38% of Indian Festive Shoppers Now Use AI for Product Research: Brand Visibility Checklist
Abhishek Dwivedi
Team Lead, SEO
AI is becoming part of India’s festive shopping journey. Integral Ad Science’s 2026 India study found that 38% of consumers plan to use AI tools to research products and gift ideas, up from 32% in 2025. At the same time, 84% expect to do most or all of their festive shopping online and 83% identify mobile as their primary shopping device. For brands, the opportunity is broader than ranking for a seasonal keyword. Product facts, reviews, feeds, mobile pages and authority signals now need to work together so search engines, marketplaces and AI assistants can understand and recommend the brand with confidence.
What the 2026 festive-shopping data says
Integral Ad Science surveyed 503 Indian consumers in September 2026 about their holiday shopping plans, digital behaviour and perceptions of online advertising. The study reports that 38% plan to use AI tools for product or gift research, compared with 32% in its 2025 survey. It also found that 84% expect to complete most or all festive shopping online, 83% identify mobile as their most-used shopping device and 86% plan to increase festive budgets. The year-on-year comparisons are directional because the two surveys were conducted at different points in the calendar. Review the methodology and findings in the IAS Festive Buying Report India 2026.
Why AI changes the product-discovery journey
Traditional festive discovery moved from an ad or search result to a product page. AI adds a layer that can summarise options, compare specifications, surface reviews and answer follow-up questions before a shopper visits a store. That makes information consistency a marketing requirement. If a price, material, warranty, delivery promise or store policy differs across the website, marketplace listing and merchant feed, an AI system has weaker grounds for a confident recommendation. Brands should treat every public product fact as part of the same knowledge system.
Build a single source of truth for product facts
Create an approved product-information source that contains product name, category, price, availability, variants, dimensions, materials, intended use, compatibility, warranty, delivery coverage, returns and support information. Give each attribute an accountable owner and a last-reviewed date. Reuse the same approved wording across the product page, Merchant Center, marketplace listings, store locator and customer-support knowledge base. This reduces conflicting answers and makes updates faster during high-volume festive campaigns. Use our agentic commerce readiness checklist to test whether this product knowledge is accessible to shopping agents.
Make product feeds useful beyond paid shopping ads
Merchant and catalogue feeds increasingly support discovery across search, ads, marketplaces and conversational shopping experiences. Include stable product identifiers, accurate availability, high-quality images, variant relationships, sale dates and destination URLs that resolve correctly on mobile. Do not hide important attributes in images or scripts that crawlers cannot reliably interpret. Our AI-ready product feed guide explains how to audit attributes for agent-led shopping journeys.
Publish comparison content that answers real buying questions
AI-assisted shoppers often ask complete questions: which phone suits a parent, which gift arrives before Diwali, or whether one appliance is worth paying more for. Build comparison pages around those decisions rather than repeating category keywords. State who each option suits, the trade-offs, total cost, delivery constraints and evidence behind the recommendation. Use tables when attributes are genuinely comparable, then add a short expert interpretation. Keep availability and pricing dynamic so a useful comparison does not become misleading.
Design for the mobile-first festive shopper
With 83% of respondents naming mobile as their primary online-shopping device, the mobile experience is central to discovery and conversion. Test Core Web Vitals, tap targets, product-image loading, variant selection, address entry, payment recovery and customer-support access on real devices. Keep critical product facts visible without forcing shoppers through accordions. Compress media without making specifications unreadable, and ensure comparison tables remain usable on narrow screens. A fast page with incomplete information still creates friction, so speed and clarity must improve together.
Connect AI visibility with paid and owned media
Organic visibility, marketplaces, creators, social video, performance media, email and WhatsApp should reinforce the same proposition. Use paid campaigns to learn which questions, products and objections attract qualified demand, then reflect those findings in product pages and service content. Our India festive commerce playbook maps channel roles across demand creation, conversion and retention. Maintain consistent offer terms so a shopper does not receive conflicting answers across touchpoints.
Measure discovery quality, not only last-click sales
IAS argues that media quality, contextual relevance and reduced waste matter as shoppers move between social, video, ecommerce and AI-assisted research. Track viewability, invalid traffic, suitable placements and attention alongside reach. For commerce outcomes, monitor qualified product-page sessions, feed disapprovals, add-to-cart rate, checkout completion, return rate and contribution margin. Separate new-customer acquisition from remarketing and annotate offer changes, inventory constraints and delivery cut-offs before interpreting performance.
A 30-day festive AI-visibility checklist
Days 1 to 5: audit the top twenty revenue-driving products and list every conflicting or missing fact. Days 6 to 10: repair feed attributes, structured data, product identifiers and mobile errors. Days 11 to 15: publish decision-led comparisons and answer high-intent questions. Days 16 to 20: connect verified reviews, expert evidence and store or support information. Days 21 to 25: align ad, marketplace, website and messaging claims. Days 26 to 30: test real shopper prompts, record brand mentions and conversion paths, then assign owners for festive-period updates.
Frequently asked questions
These answers cover the most common questions Indian retail and D2C teams ask when preparing for AI-assisted festive discovery.
How can a brand appear in AI shopping recommendations?
A brand improves its chances by publishing accurate product facts, complete feeds, useful comparison content, credible reviews and clear commercial policies. AI systems may use several sources, so consistency matters across the website, marketplaces and reputable third-party references. No markup or content format guarantees a recommendation. The goal is to make the product easy to understand, verify and compare for a specific shopper need.
Do Indian shoppers really use AI before festive purchases?
The IAS 2026 survey found that 38% of 503 Indian respondents planned to use AI tools for product or gift research. That is six percentage points above its 2025 result. The finding describes stated intent within the surveyed sample, not every Indian shopper, but it provides a timely signal that conversational research is becoming a meaningful part of festive discovery.
Which product information matters most to AI systems?
Prioritise exact price and availability, product identifiers, variants, materials, dimensions, compatibility, delivery coverage, returns, warranty and verified ratings. Add the details that determine suitability, such as skin type, size, energy use or supported devices. Keep these fields consistent and current across every channel. Unsupported promotional language is less useful than specific, verifiable attributes.
Can paid advertising improve organic AI visibility?
Paid campaigns can create demand, earn visits and reveal the language shoppers use, but spending does not directly buy an organic AI citation. Advertising insights can improve product pages, FAQs and comparisons when teams use real query and conversion data. Strong brand demand and credible third-party coverage may support wider visibility over time, but organic inclusion remains dependent on relevance, evidence and the systems producing the answer.
How should brands measure traffic from AI assistants?
Use tagged landing pages, web analytics and CRM outcomes to measure referral sessions where a source is identifiable. Track branded-search lift, assisted conversions, product-page engagement and repeated mentions in a controlled set of shopper prompts. Some AI journeys provide limited referral data, so combine direct traffic trends with surveys, post-purchase questions and test-prompt monitoring. Treat citation counts as a visibility indicator, not a substitute for revenue and margin.
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Key Takeaways
- 38% of surveyed Indian consumers plan to use AI for festive product or gift research.
- Consistent product facts across websites, feeds and marketplaces improve machine understanding.
- Mobile clarity, speed and checkout resilience matter because 83% primarily shop by phone.
- Decision-led comparisons and credible reviews help shoppers evaluate fit and risk.
- Measure media quality, qualified discovery and commercial outcomes together.
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