Zepto, Ajio & Royal Enfield: Winning at AI Search

Most marketing content about AI in advertising is written for the US or global market. Very little of it names Indian brands, uses Indian shopping behavior, or talks about what recruiters in India are actually screening for right now.

That's exactly the gap this post fills. Four Indian and India-facing brands — Lenovo India, Ajio, Zepto, and Royal Enfield — are already running a specific three-step AI Search playbook, and the results are public. If you're a marketer or a student trying to understand where performance marketing is headed in India specifically, this is the most concrete, locally-relevant case study you'll find. 

This isn't a small or temporary test either. Search Engine Land reported that India was Google's first international expansion market for AI Mode, ahead of every other country outside the US — a strong early signal that Indian search behavior is a genuine priority for Google, not an afterthought.

Did you know? 86% of Indian shoppers who use AI-powered Search say they're open to trying new brands or products they discover there.

What "AI Search" Actually Means for Indian Shoppers

Search stopped being a static list of blue links a while ago. What's changed recently is how people search — and Indian users are adopting these new patterns fast. (For a deeper look at what's actually shifted over the past twelve months, see One Year of Google AI Mode in India: What the Data Actually Shows.) 

1. Multimodal Search

Shoppers are no longer limited to typing. AI Search now understands text, voice, images, and gestures together.

More than 1 in 6 AI Mode queries are now entirely non-text, and image-based searches are growing over 40% month-over-month. Tools like Google Lens power tens of billions of visual searches every month, and a meaningful share of those already show commercial intent — meaning someone sees a product and wants to buy it, not just learn about it.

2. Conversational Depth

AI Mode queries are now roughly three times longer than a traditional keyword search.

In India specifically, this shows up in a very recognizable way: shoppers mixing Hindi and English in the same search, describing exactly what they want and their budget in one natural sentence — the same way they'd ask a knowledgeable shop assistant, not a search engine.

3. Agentic Intelligence

AI Search is starting to act less like a results page and more like a personal shopping assistant — synthesizing information across sources to move someone from vague curiosity to a confident decision, sometimes even completing the purchase within the search experience itself.

Why This Matters More in India Than Almost Anywhere Else

The data backs up why brands are moving fast here specifically:

• 84% of Indian shoppers using AI Overviews or AI Mode say it helps them make faster purchase decisions
• 87% say it helps them make more confident decisions
• 86% are open to trying a new brand or product they encounter through AI Search

That last stat is the one that should get a marketer's attention. High openness to new brands means the cost of earning a first-time customer through AI Search is currently lower than it will be once every competitor catches on. That window won't stay open forever.

The 3-Step AI Search Playbook (What These Brands Are Actually Doing)

Before the brand breakdowns, here's the underlying framework all four are using in some form.

Step 1: Fix Your Data Foundation First

AI-powered bidding is only as good as the data feeding it. Brands are connecting their CRM and offline data directly into Google Ads so the system can identify which conversions are actually the most profitable — not just the most frequent — and bid accordingly.

Step 2: Use AI Max for Search + Smart Bidding to Capture Real-Time Intent

AI Max for Search extends targeting into new, longer, more specific queries without needing a matching keyword list. Paired with Smart Bidding — which adjusts bids using real-time signals — this combination is built specifically for the longer, messier, more conversational searches AI Mode is producing.

Advertisers using AI Max typically see about 27% more conversions at a similar cost, even when most of their existing campaign still runs on traditional keyword matching. For a full breakdown of how this feature works and how to set it up, see What Is Google AI Max for Search? (2026 Guide).

Step 3: Optimize Performance Max With Better Creative and Audience Signals

Performance Max pulls together Search, YouTube, Maps, and Discover into one AI-driven campaign. It performs best when fed two things: diverse creative (vertical video, localized language copy, creator-style content) and strong audience signals (top-performing search terms, customer match lists, and clear exclusions so the algorithm isn't wasting spend on the wrong users). For the complete strategy behind this step, read Why Google Performance Max Is the Future of Digital Marketing.

Real Indian Brands, Real Results

Lenovo India

Instead of waiting to be found, Lenovo India used AI Max for Search to proactively target incremental, long-tail queries — everything from laptop accessory searches to promotional campaigns.

The result: a 73% lift in purchases and a 51% surge in return on ad spend.

Ajio

The fashion e-commerce platform used AI Max for Search to capture broad, multi-layered shopping intent — the kind of complex, multi-need queries AI Mode is now built for.

The result: revenue jumped 38%, with ROAS up 31%.

Zepto

The quick-commerce platform leaned on Performance Max, feeding it strong creative and audience signals to scale acquisition efficiently rather than just spend more.

The result: 31% more user acquisitions at a 47% lower cost per action.

Royal Enfield (motorbike rental)

By pairing Performance Max with AI Max for Search together, Royal Enfield's rental business captured demand across both broad discovery and specific booking-intent searches.

The result: monthly bookings up 3.3X, with cost-per-booking down 70%.

Four different business models — quick commerce, fashion retail, electronics, vehicle rentals — and the same underlying pattern: brands that stopped relying on fixed keyword lists and let AI match real intent saw the biggest gains.

