MakeMyTrip's Dynamic Pricing in Travel Booking: A Technology-Driven Revenue Strategy

Industry & Competitive Context

India's online travel market represents one of the most dynamic digital commerce segments in Asia. According to industry data cited by market research aggregators, the Indian online travel market was estimated at approximately $23 billion in 2025 and is projected to grow at a compound annual rate of around 7–8% toward $34 billion by 2030. The structural drivers are well-documented: rising middle-class incomes, expanding low-cost carrier penetration, post-pandemic revenge travel, and surging smartphone and internet adoption — particularly in Tier 2 and Tier 3 cities. The Indian online travel agency (OTA) landscape is dominated by MakeMyTrip Group (comprising the MakeMyTrip, Goibibo, and redBus brands), with domestic competitors including EaseMyTrip, Yatra Online, Cleartrip (owned by Flipkart), and Ixigo, alongside global incumbents such as Booking.com and Expedia. What distinguishes the Indian OTA context from its Western counterparts is the structural heterogeneity of demand: a price-sensitive mass market coexists with a rapidly growing premium leisure traveler segment, while the ratio of first-time digital travel bookers remains high relative to mature markets. This heterogeneity makes pricing strategy not merely an optimization problem but a fundamental strategic lever for differentiation and margin management. The airline ticketing segment, historically the OTA's core revenue driver, carries structurally thin margins due to price transparency, commoditization, and airline commission caps. Hotels and holiday packages, by contrast, offer materially higher adjusted margins — a structural reality that has reshaped how MakeMyTrip has prioritized its pricing investments. As confirmed in MakeMyTrip's official FY2024 earnings release (dated May 15, 2024), the Adjusted Margin percentage for the Hotels and Packages segment stood at 17.9% versus only 6.5% for Air Ticketing, underscoring why dynamic pricing in the non-flight segments carries outsized strategic importance.

Brand Situation Prior to the Strategy

MakeMyTrip was founded in 2000 by Deep Kalra, initially targeting the Indian diaspora in the United States with itinerary services between the US and India. The company entered the Indian domestic market in 2005, capitalizing on the simultaneous emergence of low-cost carriers (LCCs) — a gap that established travel agents did not serve. MakeMyTrip was listed on the NASDAQ on September 17, 2010, in the first IPO by an Indian company in the US since July 2006, raising approximately $80.5 million at a valuation of $478 million (Wikipedia).

By the mid-2010s, the Indian OTA market had become fiercely competitive, characterized by heavy discounting, high customer inducement costs, and structurally loss-making operations. The turning point came in October 2016 when MakeMyTrip and Ibibo Group — then India's largest travel group, owner of Goibibo and redBus — announced a merger through an all-stock transaction valued at approximately $720 million. The deal closed on January 31, 2017, as confirmed in the Wikipedia entry for Ibibo, which cites MakeMyTrip's acquisition of 100% equity interest in Ibibo Group. Also in January 2016, China's Ctrip (now Trip.com) agreed to invest $180 million in MakeMyTrip through convertible bonds. In 2019, Ctrip further increased its stake by acquiring 42% of MakeMyTrip from Naspers. The post-merger entity commanded a dominant position across flight, hotel, and intercity bus ticketing. The combination also brought substantial customer data scale — a prerequisite for machine learning-based pricing systems. However, prior to deploying sophisticated dynamic pricing infrastructure, MakeMyTrip faced a strategic problem common to all high-traffic OTAs: the tension between offering the most competitive visible price to attract booking intent, while simultaneously maximizing per-transaction adjusted margin across a non-homogenous product inventory. Traditional rule-based promotional pricing was insufficient for this dual objective at scale.

Strategic Objective

MakeMyTrip's documented strategic objectives, as stated in multiple investor presentations and earnings calls available through its official investor relations site (investors.makemytrip.com), have consistently centered on three pillars: (1) growing gross bookings, (2) improving adjusted operating profit margins, and (3) enhancing personalized customer experience. Dynamic pricing functions as the operational mechanism that bridges all three. As confirmed in MakeMyTrip's FY2024 official earnings release, the company articulated its goal as serving customers through "a comprehensive portfolio of travel and ancillary products with personalised experiences." The statement from Group CEO Rajesh Magow in the May 2024 earnings release specifically noted that the company's strategy to deliver "personalised experiences" across both leisure and business travel was yielding measurable financial results. The strategic objective of dynamic pricing, therefore, is not merely revenue maximization in the classical sense; it is the monetization of personalization — pricing the right inventory to the right user segment at the right point in the booking funnel, while managing customer inducement costs (which are reported as a reduction of revenue in MakeMyTrip's IFRS financials).

