevant site actions. We do not infer store sales from citation counts or assign every conversion to an AI answer. Changes in campaigns, seasonality, offers and measurement conditions need to be considered.
Experience, with clear roles
Our public references describe recommendation and response modelling for NetPincér/Delivery Hero, retail-location and format questions associated with Fresh Corner, Cofidis offer modelling, earlier Citibank expert work and partner-delivered MBH reporting. They cover different AI, analytics and reporting tasks; they are not automatically AEO improvement cases or current client endorsements.
The MarTech Outlook Europe profile provides additional background on our consumer-marketing and custom-model capabilities. Our search portfolio contains 92 registered SEO project records. Each project’s scope and results require its own documentation; the record count does not mean 92 verified AEO outcomes. Non-public client materials require prior written client permission.
Frequently asked questions
Is the agent already completed?
The GINOP marketing-agent core is complete. We configure questions, offer facts, access and report views for the assignment, and validate client-specific adapters.
Can you guarantee an AI recommendation?
No. We work on accessibility, content clarity, factual accuracy and consistent measurement, then evaluate changes through documented evidence.
Can a project start with public information?
Yes. An initial public-visibility review can use public sources. Analytics or internal facts are used only where justified, through agreed permissions and a documented data flow.
What should we bring to the first discussion?
Your priority audience, product or offer topics, target markets and a few important customer questions. We then agree the scope, evidence, deliverables and follow-up plan.
Discuss your AI-search priorities — or explore the DUMMY report first.