Onboarding Project | MakeMyTrip | Priyal Jethva

You're about to walk through something I’ve poured a lot of thought, time, and heart into.

This project began with one question: "How can we make those very first moments on MakeMyTrip feel smooth, seamless, and maybe even a little magical for the users?"

Because let’s be honest, we’ve all been there 😞

You open a travel app, and suddenly there are 15 banners, 6 pop-ups, offers flying at you, and a dozen different places to click. You’re not sure where to begin, what’s important, or how to get what you came for, whether that’s booking a quick bus ride, a long-overdue holiday, or simply checking flight prices.

And that’s the moment that matters. That’s where great onboarding comes in, not just to guide, but to delight, reassure, and make users think, "Ah, this app gets me."

Before we get into the nitty-gritty, let me paint you a picture of where you've landed. MakeMyTrip isn't just another travel company – it's the travel company that changed how millions of Indians explore the world.

Founded back in 2000 (when booking flights online felt like magic), MMT has grown into India's leading online travel platform. We're talking about a company that processes over 40 million transactions annually, connects travellers to 1,00,000+ hotels worldwide, and has somehow made planning that spontaneous Goa trip as easy as ordering pizza.

But here's what makes MMT special – it's not just about the numbers. It's about that family in Pune planning their first international vacation, the business traveler who needs to get from Mumbai to Bangalore without the usual hassle, or the college friends finally taking that long-awaited road trip to Leh. MMT is in the business of making memories possible.

✅ IMPORTANT TO NOTE: For this project, I’ve focused on the Flight Booking Experience on MakeMyTrip – the most common and high-frequency use case across user types. By narrowing it to this use case, we get a sharper lens on the real motivations, friction points, and decision patterns of our users.

User Calls: I conducted 8 User Interviews — a mix of GrowthX members, friends, and family.
Focus: Understand how they book flights using MakeMyTrip.

View User Calls Data Here👇

User Interviews Data File

The goal was to learn what works well, what’s confusing, and what actually makes them choose MMT over other platforms. I’ve put all the responses and patterns into a Google Sheet (linked here) and above to make sense of common behaviours and issues. This step was super important for me because it directly helped me shape my ICP profiles. So I gave it a lot of time and effort to make sure I truly understood the user. Now, based on the calls, I made 4 ICPs. Let's have a look at them!

Based on the table above, we have prioritized ICP 1 and ICP 3. Here's why👇

🥇 ICP 1 - Business Travellers (Abhishek Rao)

Why #1 Priority?

• High repeat frequency = compounding revenue:
  20–25 flights a year per person is unbeatable. For just 1M such users, that’s 20–25M annual flight bookings.
• High spend + low friction:
  ₹7K–₹15K per booking, often company-paid. Doesn’t waste time comparing deals — values speed, convenience, and GST invoices.
• Very high distribution potential:
  B2B partnerships, corporate tie-ups, loyalty programs (MMTBlack), and referrals within organizations → all fuel repeatable, scalable growth.
• Sticky behaviour:
  Once MMT becomes the go-to, they rarely churn. Habits + systems (like saving GST details, saved traveler info) create long-term lock-in.
• TAM is booming in India:
  Corporate travel in India is back in full swing post-COVID, especially in cities like Bangalore, Hyderabad, Mumbai, and Gurgaon.

All in all, this ICP is perfect for volume-driven use case with high LTV, scalable distribution channels, and operational simplicity. This ICP can provide consistent, year-round bookings that aren't seasonal or dependent on holidays.

🥈 ICP 3 – Couple Travellers (Aakash & Rhea)

Why #2 Priority?

• Moderate frequency, still meaningful volume:
  Couple travellers typically take 4–5 trips a year, averaging 8–10 flights annually. While not as frequent as business users, this volume is still significant and highly predictable, especially during birthdays, anniversaries, and long weekends.
• High intent:
  They research thoroughly, often compare across platforms, and don’t mind spending a bit more if it guarantees a great experience.
• TAM is growing:
  Millennials + Gen Z couples now prioritize travel as a lifestyle choice. This segment is exploding in metro & Tier 1 cities. They are also increasingly booking flights themselves vs relying on agents.

User Goals Include:

1. WHO is signing up?
2. WHAT are they trying to do?
3. WHY are they signing up?

Notes:

• All four goals here are Functional, since flight booking is inherently a task-driven flow (vs. emotional discovery, like hotels or curated experiences).
• Even for ICP 3 (couples), though the reason for travel may be emotional, the act of booking flights remains functional.

I’ve completed the onboarding teardown for MakeMyTrip in the most detailed way possible, not just skimming through it but really putting myself in the shoes of a first-time user.

