Google Pay’s Scratch Card Rewards System

Executive Summary

When Google launched its India-first payments app Tez in September 2017, it entered a market that was simultaneously a greenfield opportunity and a fiercely crowded competitive arena. Paytm had over 200 million wallet users. PhonePe was backed by Flipkart and Walmart. BHIM had the Government of India's direct endorsement. Google had none of these structural advantages. What it had was a deep understanding of behavioural psychology and the willingness to apply it systematically as a growth strategy. The Tez Scratch Card system — a probabilistic, variable-reward mechanism tied to every eligible UPI transaction — was not an afterthought or a promotional add-on. It was the centrepiece of a precisely engineered incentive architecture designed to convert digital payment behaviour from a rational choice into a compulsive habit. This case examines how that design worked, why it succeeded in the short term, and what its long-term strategic implications reveal about the economics and ethics of gamified growth.

1. Industry & Competitive Context

India's digital payments market was structurally detonated, not gradually developed. In November 2016, the Government of India demonetised ₹500 and ₹1,000 banknotes — together representing approximately 86.4% of all currency in circulation at the time — forcing hundreds of millions of Indians into digital payment behaviours they had not previously adopted. The Unified Payments Interface (UPI), an interbank real-time payment protocol developed by the National Payments Corporation of India (NPCI), provided the infrastructure on which this shift occurred. UPI transaction volumes surged following demonetisation, growing from 17 million transactions in August 2017 to 30.8 million in September 2017 — an 85% month-on-month increase, as reported by NPCI data contemporaneously covered by Media Nama. The competitive landscape Google entered when Tez launched on September 18, 2017 was already defined by established players with structural advantages. Paytm had entered digital payments as early as 2014 and had accumulated significant brand equity among urban consumers. PhonePe, backed by Flipkart and subsequently by Walmart, had launched on the UPI network in August 2016. BHIM, the government's own UPI application launched in December 2016 with Prime Minister Modi's direct endorsement, had recorded 10 million downloads within its first ten days. Together, BHIM and PhonePe accounted for 86% of all UPI transactions as of August 2017, as reported by MediaNama's analysis of NPCI data at the time of Tez's launch. Google entered this market twelve months after PhonePe and with no pre-existing user base in Indian digital payments. Its global payments product, Android Pay, was unsuitable for India's market conditions — as Caesar Sengupta, VP of Google's Next Billion Users initiative, stated publicly at the Tez launch event and in a Q&A session reported by Nasdaq: the low penetration of NFC-equipped smartphones and the near-absence of credit card holders (fewer than 25 million credit cards in a population of 1.3 billion) made Android Pay's global model inapplicable in India. This necessitated a fundamentally different product and go-to-market strategy.

2. Brand Situation Prior to the Scratch Card Strategy

Google's brand in India in 2017 was powerful but category-generic. Indians used Google Search, Google Maps, and YouTube extensively, but these products established Google as an information and media platform — not a financial services brand. In payments specifically, Google had no brand equity, no user relationships, and no merchant network. By contrast, Paytm had years of consumer-facing advertising, offline merchant QR codes, and a wallet ecosystem that had grown dramatically through demonetisation. Google's strategic challenge was therefore not one of brand awareness but of behavioural displacement: it had to convince consumers who were already using other digital payment platforms — or still preferring cash — to switch to or adopt Tez as their primary UPI app. In a market where UPI transactions are interoperable (any UPI ID can send to any other regardless of app), functional differentiation was minimal. The payment infrastructure was identical across apps. Speed, security, and interface were quickly matched across competitors. In this context, sustainable user preference could not rest on product features alone — it required a mechanism that created habitual usage independent of functional superiority. The Tez Scratch Card system was Google's answer to this challenge.

