Product Feature Proposal

ZILO Looks.
Don't shop clothes.
Shop outfits.

Same-day outfit bundles for the occasions men already dress up for. Built on the 30-minute try-on window ZILO already runs.

By Gaurav · Product & Strategy Intern Application · April 2026

The Gap

ZILO's biggest unlock isn't faster delivery. It's fewer decisions.

Women drive fashion e-commerce in India. Men don't because browsing 200 brands for a single outfit is friction, not fun. ZILO's try-at-home solves fit risk. It does not solve decision risk.

200+
Brands live on ZILO. Great for browsers. Overwhelming for decision-averse buyers.
zilo.one
30 min
Current try-on window. Perfect for 2-3 items. Wasted on 1 item at a time.
zilo.one
60-120 min
Current delivery SLA. Already a moat vs next-day fashion. Leverage it for bundles.
zilo.one
Mumbai
Single city today. Any proposal must be testable in one city before scaling.
zilo.one
Real Test
I tried ZILO for a friend's wedding reception.
Goal: one outfit. Walked through the app like a user would, timed every step.
0:00 Opened Men section. Clean grid, fast load.
1:40 Started filtering. Kurta? Shirt? Bandhgala? No category for "wedding guest."
7:10 Picked a kurta. Now need bottoms. New search. Different brand. Won't match.
14:00 Found pants. Need a stole or jacket. Scrolling accessories.
23:00 Gave up. Asked my sister. She sent 3 Instagram screenshots in 40 seconds.
🔍

Men shop by occasion, not category

Nobody wakes up wanting "a kurta." They want "something for Diwali at my in-laws'." The occasion is the search query. Current apps force men to translate that into categories, brands, and colors.

💼

Try-at-home is wasted on one item

A 30-minute rider wait costs the same whether I try one shirt or a full outfit. Bundle economics make the model work harder. Same rider cost spread across 4 items is a different per-unit number.

⚡

The try-on moment is the funnel

Once the bag is at my door, conversion is higher than any digital browsing session. More items in the bag means more chances to keep something. Current model leaves that upside on the table.

The Proposal

Pick the occasion. We pick the outfit.

A new top-level tab in the app called Looks. Browse by occasion, not by category. Each Look is a 3-5 piece outfit put together by ZILO's styling team. Delivered together. Try everything in one 30-minute window. Keep what works.

ZILO Looks

Occasion-first outfit bundles, delivered to try. Launching with men because that's where the decision-pain is highest and the category is most underpenetrated.

"I need something for Rohan's wedding reception on Saturday."
One tap. Rider arrives in 90 minutes with 4 curated Looks. Keep one. Done.
How it works

Three taps, one delivery, one try-on.

No new tech required. Merchandising, not engineering.

1

Pick the occasion

Wedding guest, first day at work, meeting the parents, Diwali, date night, festive cousin reunion, gym-to-brunch. Launch with 12 occasions built from the top Mumbai search queries.

2

See 3-5 Looks

Each Look is a full outfit from one or two matched brands. Budget tiers: ₹2,500 / ₹5,000 / ₹10,000+. Stylist-curated. All pieces in your saved size (or two adjacent sizes auto-included).

3

Try the whole Look

Rider arrives with 3-12 pieces. Same 30-minute window. Try the full outfits as outfits, not items in isolation. Keep the Look that works. Return the rest to the rider.

Success Metrics

What I'd watch in the first 8 weeks.

One leading indicator, three health checks. Keep it simple. If Looks doesn't move AOV meaningfully in 8 weeks, kill it or rethink the occasion list.

AOV per Look order
2.5x single-item AOV
The core thesis. A Look should land at 2.5-3x a normal ZILO basket because it's 3-5 matched pieces instead of one. If this doesn't hold, the economics don't work.
Keep rate per Look
≥35% of Looks have at least one item kept
If users try a Look and keep nothing, the styling is off. If they keep one piece from most Looks, we're curating well. Below 35% = bad curation, not bad idea.
Male user share
Watch it
Looks launches for men specifically because men are underpenetrated in Indian fashion apps and most decision-averse. Does this segment's share of ZILO's MAU climb after launch?
Repeat within 60 days
Watch it
Does a Look user return to place a second Look within 60 days? Occasions recur. If the first Look experience is good, the same user should show up for Diwali, anniversary, interview.
∞

North star: Looks GMV as % of Men's GMV. One number that captures whether outfit-mode is a real behavior or a novelty tab. If it sits above 20% within a quarter, ZILO has found a second way to shop, not just another filter.

Roadmap

Ship manually. Automate later.

Phase 1 is a merchandising experiment, not a machine learning project. Prove that men want outfits curated for them before investing in the recommendation engine.

Phase 1 · 4 weeks

Manual Looks, Men's, Mumbai

  • 12 occasions, 3 Looks each, 3 budget tiers
  • Stylist-curated from existing catalog
  • New tab in the app, no new logistics
  • Budget: one stylist + design sprint
Phase 2 · 8 weeks

Personalization layer

  • Size profile auto-populates saved sizes
  • Looks filtered by past purchases and returns
  • "My vibe" quiz (casual vs formal vs streetwear)
  • A/B test curated vs generic Look order
Phase 3 · 12 weeks

Women's + expansion

  • Open Looks for women with different occasion set
  • User-generated Looks: keep a ZILO cart, publish it
  • Stylist partnerships with Mumbai influencers
  • Delhi pilot on validated playbook
Risks & Trade-offs

What I'd worry about.

RiskSeverityMitigation
Curation quality — bad Looks kill the feature High Phase 1 is manual on purpose. One stylist, 36 Looks, reviewed weekly. Keep rate < 35% means redesign the Look, not the feature.
Rider capacity — heavier bags, longer handoffs Medium Average Look is 3-5 pieces, similar weight to a typical multi-item ZILO order. Try-on window stays at 30 min. No fleet change required.
Return logistics — customer keeps 1, returns 4 Low Returns already happen on every try-at-home order. Rider takes them back same-trip. The unit economics get better per delivery, not worse.
Brand resistance — merchants don't want their items bundled with competitors Medium Lead with two-brand Looks (one for top, one for bottom) where brand pairings are pre-approved. Single-brand Looks for premium partners as an incentive.
It's just a filter — users see it as a search, not a new mode Medium Treat Looks as a first-class tab. Distinct visual language. Editorial layout, not a product grid. This is shopping by feeling, not SKU.
Why ZILO, why me

Quick commerce won fast grocery. The next wedge is quick-curated fashion. ZILO is the only app with the right infra.

Myntra can't do this (no 30-min try). Ajio can't do this (no instant delivery). A stylist WhatsApp account can't do this (no logistics). Only ZILO has the three pieces. Looks is the feature that uses all three.

I'd love to work on this with the team. I spent a week reading Q3 earnings for quick-commerce peers, walked through ZILO, built manual Looks to time the flow, and wrote this. If there's a 2-month sprint worth shipping, I want in.