Onboarding project | Newme

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Onboarding project | Newme

Ideal Customer Profile

Introduction

☝🏼 But wait... What is Newme?

Imagine it’s Saturday night. You’ve opened your wardrobe for the fifth time, and still, nothing feels “you.” Trends change fast, and what worked last month feels outdated today. You want to try something new — not just a new outfit, but a new vibe. And why not? You're constantly evolving — your clothes should too.

You open your phone, tap into Newme — a fashion-forward platform where Gen Z shops what’s hot right now. In minutes, you've picked a bold co-ord set, an edgy jacket, and accessories that scream your vibe. It’s all on-trend, affordable, and ships fast. You feel seen. You feel fresh. You feel... Newme.

Newme is India’s fastest-growing Gen Z fashion platform, offering trend-first, affordable styles that drop weekly — keeping pace with how fast Gen Z moves. With over 4 million monthly active users, Newme is redefining how young India shops.

Creating an Ideal Customer Profile for Newme

To dive deeper into what drives our users — their motivations, shopping habits, and what draws them to Newme — we conducted user research and spoke directly with active shoppers on the platform. Based on insights from ~10 such conversations, we’ve outlined the following Ideal Customer Profiles (ICPs):

Criteria	ICP 1	ICP 2
Name	Diya	Tisya
Age	23	19
Demographics	Working professional, lives in Gurgaon, disposable income	College student, lives in Bangalore, budgets monthly pocket money
Income	1,00,000 per month	10,000 per month (pocket money + internship earnings)
Need	Trendy yet office-appropriate fashion, quick delivery	GenZ styles for college, Insta-worthy outfits
Apps they spend most of their time on	Instagram, Pinterest, Whatsapp, Facetime, Linkedin, Netflix, Apple TV, Slack, Swiggy, District	Instagram, Youtube, Netflix, Whatsapp
Willingness to pay	Medium–High: Will pay for value and curation	Low–Medium: Looks for discounts and value packs
What do they spend most of their time on	At work, travelling, fitness- gym/activities like yoga, pilates, pickle ball	University, gym+ sports(tennis), hanging out with friends
Where do they spend most of their money	Food+Travel- Swiggy, Zepto, Blinkit, Uber	Shopping- Myntra, Savana
Pain Point	Limited time to shop, dislikes long returns & uncertainty and unreasonable pricing	Affordability, dislikes boring UX and unclear sizing
Solution	Shops at Zara, H&M, Mango- finds the right style but not happy with pricing	Urbanic, Savana, Myntra Instagram thrift stores
Behavior	Shops mostly during salary days or occasions	Scrolls app at night or between classes, impulse purchases
Perceived Value of Brand	Reliable & cool GenZ fashion brand	Relatable, trendy & accessible online fashion store
Marketing Pitch	“Your work-to-party wardrobe, delivered tomorrow.”	“Slay every day with fits that match your vibe (& budget).”
Goals	Build a strong, consistent wardrobe without the hassle	Get maximum trend for minimum spend
Frequency of Use Case	0-1 times a month	Weekly browsing, 1–2 purchases a month
Average Spend on the Product	₹3000–₹4000	₹800–₹1500
Value Accessibility to Product	High — needs easy search, size filters, quick delivery, GenZ but corporate	High — wants “Shop the look” & student deals
Value Experience of the Product	High — looks for smooth UX, return ease, short delivery time	High — gets excited by trends, gamified offers, and rewards

Let's understand out ICPS better...

Meet Diya
Diya, 23, is a young working professional living in Gurgaon. With a disposable income and a packed schedule, she’s always on the lookout for trendy yet work-appropriate fashion that aligns with her fast-paced lifestyle. She values seamless experiences — quick delivery, easy returns, and curated edits that suit her work-to-party wardrobe needs. She shops occasionally but spends more per order, seeking style with substance.

Meet Tisya

Tisya, 19, is a college student in Bangalore who thrives on trends. With a modest monthly budget from pocket money and internships, she scrolls through Newme between classes or at night — hunting for affordable, GenZ-coded outfits that are Insta-worthy. Shopping is her way of self-expression, and she gravitates toward platforms that are fun, rewarding, and visually stimulating.

What are the Goals? JTBD of the User

Diya's JTBD

Diya is a working professional who wants her outfits to reflect both confidence and style, whether it’s for client meetings or last-minute dinner plans. With a packed schedule, she values fast delivery, a smooth shopping experience, and curated collections that help her find office-to-evening looks quickly, without wasting time. Also note- she hates repeating outfits!

Tisya's JTBD

Tisya is a college student who loves keeping up with fashion trends and expressing herself through her outfits from classes to the library to the club. But with a limited budget, she’s always on the lookout for trendy, Insta-worthy pieces that don’t break the bank. She values affordability, clear sizing, and a fun, GenZ shopping experience that feels as vibrant as her style.

JTBD and validation

Diya's JTBD + Validation

Goal Priority	Goal Type	JTBD	Validation approach	Validation
Primary	Personal	Feel confident and stylish in their outfits, whether for professional settings or social events.	User interviews	“I want to walk into a client meeting knowing I look sharp—it just sets the tone.”
Secondary	Social	Find new, trendy outfits easily so they avoid outfit repetition and feel good when going out.	User interviews	“I hate repeating outfits when I go out with friends—it feels like I’ve run out of looks.”

Tisya's JTBD + Validation

Goal Priority	Goal Type	JTBD	Validation approach	Validation
Primary	Social	Trendy outfits that reflect their personality and stand out in social settings.	User interviews	“I love when girls from my college ask me where my outfit is from- it looks really good! ”
Secondary	Financial	Easy to discover stylish clothes that fit within a tight budget, without compromising on quality or vibe.	User interviews	“I’m always hunting for pieces that look expensive but don’t wreck my budget.”