3. Strategic Objective

The scratch card reward system served three documented strategic objectives operating across different time horizons. The immediate objective was activation and onboarding: converting new app installs into first transactions as rapidly as possible, collapsing the gap between download and first payment behaviour. Google addressed this explicitly at launch by nudging new users to complete an initial transaction of as little as ₹1 upon joining — a mechanic documented in the Observer Research Foundation's published policy analysis — ensuring that every new user experienced their first scratch card reward during the onboarding flow itself. The medium-term objective was habit formation: converting single-transaction users into frequent, habitual users through a reward structure that maintained behavioural engagement across the weeks and months following initial adoption. The variable-reward design of the scratch card — described in detail in the ORF analysis — was specifically calibrated to maximise this objective. The long-term objective was platform scale: reaching a transaction volume and user base large enough to make Google Pay the default payment infrastructure for a material share of India's digital transactions, creating network effects that would sustain market position beyond the period of active cashback investment. As Caesar Sengupta stated in an official Google blog post published on September 18, 2017: "We wanted to build a product that can compete with cash. It needs to be simple, affordable, and work everywhere and for everyone."

4. Campaign Architecture & Execution

The scratch card reward system comprised three documented layers of incentive design, each serving a distinct growth function.

Layer 1: The Probabilistic Scratch Card (Core Mechanic)

At launch, Tez introduced a digital scratch card mechanism tied to every qualifying UPI transaction. As documented by the Observer Research Foundation (ORF) in its published policy analysis titled "The Weaponisation of Cashbacks on UPI by Google Pay," users received a digital scratch card after completing an eligible transaction. Upon "scratching" the virtual card within the app, users would receive either a cashback amount — credited directly to their bank account — or the message "Better Luck Next Time." Reward amounts were randomised and non-deterministic. At launch, as reported by India .com's contemporaneous coverage of the Tez launch event on September 18, 2017, scratch card rewards were offered up to ₹1,000 on transactions above a minimum threshold. Additionally, users were eligible to win ₹1 lakh weekly through "Lucky Sundays," as documented by Pymnts.com and Digit.in reporting on the launch. The design of this mechanic is strategically significant. Unlike Paytm's fixed cashback model — which offered a predetermined percentage return on transactions — Google Pay's scratch card was non-deterministic. The reward amount was unknown to the user before scratching. This is the defining characteristic of a variable-ratio reinforcement schedule — a reward structure documented in behavioural psychology literature (originally systematised by BF Skinner) as the most powerful schedule for establishing and maintaining persistent habitual behaviour. Variable-ratio schedules, in which rewards are delivered unpredictably following a behaviour, produce more compulsive and persistent engagement than fixed or predictable reward schedules. Finshots, a widely read Indian financial media publication, documented this mechanism explicitly in a January 2020 analysis: "Unlike a fixed cashback offer, a scratch card is much like a lottery ticket. In most cases, it's a dud… However, in the off chance that you hit the jackpot, you get a massive payout." Google also ensured that the digital interaction replicated the tactile, anticipatory experience of physical scratch cards — a product already familiar to Indian lottery participants. The "scratch" gesture on the smartphone screen, the moment of suspense between scratching and outcome reveal, and the emotional contrast between winning and "Better Luck Next Time" all leveraged an already-loaded cultural and emotional reference frame.

Layer 2: Referral Incentives (Viral Acquisition)

Google Pay extended its cashback model to cover referral-based user acquisition. As documented by the Tez/Google Pay Wikipedia article, new users who joined via referral received ₹51 credited to their bank account after completing their first qualifying transaction of at least ₹1. The referring user received an equivalent fixed reward. This fixed referral bonus — in contrast to the probabilistic nature of regular scratch cards — provided a guaranteed conversion incentive and was available up to a total earning cap per user, as documented in contemporary user analyses. The referral mechanic created a structural viral loop: existing users had a financial incentive to bring new users into the ecosystem, who were immediately rewarded upon first transaction, reducing the activation barrier to near zero.

Layer 3: Seasonal Campaign Extensions (Occasion-Based Intensification)