Careers in AI-Driven Performance Marketing: What Recruiters in India Are Screening For

If you're a student or early-career marketer, this case study doubles as a hiring signal — and it maps closely to what's covered in our Performance Marketing Jobs India 2026: Complete Career Guide. Here's what's actually changing in job descriptions right now:

• Data literacy over keyword lists — knowing how to connect CRM/offline data into Google Ads Data Manager matters more than knowing hundreds of match-type rules
• Comfort with AI Max and Smart Bidding — being able to explain what these tools do and read their reports is now a baseline expectation, not a bonus skill
• Creative production, not just campaign management — Performance Max rewards brands with diverse, localized creative, so skills like vertical video editing and regional-language copywriting are increasingly bundled into "performance marketing" roles
• Comfort with code-mixed, conversational search behavior — understanding how Indian users actually search (Hindi-English mixing, voice, image search) is a genuine edge over marketers trained only on English, text-based keyword thinking
• Analytical storytelling — being able to explain why a campaign worked (not just report that it did) is what separates junior from senior hires in an AI-automated world

How to Build These Skills Right Now

• Run a small Performance Max or AI Max test campaign in a free Google Ads account, even with a tiny budget — and if you're weighing where that first budget should go, Google Ads vs Facebook Ads: Cost, Reach & Conversions Compared is a useful starting point
• Practice writing ad copy that naturally includes local language mixing, not just English
• Get comfortable pulling and reading a Search terms report — it's the single most-referenced skill across all four case studies above
• Follow Indian case studies specifically (like this one) — global examples are useful, but interviewers respond strongly to candidates who understand the Indian market

Common Mistakes Brands Make With This Playbook

To keep this complete and balanced, not every AI Search rollout goes as smoothly as the four cases above. The most common mistakes:

• Skipping the data foundation step — jumping straight to AI Max or Performance Max without clean CRM/offline data means the AI is optimizing on incomplete information
• Treating Performance Max as "set and forget" — it still needs regular creative refreshes and audience signal updates to keep performing
• Ignoring exclusions — broader AI targeting without content and brand exclusions can pull in irrelevant or low-quality traffic
• Using only English creative — brands that skip localized, code-mixed language copy leave real performance on the table in the Indian market specifically

Where This Is Headed

Search in India is shifting from something people "do" occasionally to something running continuously in the background of how people shop, compare, and decide. As AI Mode and AI Overviews become the default way people search, brands that already understand multimodal and conversational intent will have a growing head start over ones still thinking in fixed keyword lists.

For marketers building a career here, the opportunity is timing: this shift is recent enough that being genuinely good at it — right now — puts you ahead of most of the current job market.

Key Takeaways

• AI Search marketing in India is being reshaped by three shifts: multimodal search, longer conversational queries, and agentic, assistant-like results
• Indian shoppers are primed for this — 84% report faster decisions and 87% report more confident decisions through AI Search
• Lenovo India, Ajio, Zepto, and Royal Enfield all used a version of the same 3-step playbook: fix your data foundation, use AI Max + Smart Bidding for real-time intent, and optimize Performance Max with strong creative and signals
• Recruiters are increasingly screening for AI Max comfort, data literacy, and localized creative skills — not just traditional keyword management

FAQ

Q: What is AI Mode in Google Search?
A: AI Mode is Google's AI-powered search experience that understands longer, more conversational, and multimodal (text, voice, image) queries, offering more personalized, synthesized answers than a traditional results list.

Q: Is AI Max for Search different from Performance Max?
A: Yes. AI Max for Search extends targeting within Search campaigns using intent-based matching. Performance Max is a separate campaign type that runs ads across Search, YouTube, Maps, and Discover together.

Q: Do these results only apply to large brands with big budgets?
A: No. The playbook — data foundation, AI Max plus Smart Bidding, and Performance Max — is available to advertisers at any budget level, though results will naturally scale with spend.

Q: Why does Hindi-English mixed search behavior matter for marketers?
A: Because AI Search now understands natural, conversational queries, brands that write ad copy and landing pages reflecting how Indian users actually search — including code-mixed language — tend to match intent more precisely than English-only campaigns.

Quick Glossary

• AI Mode — Google's conversational, AI-powered search experience
• AI Overviews — AI-generated summary answers shown directly in Search results
• AI Max for Search — AI-powered intent matching within Google Search campaigns, extending reach beyond fixed keyword lists
• Performance Max — a Google Ads campaign type that runs across Search, YouTube, Maps, and Discover from one campaign
• Smart Bidding — Google's automated bidding system that uses real-time signals to optimize bids

Now that you've seen how Indian brands are winning at AI Search, read our Performance Marketing Jobs India 2026 guide to see exactly which roles are hiring for these skills right now.

About the Author

Sapna is a Content Writer and Digital Marketing Specialist at DizitalAdda with over 3 years of experience in SEO, content strategy, and writing about AI tools and emerging search trends. She covers topics across digital marketing, search engine optimisation, generative AI, and career guidance for students and professionals looking to build a future in the digital space. Based in New Delhi.