From the conversations I had with users, a few common traits emerged:

Most users discovered Newme through influencer recommendations — especially on Instagram
Users feel the app experience could be more premium and smoother
They love Newme for giving Indian accessibility to clothes that look like Oh Polly or Revolve at such an affordable price!

Onboarding Teardown

🛍️ Newme Onboarding Teardown – App Experience

Newme can be accessed in two ways:

Online via the mobile app
Offline through retail stores across India

In this teardown, we’re focusing on the online journey—from downloading the app to signing up and diving into a shopping experience designed for Gen Z.
Download → Sign up → Shop till you drop 💅

Newme Onboarding Teardown.pdf

🧠 Psychological Impact of the Onboarding Journey – Newme

To understand how users emotionally experience Newme’s onboarding, we mapped the customer journey and evaluated the psychological impact of each step on their mood.

By plotting this journey, we identified key emotional highs (Aha! moments) and subtle friction points that shape how Diya feels throughout

Multiple "Aha! Moments" were noticed during onboarding, helping us predict the factors that motivates our users, nudges them and helps them come back onto the platform again and again.

Activation metrics

🎯 Activation Metrics Hypothesis – Newme

North Star Metric:
Increase in First-Time Purchase Conversions

The ultimate goal of onboarding is to drive users toward their first purchase — fast. For Newme’s fashion-forward Gen Z ICP, this directly translates to finding a trendy outfit quickly for a social occasion with quick delivery. The faster she discovers value, the more likely she is to return.

Our activation hypotheses focus on early engagement, smooth product discovery, pricing gratification, and checkout momentum.

Hypothesis 1: App Revisit Frequency in First Week

Activation Metric: X% of new users open the app at least 3 times within the first 7 days of install.

Reasoning:
We’re not aiming for instant conversion — but repeated exposure builds familiarity and desire. Our teardown showed the app is visually engaging and hooks users with personalization and fast delivery promises. Reopening the app is an early signal of growing interest and comfort.

Hypothesis 2: High Engagement With Personalized Feed

Activation Metric: A% of users engage (scroll/swipe/click) with at least 5+ items in the “Exclusively For You” section within their first session.

Reasoning:
Gen Z craves curation. The personalized feed acts as the discovery engine. A high interaction rate here suggests the algorithm is resonating, and the user is actively hunting for “the look.”

Hypothesis 3: Time to First Wishlist or Cart Action

Activation Metric: Y% of users add at least one product to cart or wishlist within 48 hours of install.

Reasoning:
The cart or wishlist moment is a soft commitment and a clear sign of product interest. It signals that the user has discovered value, even if they’re not ready to check out immediately. Swiping gestures or visual discovery tools can help drive this further.

Hypothesis 4: Social Sharing Trigger in First Week

Activation Metric: C% of new users share at least one product or wishlist with a friend on WhatsApp or Instagram within 7 days of app install.

Reasoning:
For Gen Z, shopping is inherently social. When a user shares an outfit, they’re not just seeking validation — they’re also expressing style identity. This behavior often precedes purchase and boosts organic reach. Features like “Share Outfit” buttons or auto-generated try-on previews can act as low-friction sharing triggers. A shared wishlist or “what do you think of this?” moment is a micro-activation.

Hypothesis 5: Post-Delivery Satisfaction Score

Activation Metric: A% of customers who received an order rate the app 4 stars or more within 6 days of delivery.

Reasoning:
This is a true signal of activation: not only did they go through discovery → purchase → delivery, but they had a good enough experience to give positive feedback. This is a better proxy than just NPS for early-stage adoption.

Onboarding Metrics

📊 Qualitative Onboarding Metrics

Factors	Tracking Suggestions
CSAT / NPS Post-Order	Prompt users to rate their experience 6–12 hours after delivery. Use emojis or 1–5 scale to boost response rate. Segment by delivery speed or category.
Wishlist Behavior	Track how soon a user adds an item to wishlist post-install. Use in-app prompts (“Want to save this?”) to understand intent.
Referral Intent	Ask “Would you recommend Newme to a friend?” after first successful order. Pair with in-app referral banner engagement.
CTA Engagement (e.g., Fast Delivery)	Use heatmaps to see click density. A/B test button copy like “Get it by Tomorrow” vs “Fast Delivery.”
In-App Messaging (Pop-ups, Nudges)	Track open & click-through on coupon banners and referral nudges. Refine based on placement and timing (before checkout vs after).
Onboarding Funnel (Awareness → Checkout)	Map onboarding drop-offs (home → PDP → wishlist → cart → payment). Segment by campaign or persona.

📊 Quantitative Onboarding Metrics

Metric	Tracking Suggestion
TAT (Time to Load)	Use tools like Google PageSpeed Insights to monitor PDP/homepage load times. Target: <2 seconds for seamless browsing.
D1 vs. D7 Retention	Track % of users returning on Day 1 and Day 7 via Mixpanel or Amplitude. Use nudges like “new drops” or style edits to boost D7.
MAU vs. DAU	Monitor active user ratio weekly/monthly. A healthy DAU/MAU (>25%) signals strong product stickiness and habit-forming usage.
Activation Rate	Define as completion of first key action set (e.g., fast delivery filter + PDP view + wishlist add). Use Segment or Mixpanel.
Cart Abandonment Rate	Track % of users who add to cart but drop before checkout. Segment by issues: delivery window, price confusion, sizing.
Product Reviews Left	Measure % of users who leave a review 3–7 days post-delivery. Incentivize with loyalty coins or early access perks.
Payment Page Drop-off	Monitor drop rate at the payment screen. A/B test payment gateway speed, trust badges, and coupon errors.