TL;DR

Zomato PM interview qa demands precision under pressure—70% of candidates fail to align product instincts with Zomato’s hyperlocal execution model. Answer like an operator, not a theorist.

Who This Is For

This breakdown targets candidates who understand that Zomato operates on thin margins and high-velocity execution, not theoretical frameworks.

  • Senior PMs with 5+ years in two-sided marketplaces who can demonstrate hard metrics on supply-side liquidity and demand elasticity without needing hand-holding.
  • Growth product leaders transitioning from hyper-local or food-tech ecosystems who have managed P&L responsibility for specific geographies or verticals.
  • Technical product managers capable of dissecting real-time logistics algorithms and explaining trade-offs between latency, driver utilization, and customer wait times.
  • Candidates who have survived rigorous data-heavy interview loops at tier-1 tech firms and can defend decisions using SQL-level granularity rather than vague intuition.

Interview Process Overview and Timeline

The Zomato Product Manager interview process in 2026 is not a test of your theoretical knowledge; it is a stress test of your operational resilience and data intuition. Having sat on the hiring committee for years, I can tell you that the timeline has compressed, but the bar for cognitive density has skyrocketed.

The entire cycle typically spans four to five weeks, though top-tier candidates often stretch this to eight weeks due to rigorous cross-functional calibration rounds. Do not expect a linear progression. You are being evaluated on how you handle ambiguity and shifting goalposts, much like you would when managing a live incident on the Zomato platform during a Friday night surge.

The process initiates with a resume screen that is far more aggressive than most applicants anticipate. We are not looking for a list of features you shipped. We are hunting for ownership metrics tied directly to unit economics. If your resume highlights user growth without mentioning burn rate, CAC, or retention cohorts, it gets discarded immediately.

The subsequent step is a 45-minute telephonic screen with a senior PM or a hiring manager. This is not a friendly chat. It is a rapid-fire validation of your first principles. You will be asked to dissect a specific Zomato problem, such as optimizing the delivery radius for Blinkit integration or reducing cancellation rates in tier-2 cities, within the first ten minutes. There is no X, but Y dynamic here where you get points for effort; you either demonstrate immediate structural thinking or the call ends early.

Once you clear the phone screen, you enter the core loop, which consists of three to four virtual onsite rounds. These are distinct and siloed. One round will focus entirely on Product Sense, specifically tailored to the hyper-local commerce ecosystem. You might be asked to design a feature for Zomato Gold that drives frequency without eroding margin. Another round will be purely analytical.

You will be given a raw dataset or a mock dashboard and asked to identify why a specific metric, say, average order value in South Delhi, dipped by 12% yesterday. We do not care if you know SQL syntax by heart, but you must know how to slice data to find the root cause.

A third round focuses on execution and leadership. Here, we probe how you navigate conflict between engineering constraints and business demands. We want to hear about times you killed a feature, not just times you launched one.

The final stage is the hiring committee review, followed by a potential chat with a VP or the CPO. This is where the real decision happens. The interviewers submit structured feedback forms with zero ambiguity.

There is no "maybe." You are either a strong hire, a weak hire, or a no-hire. A single "no-hire" with strong evidence regarding a core competency like data integrity or ethical judgment can veto the entire process. We have seen candidates ace three rounds and get rejected because they demonstrated an inability to prioritize customer trust over short-term revenue in a scenario-based question.

Timelines are strict. Feedback is expected within 24 hours of each round. If you do not hear back within three business days, it is rarely a good sign.

The company moves at a velocity that requires immediate alignment. We do not hold candidates in limbo out of politeness; we move fast because the problems we are solving change daily. In 2026, with the deep integration of AI into logistics and menu personalization, we expect candidates to have a point of view on how automation impacts the human element of food delivery.

Candidates often mistake the process for a series of hoops to jump through. It is not. It is a simulation of the job. The pressure you feel during the case study, the pushback you receive during the leadership round, and the scrutiny of your metrics are exactly what you will face when you are leading a squad responsible for millions of daily transactions.

