AUDIT EXPERIENCE BY CATEGORY
Different products create different discovery problems.
The audit begins with the buying decisions unique to the category—not a generic list of prompts applied to every brand.
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Fashion & apparel
SOLAÍ THE LABEL · SIX5SIX · Soch · &Circus
Fashion discovery depends on context that basic product titles rarely capture: occasion, fit, silhouette, climate, styling and who the product is designed for.
COMMON CHALLENGES
- Size and fit information is inconsistent or trapped in images.
- Products lack occasion, style, climate and comparison context.
- AI answers repeatedly favour better-known brands and editorial sources.
WHAT WE CHECK
- High-intent prompts by product type, occasion and customer need.
- Fit, fabric, construction, care, styling and variant information.
- Competitor mentions, citations, category pages and structured data.
HOW TO IMPROVE
- Strengthen PDP attributes, fit guidance and use-case language.
- Build category and comparison content around real buying questions.
- Connect products, collections, reviews and schema more clearly.
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Beauty, skincare & hair
SkinInspired · Hair Drama Company
Customers ask AI about concerns, ingredients, compatibility and routines. Missing evidence or unclear claims make it difficult for AI—and shoppers—to compare products confidently.
COMMON CHALLENGES
- Benefits are stated without enough ingredient or evidence context.
- Skin, hair, concern and routine suitability are incomplete.
- Safety, usage and compatibility questions remain unanswered.
WHAT WE CHECK
- Concern-led prompts, ingredient questions and routine comparisons.
- Claims, ingredients, usage, suitability, proof and review signals.
- Whether authoritative sources support the product story.
HOW TO IMPROVE
- Clarify factual ingredients, benefits and suitability attributes.
- Add responsible FAQs, routines, comparisons and supporting evidence.
- Separate verified product facts from marketing language.
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Nutrition, wellness & supplements
FreshLuxe · ProSupps India · Living The Good Life Naturally
Wellness decisions combine goals, ingredients, dosage, format, restrictions and trust. AI systems may avoid products when key facts or supporting evidence are unclear.
COMMON CHALLENGES
- Dosage, format, ingredients and intended use are fragmented.
- Health-related wording creates claim and trust risks.
- Large incumbents dominate recommendation and citation patterns.
WHAT WE CHECK
- Goal-led, ingredient-led and format-led buying questions.
- Composition, directions, warnings, certifications and substantiation.
- Recommendation frequency, competitors and source quality.
HOW TO IMPROVE
- Improve factual product structure without overstating outcomes.
- Add comparison, suitability, usage and safety information.
- Develop credible sources and category education around shopper needs.
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Food, organic & FMCG
Gramiyaa · Praakritik · Candor Foods · Zama Organics
Food discovery is shaped by ingredients, origin, dietary needs, processing, flavour, format and certifications—details that are often inconsistent across a catalogue.
COMMON CHALLENGES
- Origin, processing and dietary attributes are difficult to retrieve.
- Similar products lack clear differentiation and usage occasions.
- Broad category queries favour marketplaces and established publishers.
WHAT WE CHECK
- Dietary, ingredient, origin, use-case and comparison prompts.
- Nutrition, allergen, certification, pack and storage information.
- Category authority, retailer presence and third-party citations.
HOW TO IMPROVE
- Standardise product and dietary attributes across the catalogue.
- Create useful category, recipe, comparison and sourcing content.
- Improve structured data and consistency across owned channels.
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Home, décor & handcrafted products
Decor Kart · Kadam Haat
Home products need rich information about material, dimensions, placement, care, craft and visual style. Thin descriptions make suitability difficult to determine.
COMMON CHALLENGES
- Dimensions, materials, finish and room context are incomplete.
- Craft, origin and care information is not consistently structured.
- Visual products are described with generic, non-comparable copy.
WHAT WE CHECK
- Room, style, material, gifting and space-specific questions.
- Dimensions, construction, care, origin and installation details.
- Image context, variants, category structure and competitor coverage.
HOW TO IMPROVE
- Build consistent material, dimension and style taxonomies.
- Add placement guidance, care, craft stories and comparisons.
- Make product and category information easier for AI to retrieve.
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Jewellery & accessories
Myra Gems · RG
Jewellery and accessories require precise material, size, construction, care and styling facts. Trust and product distinction matter as much as discovery.
COMMON CHALLENGES
- Material, plating, dimensions and care details can be ambiguous.
- Style and occasion language is inconsistent across products.
- Trust signals are weaker than those of large retailers.
WHAT WE CHECK
- Material, occasion, gifting, style and comparison questions.
- Specifications, care, authenticity, policies and supporting proof.
- Category visibility, competitive positioning and source coverage.
HOW TO IMPROVE
- Standardise specifications and responsible authenticity language.
- Add styling, gifting, care and comparison guidance.
- Strengthen trust signals across PDPs, policies and external sources.