Campaign Architecture & Execution

MakeMyTrip's dynamic pricing architecture operates across several publicly documented dimensions, though specific algorithm design and proprietary model specifications are not disclosed in official filings.

User Segmentation as the Foundation. MakeMyTrip's investor presentations and earnings commentary confirm the company's use of behavioral and transactional data to segment users. Group CEO Rajesh Magow stated during the October 2024 earnings call (as reported by Phocus Wire and Skift) that the company's AI assistant Myra had "significant traction among new and non-metro users," indicating segment-differentiated product delivery. The company classifies users by their booking stage and history — first-time searchers, repeat browsers, and confirmed past bookers — and delivers differentiated pricing signals, discounts, and recommendations based on these cohorts. This is consistent with the company's stated emphasis on user personalization in investor materials.

Hotels & Packages as the Pricing Battleground. Given the material difference in adjusted margins between air ticketing and hotels (6.5% vs. 17.9% as per FY2024 Q4 financials), MakeMyTrip's pricing investment is disproportionately focused on the accommodation segment. The FY2024 earnings release confirms that the Hotels and Packages adjusted margin increased by 41.3% year-over-year in Q4 FY2024 on a constant currency basis, while gross bookings in this segment grew 28.8%. This divergence — margin growing faster than bookings — is consistent with successful dynamic pricing execution: pricing power increasing without a proportional sacrifice in volume.

Generative AI and the Myra Platform. The most formally documented evolution of MakeMyTrip's pricing technology is the Myra AI travel assistant. As reported by Phocus Wire (August 2025) and confirmed by CEO Rajesh Magow in public earnings commentary reported by Skift (October 2024) and Media Nama (November 2025), Myra was initially launched to streamline international flight bookings and subsequently expanded to hotel and homestay bookings. The CEO confirmed that Myra provides "real-time pricing and availability" to users through conversational queries. By Q2 FY2026 (fiscal quarter ending September 2025), the company reported that Myra had scaled to 25,000 conversations daily and that over 35% of travelers engage with the assistant up to 90 days before their trip. One in four users returns to Myra for queries about itineraries, visa requirements, hotels, and experiences — as stated by the CEO on the earnings call per MediaNama reporting.

GenAI for Pricing and Availability Queries. Skift (October 2024) specifically reported that MakeMyTrip was deploying generative AI to "handle pricing and availability queries, as well as provide personalized hotel recommendations," citing the company's earnings call. This confirms the direct application of large language model-based systems to pricing interaction layers, not merely to content generation. Additionally, as reported by Phocus Wire (October 2025), the company launched a generative AI-powered pre-sales chatbot with an "agentic seller persona for advanced search and quick actions," designed to improve conversion rates at the top of the booking funnel.

Customer Inducement Costs as a Pricing Tool. A distinctive feature of MakeMyTrip's pricing architecture is the formal treatment of promotional discounts as "customer inducement costs" recorded as a reduction of revenue under IFRS accounting. In Q4 FY2024, customer inducement costs in Air Ticketing were $28.6 million (down from $36.2 million in Q4 FY2023), while customer inducement costs in Hotels and Packages were $31.5 million (up from $22.1 million). This asymmetric movement — reducing air discounting while increasing hotel discounting — reflects a deliberate strategic reallocation of pricing investments toward the higher-margin hotels segment, with dynamic tools enabling more targeted discount delivery.

No verified public information is available from official MakeMyTrip sources on the specific machine learning models used, the number of pricing signals processed per transaction, or the technical infrastructure underlying the pricing engine.