We are not hiring for potential; we are hiring for immediate impact. If you cannot articulate how your past decisions moved the needle on profitability or efficiency, you will not survive the loop. The Zomato PM role demands a specific type of operator who thrives in chaos but maintains rigorous analytical discipline. The process is designed to filter for exactly that. If your preparation relies on memorizing frameworks rather than understanding the brutal realities of two-sided marketplaces, the timeline will end quickly for you.

Product Sense Questions and Framework

Zomato’s PM interviews test whether you can dissect real-world product problems with rigor, not just regurgitate frameworks. Expect questions that force you to balance user needs, business constraints, and market dynamics—often with incomplete data. Here’s what they’re actually evaluating.

First, the classics: “How would you improve Zomato’s search and discovery?” Most candidates default to algorithmic tweaks or UI polish. The mistake is ignoring the operational reality: 70% of Zomato’s GMV comes from repeat users, not new discovery. The better answer focuses on personalization for high-LTV cohorts—like surfacing “your usuals” for power users in metro cities where frequency is 8-10 orders/month. Not generic relevance, but habitual retention.

Another frequent scenario: “Design a feature for restaurant partners to boost visibility.” Weak answers propose bidding systems or gamified leaderboards. Strong ones recognize Zomato’s commission model (15-25% per order) and the tension between demand generation and partner profitability. The right move? A performance-based boost (e.g., “Spend 2% extra commission for a 10% CTR bump”) tied to measurable ROI. Not arbitrary incentives, but unit economics.

Then there’s the curveball: “Zomato Gold was sunset. Would you bring it back?” Most candidates analyze subscription mechanics. The sharp ones dig into the margin math: Gold’s infinite dining offers eroded restaurant margins by 12-15% in pilot cities, leading to partner churn. The framework isn’t “should we relaunch?” but “how do we align user delight with partner sustainability?” Answer: Tiered loyalty (e.g., “5% cashback for 5+ orders/month”) funded by Zomato’s ads business, not restaurant subsidies.

A telltale sign of a weak candidate is over-indexing on user growth. Zomato’s PMs are judged on GMV and contribution margin, not DAUs. When asked, “How would you increase order frequency in Tier 2 cities?” the losing answer is “localized marketing.” The winning one is “bundle groceries with food delivery to increase basket size,” leveraging Blinkit’s infrastructure (post-acquisition) to offset last-mile costs. Not top-of-funnel hacks, but bottom-line efficiency.

Lastly, expect a stress test: “A top restaurant threatens to delist unless we lower commissions. What do you do?” Mediocre responses involve negotiation or temporary discounts. The Zomato way? Run the numbers. If the partner drives 5% of local GMV but 8% of support tickets (due to high order volumes), the answer is to let them churn and reallocate resources to mid-tail restaurants with better margins. Not relationship management, but portfolio optimization.

The pattern is clear: Zomato doesn’t hire PMs who optimize for vanity metrics. They want those who can trade off growth, profitability, and partner health—with data, not intuition. Frameworks are table stakes; the edge is in the nuance.

Behavioral Questions with STAR Examples

When Zomato’s product management interview panel evaluates candidates, they look for evidence that you can translate ambiguous problems into measurable outcomes while navigating the fast‑moving, hyper‑local dynamics of food delivery. The STAR framework (Situation, Task, Action, Result) is the lingua franca for these behavioral probes, and the interviewers expect you to anchor each story in concrete numbers that reflect Zomato’s scale and priorities.

Situation: Scaling a New Restaurant Onboarding Flow

In early 2025, Zomato’s Hyperlocal team faced a 22 % drop‑off rate during the restaurant sign‑up process on the partner app, which threatened the quarterly target of adding 150 k new dining partners across Tier‑2 cities. The root cause was identified as a cumbersome KYC upload step that required partners to switch between three separate screens, increasing average completion time from 4.2 minutes to 7.8 minutes.

Task: Reduce Friction and Lift Conversion

My mandate was to cut the drop‑off by at least 10 percentage points within six weeks while ensuring compliance with RBI‑mandated verification standards. I needed to balance user experience with regulatory risk, coordinating with legal, ops, and the design system team.

Action: Data‑Driven Redesign and Pilot

I began by extracting funnel metrics from Mixpanel, confirming that 68 % of abandonments occurred at the document‑verification screen. I then facilitated a cross‑functional workshop to map the partner journey and identified three leverage points: consolidating ID and address proof into a single upload, introducing real‑time OCR validation, and providing inline tooltips that explained why each document was required.

