Resources > Case Studies > Aveeno Baby India
Aveeno Baby India Case Study: From AI Search Visibility to a Roadmap for Growing Share of Voice
How Addlly AI benchmarked brand visibility, sentiment, competitor positioning, product-page readiness, and schema gaps to help Aveeno identify its next GEO priorities
As parents use AI platforms to compare baby skincare products, ingredients, and recommendations, brands need to know how AI engines understand, cite, and recommend them.
Aveeno Baby India worked with Addlly AI to understand how the brand appeared across AI-led discovery journeys and what actions could strengthen future Share of Voice.
Addlly AI delivered a comprehensive Generative Engine Optimization audit covering brand visibility, sentiment, competitor positioning, product-page readiness, schema, and content structure. The result was a practical roadmap for moving from AI visibility measurement to execution.
Data as of 18 June 2026.
The Business Challenge
AI search is changing how consumers discover and compare baby skincare products.
Parents now ask conversational questions about sensitive skin, moisturisation, baby washes, ingredient safety, newborn care, and product suitability. These questions influence brand consideration before a consumer visits a brand website, marketplace page, or retailer listing.
Aveeno Baby India wanted to understand:
- How the brand appeared across AI-led discovery journeys
- How AI platforms interpreted their products and brand positioning
- How competitor brands were being represented
- Whether product pages were structured for AI discovery
- Which schema and content signals needed improvement
- What actions could help grow future AI Share of Voice
The goal was not just to measure visibility. It was to convert the audit into a clear plan for GEO execution.
Tools Used
| Tool | Purpose |
|---|---|
| GEO Audit Agent | Benchmarked brand visibility across AI-led discovery journeys |
| AI GEO Agent | Mapped consumer intent and prioritised high-impact discovery opportunities |
| Multi-LLM Testing Framework | Evaluated brand representation across major AI platforms |
| AI Visibility Dashboard | Consolidated visibility, sentiment, competitor, and category-level intelligence |
| Citation Forensics Framework | Analysed the types of sources influencing AI-generated answers |
| Product Description Analysis | Reviewed product content for AI and agentic shopping readiness |
| Schema & Structure Audit | Assessed page structure, FAQs, product attributes, and structured data signals |
| Brand Agent | Created the brand intelligence layer for future execution |
| Execution Agents | Supported the roadmap for PDP optimisation, schema, FAQs, and content engineering |
What Addlly AI Delivered
Addlly AI conducted a structured GEO audit designed to help Aveeno Baby understand its AI visibility and identify the next actions needed to improve discoverability.
The audit covered five core areas.
1. AI Search Visibility Benchmarking
Addlly AI assessed how Aveeno appeared across AI platforms and discovery journeys.
This helped establish a clearer baseline for how the brand was being surfaced, described, and positioned in AI-generated responses.
2. High-Impact Query Prioritisation
Rather than testing a random set of prompts, Addlly AI mapped a universe of more than 2,000 potential consumer discovery queries and prioritised the ones with the strongest business relevance.
The selected queries reflected high-value moments across discovery, comparison, ingredient research, product suitability, and recommendation-led journeys.
This ensured the audit focused on questions that could influence brand consideration, not just broad informational traffic.
3. Sentiment and Brand Interpretation
The audit reviewed how AI systems described Aveeno across different consumer needs and product contexts.
This helped identify whether AI-generated responses reflected the right brand associations and where additional content support could improve interpretation.
4. Competitor Positioning
Addlly AI benchmarked Aveeno against relevant baby skincare competitors selected for the audit.
The goal was to understand how AI platforms compare brands in the category and where Aveeno could strengthen future Share of Voice.
5. Product Description Readiness
Addlly AI reviewed product descriptions to assess whether they were clear, structured, and specific enough for AI-led discovery.
The analysis looked at whether product pages communicated:
- Who the product is for
- What concern it addresses
- Which ingredients or formulation details matter
- How the product should be used
- What makes it different from alternatives
- Whether product attributes were complete and consistent
This helped identify how product content could be improved for AI engines and future shopping agents.