Positioning & Consumer Insight

MakeMyTrip's pricing strategy is anchored in a consumer insight that it has communicated publicly: travel booking in India is a high-involvement, multi-session planning process. The company's official communications consistently acknowledge that users — particularly in leisure travel — engage with the platform across multiple sessions before completing a booking, with price as both an initial signal of affordability and a final trigger for commitment. The Myra data, specifically the statistic that 35% of travelers engage with the assistant 90 days before travel, validates this long planning window. The pricing positioning is therefore not simply "cheapest price" but "most relevant price at the right moment." This is distinct from a pure lowest-price strategy (associated with brands like EaseMyTrip, which has publicly positioned itself on zero-convenience-fee transparency). MakeMyTrip's premium market position, supported by its MMTBLACK loyalty program and comprehensive product breadth, allows it to price for perceived value rather than pure commodity benchmarking. The result is a dual-segment positioning: competitive on headline prices to capture search-intent traffic, while monetizing intent through well-timed, personalized upsells and package bundling — the mechanism through which Hotels and Packages outperforms Air Ticketing on margins. The company has also explicitly identified Tier 2 and Tier 3 cities as a growth frontier. Rajesh Magow noted in the Q2 FY2026 earnings call (per Media Nama, November 2025) that voice adoption of Myra in Tier 2 and Tier 3 cities is "50% higher than in metros," and that "60% of voice queries come in English compared to just 20% in text chat." This behavioral divergence has direct pricing implications: non-metro users may exhibit different price elasticities and booking timelines, requiring differentiated pricing signals to optimize both conversion and margin.

Media & Channel Strategy

MakeMyTrip's channel strategy for dynamic pricing delivery is primarily app-centric and mobile-first. The company operates across its MakeMyTrip, Goibibo, and redBus mobile applications and web platforms, with the mobile app serving as the primary personalization surface. MakeMyTrip has disclosed in investor presentations its emphasis on a "travel super-app approach, offering comprehensive travel and related services across our platforms for retail, trade and corporate customers" (as attributed to Group COO Mohit Kabra per PhocusWire, October 2025).

Business & Brand Outcomes

The following outcomes are sourced exclusively from MakeMyTrip's official FY2024 earnings release (May 15, 2024, available at investors.mmtcdn.com) and credible trade publications reporting on earnings calls:

Gross Bookings. MakeMyTrip's full-year FY2024 gross bookings reached $7,954.4 million, a 24.9% increase year-over-year on a constant currency basis, up from $6,566.2 million in FY2023.

Revenue. Full-year FY2024 revenue was $782.5 million, a 35.7% increase in constant currency over FY2023's $593.0 million.

Adjusted Operating Profit. Full-year FY2024 Adjusted Operating Profit was $124.2 million, representing a 76.7% year-over-year increase from $70.3 million in FY2023. This was described by management as the company's "best-ever financial performance" in its fiscal year 2024 earnings release.

Hotels & Packages Performance. Full-year FY2024 Adjusted Margin in Hotels and Packages was $348.9 million, a 38.4% increase in constant currency, with the Hotels and Packages Adjusted Margin percentage improving to 17.9% in Q4 FY2024 versus 16.3% in Q4 FY2023 — indicating improving pricing efficiency in the most margin-rich segment.

Fiscal Year 2025 Gross Bookings. MakeMyTrip reported record gross bookings of approximately $9.8 billion for FY2025, representing approximately 30% growth over FY2024, as cited by multiple market reports referencing the company's public disclosures.

Q3 FY2025 Results. As reported by Phocus Wire (January 2025), Q3 FY2025 gross bookings increased 27% to $2.6 billion; adjusted operating profit rose to $46 million from $33 million year over year; and net profit improved to approximately $45 million from $39 million year over year.

Myra AI Engagement. As per Media Nama (November 2025) citing the CEO's earnings call statements: Myra scaled to 25,000 daily conversations; over 35% of travelers engage with Myra 90 days before travel; one in four users returns for itinerary and ancillary queries.

Market Leadership. MakeMyTrip Group — including Goibibo and red Bus — commands dominant market position across India's OTA segment, with red Bus holding approximately 70% of India's online intercity bus ticketing segment, as cited in market analyses referencing the company's competitive disclosures.