Google layered seasonal campaign extensions onto the core scratch card mechanic to create periodic intensification moments that re-engaged users and attracted new ones. The most extensively documented of these was the Diwali 2019 campaign, which introduced a collectible digital "diya" (lamp) mechanic: users received one of five different diya stamps for each qualifying transaction, and collecting all five yielded a guaranteed ₹251 cashback and entry into a ₹1 lakh lucky draw. As documented in LinkedIn analysis at the time and reported across Indian media, Google subsequently introduced a social layer — users could gift or request missing stamps from contacts in their network — converting the campaign into a network effect engine that returned dormant users and drew in new ones through peer participation. The ORF analysis also documented the "Lucky Friday" mechanic: a weekly ₹1 lakh prize draw for transactions of ₹500 or more completed before a specified time on Friday mornings. This time-gated mechanic created a recurring weekly behavioural rhythm, anchoring a specific transaction behaviour to a specific time-of-week trigger. As documented by the ORF, certain cashback programmes were not made available to Google Pay users in Tamil Nadu specifically because they were deemed to violate the Tamil Nadu Prize Scheme (Prohibition) Act 1979, which bans lottery-based systems. This regulatory exclusion is significant because it confirms that Google's own legal assessment classified the scratch card system as lottery-adjacent — an important strategic and ethical data point.

5. Positioning & Consumer Insight

The consumer insight underpinning Google Pay's scratch card strategy rests on two reinforcing observations about Indian digital payment consumers in the 2017–2020 period, both of which are documented in credible sources. The first insight is that the primary barrier to digital payment adoption was not distrust of technology, but the absence of a compelling reason to change existing behaviour. Cash worked. UPI was technically superior, but convenience alone does not displace deeply embedded behavioural habits — particularly among first-generation digital payment users. A small, probabilistic financial reward attached to each transaction created what behavioural economists call a "nudge": a non-coercive, choice-preserving prompt that makes the desired behaviour marginally more attractive than the status quo, repeated consistently enough to establish habit. The ₹1 minimum transaction threshold at onboarding was precisely this nudge: almost no effort, near-zero financial commitment, and an immediate reward experience that primed the habit loop. The second insight is about the psychology of aspiration in mass-market India. Fixed cashbacks of 2–5% on transactions are arithmetically rational but emotionally inert — they reward rational behaviour without triggering emotional engagement. The scratch card, by contrast, created the possibility of a disproportionate reward (₹800 back on a ₹100 transaction, for instance — an anecdote cited in Finshots' analysis). In a mass-market where the chance to win significantly more than you spent is experienced as genuine excitement rather than a statistically marginal event, the scratch card activated a qualitatively different emotional response than a guaranteed discount. It converted every transaction into a micro-lottery ticket, making the act of paying through Google Pay inherently more engaging than paying through a competitor's app, even when the probability of a meaningful reward was low. Tez's product design team explicitly identified two target user personas at launch, as documented in Increment's case study: working professionals motivated by cash rewards, and women and new internet users interested in managing finances securely. The scratch card mechanic was calibrated primarily to the first persona — the reward-seeking early adopter who would anchor and validate the platform before mass-market adoption followed.

6. Media & Channel Strategy

Google Pay's distribution and awareness strategy departed significantly from conventional fintech marketing playbooks, relying primarily on platform ecosystem leverage rather than paid advertising.

Pre-installation partnerships: At launch, Google partnered with Indian smartphone manufacturers Lava, Micromax, XOLO, Nokia, and Panasonic to pre-install Tez on devices, as documented by India .com's launch reporting and the Google official blog. These brands had strong penetration in the mid-range and entry-level Android market — precisely the device tier used by the mass-market Indian consumer Google was targeting.

Multi-language interface: Tez launched in eight languages — English, Hindi, Bengali, Gujarati, Marathi, Kannada, Tamil, and Telugu — as confirmed in the official Google blog post by Caesar Sengupta and corroborated by multiple contemporary news reports. This was a deliberate decision to make the product immediately accessible to non-English-speaking users, reflecting the "Next Billion Users" strategic mandate.

Bank partnerships: Tez launched with partnerships with Axis Bank, HDFC Bank, ICICI Bank, and State Bank of India, as documented by TechRadar's launch coverage. These relationships provided both the UPI infrastructure and the institutional credibility that Google lacked as a new entrant in financial services.

Referral network effects: As documented in the official Google Help page for India, Google Pay's referral programme rewarded both referrers and new users upon the first qualifying transaction, using unique referral codes distributed through the existing user base. This converted Google Pay's growing user base into a distributed acquisition channel, without media spend.