6. Schema, Structure, and Content Engineering
Addlly AI audited the technical and structural signals that help AI systems understand product and category pages.
This included reviewing:
- Product schema
- FAQ structure
- Page headings
- Content hierarchy
- Product attributes
- Internal linking opportunities
- Educational content gaps
- Structured data opportunities
This gave Aveeno a clearer view of what needed to be improved before execution.
What the GEO Audit Covered
The public case study does not disclose client-specific findings, competitor scores, sentiment results, or proprietary audit outputs.
Instead, the audit focused on building a structured view of the signals that influence AI visibility across the baby skincare category.
Brand Visibility
Addlly AI assessed where and how Aveeno appeared across AI-led discovery journeys, including brand-led, product-led, and need-led questions.
Consumer Intent
The audit mapped how parents ask questions across the baby skincare journey, from early research to product comparison and recommendation.
Competitor Context
Addlly AI reviewed how AI platforms represented competing brands within the category, without relying only on traditional SEO rankings.
Product-Page Readiness
The audit assessed whether product pages gave AI systems enough structured and specific information to understand, compare, and recommend products accurately.
Citation Signals
Addlly AI analysed the types of sources influencing AI-generated answers, including owned pages, third-party content, marketplace pages, and publisher sources.
Content Engineering
The audit reviewed page structure, schema, FAQs, internal links, and content gaps that could influence future AI discoverability.
From Audit to Execution
The value of a GEO audit is not the report. It is the action plan that follows.
Addlly AI translated the audit into a roadmap across four execution areas.
| Execution Area | What Addlly AI Assessed | How It Supports GEO |
|---|---|---|
| Product Pages | Product descriptions, attributes, benefits, and use cases | Helps AI systems understand and recommend products more accurately |
| Educational Content | Consumer questions, category gaps, and decision-making journeys | Builds authority around high-intent discovery topics |
| Schema & Structure | Structured data, FAQs, headings, and page hierarchy | Improves machine-readability and AI interpretation |
| Citation Readiness | Source types influencing AI answers | Helps brands strengthen the signals that shape AI-generated recommendations |
The roadmap was designed to move directly into execution through Addlly AI agents built on the Brand Agent.
The Brand Agent acts as the intelligence layer. It captures the brand’s positioning, tone of voice, product taxonomy, approved claims, audience segments, and content guardrails.
Execution agents can then use this foundation to support:
- Product description optimisation
- FAQ generation
- Schema recommendations
- Category-page improvements
- Content cluster creation
- Internal linking opportunities
- Citation-ready educational content
- GEO monitoring and iteration
This helps marketing, digital, SEO, and content teams move from “what did the audit find?” to “what should we fix first?”
Business Impact
Addlly AI helped Aveeno Baby India turn AI search uncertainty into a structured plan for GEO execution.
The audit delivered:
- 5-platform AI visibility benchmark across major AI search and answer engines
- 2,000+ potential consumer queries mapped to identify the highest business-impact discovery journeys
- Prioritised audit set selected across branded, unbranded, product-led, comparison-led, and need-led journeys
- 3 layers of competitive intelligence covering visibility, sentiment, and category positioning
- Product-page readiness review to assess how clearly AI systems could interpret product information
- Schema and structure audit across product, FAQ, heading, attribute, and content hierarchy signals
- Brand Agent foundation to convert audit intelligence into governed execution
- Execution-agent roadmap across PDP optimisation, FAQs, schema, content engineering, and citation readiness
For Aveeno Baby, the value was not another dashboard. It was a clear view of what to prioritise next: which content to strengthen, which product-page signals to improve, where schema needed attention, and how to build a stronger foundation for future AI Share of Voice.
Why Addlly AI’s GEO Audit Is Built for Execution
Most AI visibility tools stop at measurement. They tell brands whether they appear in AI answers. Useful, but not enough.
Addlly AI connects visibility to action.