Working with the design lead, I produced low‑fidelity prototypes that were tested with 30 active restaurant owners in Delhi and Bengaluru. Iterative usability testing showed a 35 % reduction in perceived effort. After legal sign‑off on the OCR storage policy, we rolled out a phased A/B test covering 5 % of new partner sign‑ups. The test group saw completion time drop to 3.9 minutes and the drop‑off fall to 12 %.

Result: Measurable Impact and Scale‑Up

Based on the test results, we approved a full rollout across all onboarding channels. In the first month post‑launch, partner acquisition rose from 9.5 k to 13.2 k per week, a 39 % increase that directly contributed to exceeding the quarterly target by 18 %. The improved flow also decreased support tickets related to verification by 27 %, freeing ops capacity for partner‑success initiatives.

Situation: Launching a Subscription‑Based Loyalty Program

Mid‑2025, Zomato’s growth team hypothesised that a paid loyalty tier could increase order frequency among high‑value users in metros, where the average order value (AOV) hovered around Rs. 380 and the repeat order rate was 31 %.

Task: Validate Hypothesis and Define MVP

I was tasked with designing an experiment to test whether a Rs. 99 monthly subscription offering free delivery and 5 % cashback would lift the repeat order rate by at least 8 percentage points without cannibalizing margin.

Action: Building a Controlled Experiment

I partnered with the analytics team to segment users based on past six‑month spend, isolating a cohort of 200 k users with an AOV > Rs. 500. We constructed a flipped‑coin random assignment: 100 k received the subscription offer via in‑app banner and email; the remaining 100 k served as control. The experiment ran for eight weeks, with daily tracking of order frequency, AOV, and delivery cost.

To mitigate risk, we capped the free‑delivery benefit at three orders per week and used a dynamic pricing model that adjusted cashback based on order margin. We also instituted a weekly health check with finance to monitor contribution margin impact.

Result: Positive Lift and Insight‑Driven Iteration

At experiment’s end, the treatment group showed a repeat order rate of 42 % (an 11 pp increase) and an average of 4.3 orders per user per month versus 3.5 in control. The incremental contribution margin remained positive at +2.3 % after accounting for subscription revenue and delivery subsidies.

Encouraged, we expanded the program to all Tier‑1 cities, adding a premium tier at Rs. 199 that included priority customer support. Six months later, the loyalty program contributed 6.2 % of total GMV, validating the initial hypothesis and providing a defensible moat against competing platforms.

Situation: Mitigating a Sudden Surge in Delivery Times During a Festival

During Diwali 2024, Zomato experienced a 48 % spike in order volume, pushing the average delivery time from 28 minutes to 44 minutes in Mumbai and Delhi, triggering a surge in customer complaints and a dip in the Net Promoter Score (NPS) from 42 to 31.

Task: Restore Service Levels Within 72 Hours

I needed to bring the 90th‑percentile delivery time back under 35 minutes without compromising order accuracy or incurring prohibitive overtime costs.

Action: Real‑Time Capacity Reallocation and Incentive Tweaks

I convened an emergency war room with ops leads, the fleet management team, and the data science group. Using live GPS data, we identified three micro‑zones where driver density was below 60 % of demand. We instantly re‑routed idle drivers from low‑demand corridors and surge‑priced those zones with an additional Rs. 15 per trip incentive. Simultaneously, we temporarily relaxed the minimum order value for free delivery in those zones to encourage batching, reducing the number of trips per order by 12 %.

We also pushed a proactive communication template to affected customers, apologizing for delays and offering a Rs. 20 coupon for the next order, which helped contain negative sentiment.

Result: Rapid Recovery and Learnings Institutionalized

Within 48 hours, the 90th‑percentile delivery time fell to 33 minutes, and NPS rebounded to 38 by the end of the week. The intervention added an estimated Rs. 1.2 million in incremental driver earnings but saved approximately Rs. 4.5 million in potential refunds and churn‑related loss. Post‑event, we codified the dynamic re‑routing algorithm into the fleet optimizer and instituted a quarterly “surge readiness” drill that now includes scenario planning for festival spikes.