Ecosystem integration: The Google Pay rewards system was later integrated across Google's existing India user touchpoints including the Google Search app and Gmail, as part of the broader unification of payments within the Google account ecosystem — a strategy Caesar Sengupta described at the August 2018 Google for India event, reported by Factor Daily. No verified public information is available on the specific media buying budget, advertising spend breakdown, or paid campaign ROI metrics associated with Google Pay's scratch card strategy in any period.

7. Business & Brand Outcomes

Early adoption velocity: Within five weeks of its September 18, 2017 launch, Tez had acquired over 7.5 million users and processed over 30 million transactions, as confirmed by Caesar Sengupta, VP of Google's Next Billion Users initiative, in a statement reported by Media Nama (October 2017). Within 37 days of launch, Tez had approximately 8.5 million installations, as documented in the Tez Wikipedia article.

Three-month milestone: By February 2018 — three months after launch — Tez was approaching 12 million active users and had processed 140 million total transactions, as disclosed by Caesar Sengupta at a Google event in New Delhi and reported by Android Authority. At this time, NPCI data cited at the same event indicated that Tez accounted for 70% of all UPI transactions between October and November 2017.

Merchant scale: By August 2018, Google Pay had 22 million monthly active users across 3 lakh (300,000) villages, towns, and cities in India, and reported an annualised transaction run-rate of $30 billion, as disclosed by Caesar Sengupta at the August 2018 Google for India event and reported by Facto Daily.

UPI market share: NPCI's publicly reported data, as covered by Inc42, shows that by March 2023, Google Pay processed 305.44 crore UPI transactions worth ₹4.83 lakh crore in a single month, representing 34.75% of all UPI transactions by volume and 33.75% by value. As of Q3 2024, Google Pay held approximately 37% of UPI transaction volume, as reported by Statista citing NPCI data. As of August 2025, Google Pay processed approximately 7.4 billion monthly transactions, representing approximately 35.53% of UPI transaction value, as reported by DD News citing NPCI data, making it the second-largest UPI platform by both volume and value behind PhonePe.

Regulatory recognition of lottery-adjacent mechanics: The ORF published analysis explicitly confirms that Google Pay's scratch card cashback programmes were excluded from availability for users in Tamil Nadu because they were assessed to violate the Tamil Nadu Prize Scheme (Prohibition) Act 1979, which bans lottery-based systems. This exclusion, a documented regulatory fact, confirms the probabilistic nature of the reward mechanic and its classification under existing gambling-adjacent consumer protection frameworks.

NPCI market cap response: In November 2022, NPCI proposed a 30% volume cap on third-party app providers operating on the UPI network, with a compliance deadline subsequently extended. As reported by Business Today, the cap was specifically framed as a response to the market dominance of PhonePe and Google Pay, which together controlled over 86% of UPI transaction volume. This regulatory intervention is an indirect, documented measure of the success of Google Pay's cashback-driven user acquisition strategy in producing a structurally concentrated market.

8. Strategic Implications

A. Variable-Ratio Reinforcement as a Growth Engineering Tool. Google Pay's scratch card system is among the most explicitly documented applications of behavioural psychology principles in Indian consumer marketing. The design choice — randomised reward amounts rather than guaranteed percentages — was not accidental. It converted every eligible transaction into a probabilistic event with a non-deterministic outcome, activating the psychological anticipation mechanism that behavioural science has consistently identified as more habit-forming than predictable reward structures. The strategic implication for platform marketers is significant: when the core product (UPI payment) is functionally commoditised and offers no inherent emotional engagement, the engagement architecture around the product becomes the primary brand differentiator. Google Pay did not build a better payment app; it built a more addictive payment experience.

B. The Onboarding Funnel as Reward Delivery Vehicle. The ₹1 minimum transaction onboarding mechanic — nudging new users to complete a near-zero-cost first transaction that immediately yields a scratch card — is a masterclass in funnel design. The conventional onboarding challenge in digital payments is the gap between download and first transaction: most users who install a payment app never complete their first payment. By embedding the reward trigger into the onboarding flow itself, Google collapsed this gap and ensured that 100% of users who completed setup experienced a positive emotional moment (scratch card anticipation and outcome) before any rational usage decision was made. This is a product marketing innovation, not merely an advertising one.