Our GEO audit is designed to show marketing, digital, and content teams what AI engines are seeing, what they are missing, and what needs to change across content, product pages, and structured data.
1.We Start With Business-Impact Queries
Not all AI search queries matter equally.
Addlly AI maps the wider query universe, then prioritises the questions most likely to influence awareness, consideration, comparison, and purchase intent.
This helps brands focus on the AI discovery moments that matter commercially.
2. We Audit the Full AI Discovery Journey
Consumers do not search in neat keyword boxes anymore. They ask questions, compare products, check ingredients, and look for recommendations.
Addlly AI maps these journeys so brands can see where they appear, where competitors enter the conversation, and where content gaps may affect future visibility.
3. We Assess Product Pages for AI and Shopping Agents
AI systems need clear product information to recommend confidently.
Our audit reviews whether product pages explain the use case, concern, ingredients, benefits, differentiators, and attributes in a way that AI engines and shopping agents can understand.
4. We Bring Content Engineering Into GEO
GEO is not just “write more content”.
It requires schema, FAQs, headings, page hierarchy, product attributes, internal links, and citation-ready content. Addlly AI audits these signals so teams know what to fix before execution begins.
5. We Build Execution on the Brand Agent
The audit does not sit in isolation.
Addlly AI uses the Brand Agent to turn audit intelligence into governed execution. This ensures recommendations are aligned with brand tone, claims, product taxonomy, and content guardrails before agents create or optimise content.
6. We Turn Findings Into a Roadmap
The final output is not a list of observations. It is a prioritised plan covering what to update, create, structure, and monitor next.
That is where GEO becomes useful for business teams: it moves from visibility tracking to execution planning.
Build Your AI Search Visibility Roadmap With Addlly AI
Addlly AI helps enterprise brands understand how they appear across AI search platforms and what to do next.
From GEO audits and competitor benchmarking to product-page analysis, schema review, content engineering, Brand Agents, and execution agents, Addlly AI helps marketing teams move from AI visibility diagnosis to measurable action.
Book a demo to see how Addlly AI can help your brand audit, plan, and improve AI visibility across ChatGPT, Gemini, Claude, Perplexity, and Google AI.
Addlly AI helped Aveeno Baby India understand how the brand appears across AI-powered discovery channels and translated those insights into a clear roadmap for improving visibility.
Want Similar Results for Your Company?
We Can Help!
Contact us or schedule a free demo to learn more.
Answers to
Frequently
Asked Questions
What Was the Goal of the Aveeno Baby India GEO Audit?
To understand how Aveeno appeared across AI-led discovery journeys and identify what could strengthen future AI Share of Voice.
What Did Addlly AI Deliver?
A GEO audit covering visibility, sentiment, competitor positioning, product-page readiness, schema, citation signals, and execution priorities.
How Were the Audit Queries Selected?
Addlly AI mapped more than 2,000 potential consumer queries and prioritised the highest business-impact journeys for the audit.
How Is GEO Different From SEO?
SEO measures rankings and traffic. GEO shows how AI engines interpret, cite, compare, and recommend a brand.
Why Does AI Share of Voice Matter?
Because consumers are using AI platforms to shortlist brands before they visit a website or marketplace page.
Why Audit Product Descriptions?
AI systems need clear product information to understand who a product is for, what concern it solves, and when to recommend it.
Why Does Schema Matter?
Schema helps AI systems read product, FAQ, category, and page information more accurately.
What Is Content Engineering?
It structures content so both humans and AI systems can understand it: schema, FAQs, headings, product attributes, internal links, and page hierarchy.
What Is the Brand Agent?
The Brand Agent is Addlly AI’s brand intelligence layer. It captures tone, positioning, claims, audience segments, and product taxonomy so execution agents can work within approved guardrails.
Can Addlly AI Support Execution After the Audit?
Yes. Addlly AI helps brands move from audit to execution across product pages, schema, GEO content, citation readiness, and AI-led marketing workflows.