These examples illustrate the depth of evidence Zomato’s interviewers expect: precise metrics, clear ownership of cross‑functional trade‑offs, and a focus on outcomes that align with the company’s growth levers—whether that is expanding partner base, increasing user lifetime value, or safeguarding service excellence during peak demand. Your STAR stories must reflect that rigor, not just a checklist of actions.

Technical and System Design Questions

Stop treating system design as a whiteboard exercise in abstract scalability. At Zomato, we do not care if you can draw a generic load balancer or recite the CAP theorem definitions from a textbook. We care if you understand the specific, messy constraints of India's hyperlocal delivery network. When a candidate walks in and starts designing for global scale without first asking about pin-code granularity or offline-first capabilities for delivery partners in low-connectivity zones, I stop the interview. That is not competence; that is pattern matching.

The reality of Zomato's architecture in 2026 is defined by the tension between real-time latency and data consistency across three distinct user states: the hungry customer, the restaurant kitchen, and the moving delivery partner. A classic trap candidates fall into is optimizing for the read-heavy customer app while ignoring the write-intensive, high-contention environment of the restaurant tablet.

You are not designing for X, but Y. You are not designing for a static menu display, but for the chaotic, millisecond-level synchronization of inventory counts when five hundred users in Bandra attempt to order the same limited-stock dish during the 8 PM rush.

Consider the geospatial indexing required for our delivery assignment engine. In 2026, with Zomato Instant expanding into non-food categories and Quick Commerce dominating the volume, the system must handle millions of concurrent location updates. A competent Product Manager does not just say "use Redis." They discuss the trade-offs of using S2 geometry versus H3 hexagons for our specific density patterns in Indian metros.

They acknowledge that in Mumbai, a 500-meter radius contains more potential demand nodes than entire cities in other markets. If your design does not account for the "thundering herd" problem where thousands of orders spike within a 2-kilometer radius simultaneously, causing database locks on the restaurant side, your system fails. We have seen outages where the ordering system stayed up, but the kitchen display systems lagged by four minutes because the write path was not decoupled from the customer read path. That is an unacceptable failure mode.

Another critical area is the handling of intermittent connectivity for our delivery partners. The Zomato Partner app operates in environments where 4G drops to 2G or goes offline entirely inside elevator lobbies or dense concrete structures. Your system design must include an offline-first strategy with conflict resolution mechanisms.

When a partner marks an order as delivered offline, and the timestamp syncs later, how does your system reconcile this with the customer's expected delivery window? How do you prevent fraud where a partner marks delivery before actually arriving? We look for candidates who propose local queueing with cryptographic signing of events, not just a simple retry logic.

Data consistency is the third pillar. In a distributed system spanning microservices for billing, inventory, loyalty points, and delivery tracking, you will face eventual consistency. The question is how you expose this to the user without breaking trust. If a user sees a refund processed in the app but the bank gateway has not yet confirmed it, how does your system state machine handle the transition?

Poor designs result in double-refunds or, worse, customers believing they have been scammed. We expect you to define the boundaries of consistency. For financial transactions, we demand strong consistency, even at the cost of latency. For live tracking of a rider's location, eventual consistency is acceptable, provided the drift is bounded within reasonable thresholds.

Do not waste time drawing generic boxes for "API Gateway" or "Database." Instead, walk us through the flow of a single order from the moment the "Place Order" button is tapped to the moment the rider's GPS pings the server confirming pickup. Discuss the specific failure points: What happens if the payment gateway times out but the restaurant accepts the order? What happens if the rider's app crashes mid-delivery? How do you reassign the order without delaying the customer by more than three minutes?

We are looking for architectural intuition grounded in business impact. A design that is technically perfect but takes six months to build is worthless in our speed-to-market culture. Conversely, a quick hack that collapses under Diwali traffic is equally useless.

The sweet spot is a system that acknowledges its own limitations and has explicit mitigation strategies for them. If you cannot explain how your design handles a 10x spike in traffic during a IPL final or a monsoon-induced surge in demand while maintaining sub-second response times for the critical path, you are not ready to lead product at Zomato. We do not hire theorists. We hire engineers of business logic who understand that code is just the vehicle for solving the logistics of feeding a nation.