C. The Market Concentration Paradox. The scratch card strategy successfully drove Google Pay to a dominant position in India's UPI market, but this very success created a regulatory consequence: NPCI's 30% market cap proposal was a direct response to the concentration produced by Google Pay and Phone Pe's cashback-driven dominance. For strategy students, this represents a classic paradox of platform competition: the tools that most effectively build market share can simultaneously attract regulatory intervention that caps the market share they have built. Google Pay's long-term market position will be shaped as much by how NPCI implements or revises the concentration cap as by Google's own competitive strategy.

D. Ethical Dimensions of Gamified Financial Products. The ORF's published analysis draws an explicit parallel between Google Pay's scratch card system and "loot box" mechanics in video games — characterising both as probabilistic reward systems that may produce gambling-adjacent behaviour. The Tamil Nadu exclusion is not merely a regulatory footnote: it is a documented precedent establishing that at least one Indian state government classified these mechanics as lottery-based under existing consumer protection law. For marketing strategists and product designers, this creates a genuine ethical and regulatory frontier: at what point does a variable-reward engagement mechanic in a financial services product cross from "behavioural design" into "gambling-adjacent practice"? This question is now being asked by regulators in the UK and US about digital loot boxes, and may arrive in Indian fintech regulation with greater force as UPI scales toward the government's projected targets.

E. The Limits of Cashback-Led Acquisition. The market share trajectory is analytically informative: Google Pay reached approximately 60% of UPI volume by September 2019, per publicly reported data, but this position eroded to approximately 37% by Q3 2024, as PhonePe built out superior merchant coverage and product breadth. The ORF analysis noted that when Paytm's CEO scaled back cashback promotions, transaction volumes immediately declined — a documented confirmation that cashback-driven volume is partially or wholly dependent on continued cashback investment rather than durable habit formation. This raises a fundamental question about the long-term brand equity built by the scratch card system: did it create loyal Google Pay users, or did it create price-sensitive transaction-seekers who will follow the next platform that offers better rewards?

Discussion Questions

1. Variable-Ratio Design vs. Guaranteed Cashback: Google Pay chose randomised, variable scratch card rewards rather than a guaranteed percentage cashback model used by some competitors. Using behavioural economics frameworks (variable-ratio reinforcement, dopamine-driven anticipation, habit loops), evaluate the strategic superiority of this design for habit formation. Under what market or competitive conditions might a guaranteed cashback model be preferable to a variable-reward model?

2. The Ethics of Gamified Financial Services: The Observer Research Foundation, a credible Indian policy think tank, characterised Google Pay's scratch card system as "weaponisation of cashbacks" and drew parallels to gambling-adjacent "loot box" mechanics in video games. The Tamil Nadu state government excluded these programmes under lottery prohibition laws. As a marketing ethicist and product strategist, construct a framework for evaluating when behavioural design in financial products crosses a line from responsible engagement to exploitative design. Should regulators intervene, and if so, how?

3. Platform Concentration and Competitive Sustainability: Google Pay's cashback strategy helped it achieve a market-leading UPI position, which then triggered NPCI's 30% volume cap proposal. Analyse this dynamic using a competitive strategy framework. Was the concentration outcome a predictable consequence of Google's strategy, or an unintended externality? How should Google Pay adapt its growth strategy in a regulatory environment designed to prevent the concentration that its own strategy produced?

4. Acquisition vs. Loyalty: Documented market share data shows Google Pay declining from approximately 60% of UPI volume in 2019 to approximately 37% by 2024, despite maintaining its cashback programme. Using the customer lifetime value and brand equity frameworks, diagnose whether this trajectory represents a failure of the cashback strategy to build durable loyalty, or a structural competitive response by PhonePe that would have occurred regardless. What product or brand investment might have produced more durable market position?

5. The Zero-MDR Constraint: UPI transactions in India operate under a zero Merchant Discount Rate (MDR) regime — meaning Google Pay earns no transaction fee from the payments it facilitates. Google's scratch card cashback programme is therefore a cost centre with no direct revenue offset. Using a platform business model framework, evaluate how Google Pay's cashback investment creates monetisable value in adjacent markets (data, advertising, credit, insurance). Is this a sustainable model, and what evidence exists in Google's publicly documented India strategy to validate or challenge this assessment?