Strategic Implications

1. Pricing as a Data Moat, Not Just a Revenue Tool. MakeMyTrip's evolution toward AI-powered dynamic pricing is a canonical example of using proprietary behavioral data as a structural competitive barrier. Each interaction — a search, a session abandoned, a price alert set, a booking completed — generates signal data that improves the next pricing decision. As the platform scales, the pricing model's quality improves non-linearly, creating an advantage that competitors with smaller data sets cannot easily replicate. This is the true strategic value of the Myra platform: it is simultaneously a customer experience layer and a data-capture mechanism.

2. The Margin Mix Strategy. MakeMyTrip's deliberate reduction in air ticketing customer inducement costs (from $36.2M to $28.6M in Q4) while increasing hotel inducement costs (from $22.1M to $31.5M in Q4) is a textbook illustration of portfolio-level pricing strategy. Air tickets, as commodities, are won on headline price and offer limited margin accretion. Hotels, as experience-differentiated products, allow for more value-based pricing and cross-sell bundling. The company is essentially using dynamic pricing to migrate its revenue mix toward higher-margin segments — a strategic deployment of promotional capital rather than a defensive discounting response to competition.

3. Personalization as Price Discrimination — Ethically Applied. MakeMyTrip's use of user segmentation and behavioral history to serve differentiated pricing and offers is, from an economic standpoint, a form of second-degree and third-degree price discrimination. The strategic challenge for the firm is that excessive personalization — where identical users perceive materially different prices for identical products — risks consumer backlash (as Uber and Amazon have experienced). MakeMyTrip's approach of using personalization primarily to match products and offers to user stage (search vs. buy intent) rather than to charge different prices for identical inventory represents a relatively consumer-aligned implementation of this strategy.

4. The Tier 2/3 Frontier as a Pricing Testing Ground. The observation that voice adoption on Myra is 50% higher in non-metro cities than metros suggests not merely a channel preference difference but a fundamentally different user journey. Non-metro users may rely more heavily on conversational interfaces to navigate complex pricing, potentially reducing the friction in price discovery. This creates an opportunity for MakeMyTrip to calibrate dynamic pricing for different geographic demand curves — a segmentation strategy that could yield disproportionate margin expansion from a currently underpenetrated customer cohort.

5. Generative AI as a Pricing Interface Revolution. The shift from algorithm-only dynamic pricing (where prices change in the background) to agentic AI interfaces (where users actively query pricing and availability) represents a fundamental change in how consumers interact with price information. MakeMyTrip's Myra, positioned as a "trip planning assistant" rather than a "pricing bot," framing is deliberate — it anchors the user's interaction around planning value rather than price anxiety. This is a sophisticated positioning move that could reduce the price sensitivity of users who engage with the assistant, since value-framed discovery conversations shift willingness to pay upward.

Discussion Questions

1. MakeMyTrip strategically reduced its air ticketing customer inducement costs while simultaneously increasing hotel inducement costs in FY2024. What does this reveal about the firm's theory of competitive advantage across different product verticals, and how does it reflect the tension between market share defense and margin improvement in a multi-product OTA platform?

2. The company's Myra AI assistant simultaneously serves as a customer experience feature and a data-capture mechanism. Using the lens of platform economics, how does this dual function create compounding advantages for MakeMyTrip's dynamic pricing capability — and what regulatory or consumer trust risks might it generate as AI engagement deepens?

3. MakeMyTrip's dynamic pricing architecture treats "customer inducement costs" as a revenue reduction rather than a marketing expense under IFRS accounting. How does this accounting treatment affect investors' perception of pricing efficiency, and what should analysts look for beyond revenue figures when evaluating the success of an OTA's dynamic pricing strategy?

4. EaseMyTrip has publicly positioned itself on a zero-convenience-fee, no-hidden-costs promise — directly countering dynamic and opaque pricing models. Given MakeMyTrip's dominant market share, under what market conditions (consumer segment shifts, regulatory change, competitor scale) could this transparency-first strategy erode MakeMyTrip's pricing power, and how should MakeMyTrip preemptively respond?

5. MakeMyTrip's Myra reports that 60% of voice queries in Tier 2/3 cities come in English, versus only 20% in text chat. What does this behavioral divergence suggest about the relationship between channel interface design, linguistic accessibility, and willingness to engage with AI-mediated pricing — and how should MakeMyTrip design its regional pricing strategy for the next 100 million users it aims to reach?