🔗 You can find the full teardown here: [MakeMyTrip Onboarding Teardown]

By concentrating on the website experience, I wanted to deeply understand how MakeMyTrip prioritizes features, messaging, and nudges in a high-stakes environment like flight bookings. In such a competitive space, it's not just about “working smoothly” anymore, it’s about how well the website can build trust, reduce friction, and drive the user to that final confirmation button.

Now, based on the teardown — here are the key cognitive biases being leveraged:

1. Anchoring Bias: Early on, MMT shows you the “cheapest” fares which sets a mental anchor. Any higher price after that feels premium or "too much", making you more likely to settle quickly.
2. Sunk Cost Fallacy: "You've come this far, what's ₹99 more?"
3. Drip Pricing - Hidden convenience fees revealed at checkout.

Why I didn't choose mobile app onboarding (for now):

While mobile apps are strong, most users from our sample group still rely on desktops for big-ticket bookings like flights. They associate laptops with higher confidence, better overview, and fewer mistakes. Also, for first-time users or non-tech savvy audiences (like parents or older travellers), the website gives a greater feeling of “control” over the booking process.

Quick competitor benchmarking:

Compared to some of its top competitors:

• Ixigo has a cleaner, less cluttered onboarding with fewer upsells early in the journey. Their UI is minimal, but that sometimes makes them feel “less trustworthy.”
• Cleartrip is straightforward and faster to use, but doesn't have as many trust nudges or filters as MMT.
• Goibibo is somewhat similar to MMT in structure, but their overuse of banners and gamification often backfires in serious booking contexts.

What sets MMT apart is its comprehensive flight visibility, brand trust, and consistent flow, but it could definitely simplify the experience to reduce friction and decision fatigue.

Well :)

Based on User Research Data

Satisfaction Scale: 1-10

Based on our user interviews, I identified that 100% of users value filters and transparency. This told me these aren't just nice to have features, they're core to user decision-making.

Users who engage with filters early are showing they're not just price shopping - they're evaluating MMT as their primary booking platform. This behaviour correlates with higher conversion.

I used the 'X action in Y time' framework to create testable hypotheses. For example, 'Use filters within first session' because our data shows this is a universal user behaviour that indicates deeper engagement.

Let's look at them👇

Hypothesis 1: User does their first flight search within 2 minutes of landing on the homepage.

This is the first key action that tells us the person is here to actually book a flight, not just randomly checking the site. If someone lands and quickly starts searching, it means the homepage is working well—it’s intuitive and it nudges them toward the core value quickly. If they don’t search for a while or drop off, maybe there’s confusion or too much going on.

Why it’s an activation metric:
Because flight search is the real starting point of the journey. It tells us that the person has intent and has started engaging with the product. This is a mini “aha!” moment for the user.

Metrics to track:

• Day 1 activity: We can track how many users performed a flight search on their first day itself. This tells us if people are reaching the key action early.
• TAT: Track time taken from homepage load to first search. This will tell us if people are confused or cruising smoothly.
• Homepage bounce rate.
• Clicks on the "Search" CTA.
  

Hypothesis 2: User applies at least one filter (like price or stops) within 3-5 minutes of seeing flight results.

Once a person gets flight results, them applying a filter shows that they’re not just casually browsing, they’re getting serious and want something specific. It’s a sign of stronger intent. If they apply filters quickly, we know the results page is helpful and not overwhelming.

Why it’s an activation metric:
Because filter usage = active comparison. It means the user is starting to trust the platform to help them find the best deal. That’s a huge early sign that the person is becoming engaged.

Metrics to track:

• TAT: From flight results to first filter applied. (Again, this can be tracked on Mixpanel or Amplitude.)
• D7 : can later compare if people who applied filters are more likely to return in a week.
• Filter usage % (how many users apply any filter)
• Drop-off after seeing search results
• Scroll depth

Hypothesis 3: User adds a flight to cart within 10 minutes of viewing flight details.

When someone checks out the flight details (baggage, timing, refund policy, etc.) and adds it to the cart, it’s a big signal. It means they’re strongly considering buying. If many people reach this step, great. If very few do, either something’s wrong with the details page or price/friction is high.

Why it’s an activation metric:
This is the closest you get to intent without a purchase. This also helps us identify who to retarget, nudge, or offer deals to. If they don’t reach cart, we can’t even re-engage properly.

Metrics to track:

• Cart abandonment rate.
• Subscription Rate vs Retention: In this case, substitute "subscription" with “add-to-cart.” How many people who add to cart come back or complete the booking?
• D1 vs D7 Retention: Are people who added to cart more likely to come back?
• TAT: Time taken from viewing details TO adding to cart.

AND WE'VE FINALLY REACHED OUR LOCATION!