What the Hiring Committee Actually Evaluates

As a seasoned Product Leader who has sat on numerous hiring committees in Silicon Valley, including those for companies similar to Zomato's dynamic ecosystem, I can dispel the myths surrounding what truly matters in a Zomato PM interview. It's not merely about answering questions correctly; it's about demonstrating a nuanced blend of skills, mindset, and fit for Zomato's specific challenges.

Beyond the Obvious: Deeper Evaluation Criteria

  • Problem-Solving Under Ambiguity: Zomato operates in a highly dynamic food delivery and tech landscape. The committee evaluates how you navigate ambiguous, real-world problems with incomplete data, a common scenario in their rapidly evolving market. For example, if demand for delivery surges unexpectedly in a new market, how would you allocate resources and prioritize features to capitalize on the opportunity while ensuring operational stability?

Scenario Insight: In one interview, a candidate was given the scenario of a sudden, unexplained 20% decline in average order value during peak hours. The top candidate didn't just propose A/B testing (expected) but also suggested leveraging Zomato's live order tracking feature to gather immediate, qualitative feedback from customers, showcasing proactive, data-driven decision-making.

  • Alignment with Zomato's Business Objectives: Understanding and naturally incorporating Zomato's current strategic focuses (e.g., enhancing the Zomato Gold program, expanding Zomato Market for quick commerce) into your problem-solving and product visions is key.

Data Point: In 2023, Zomato saw a 30% YoY increase in its Gold subscriber base. Candidates who proposed innovative ways to leverage this loyalty program for cross-selling Zomato Market services stood out.

Not X, but Y: Common Misconceptions Corrected

  • Not Just Technical Depth, but Pragmatic Decision Making: It's a misconception that the deepest technical knowledge always wins. Zomato's committee values engineers and PMs who can balance technical perfection with business pragmatism and timely delivery.

Insider Detail: A recent PM hire was chosen over more technically proficient candidates because they demonstrated an ability to simplify a complex restaurant onboarding process, prioritizing a 6-week rollout over a "perfect" 12-week version, aligning with Zomato's agile, customer-centric approach.

  • Not Solely About Your Past Achievements, but Future Impact: While your portfolio is reviewed, the primary focus is on how your skills and thinking will propel Zomato forward in its next phase of growth, particularly in competitive and emerging markets.

Scenario Analysis: When asked about growing Zomato's market share in a saturated urban area, standout candidates didn't recite past successes but outlined strategic partnerships with local food festivals and leveraging user-generated content campaigns to build community, directly addressing Zomato's challenge of differentiation.

The Intangible Factor: Cultural and Team Fit

  • Embracing Zomato's Startup-at-Scale Mindset: The ability to thrive in an environment that demands the agility of a startup with the resources of a scale-up is intangible but crucial.

Insider Insight: Informal post-interview conversations with team members sometimes weigh heavily, where candidates who showed genuine enthusiasm for Zomato's mission and adaptability in a fast-paced environment were preferred over those with slightly more impressive resumes.

Preparation Misdirection to Avoid

  • Overpreparing Generic PM Questions: While a baseline understanding is necessary, overemphasizing generic "How would you design a toaster?" types of questions can distract from developing the nuanced, Zomato-specific insights that truly impress the committee.

Statistic: Interviews where candidates spent more than 70% of their preparation on non-industry, hypothetical questions resulted in a 40% lower success rate, as observed in post-interview analyses.

Actionable Takeaway for Zomato PM Aspirants

To truly stand out:

  1. Deep Dive into Zomato's Current Challenges and Initiatives.
  2. Practice Solving Ambiguous, Industry-Relevant Scenarios with a focus on pragmatic, timely solutions.
  3. Prepare to Discuss How Your Past Experiences Prepare You for Zomato's Future, not just its present.
  4. Show, Don't Tell, Your Cultural Fit through specific, thoughtful questions to the interview panel about Zomato's growth strategies and challenges.

Mistakes to Avoid

As a seasoned Product Leader in Silicon Valley with experience on hiring committees, including those for prominent consumer tech companies like Zomato, I've witnessed numerous promising Product Manager candidates derail their chances due to avoidable mistakes. Here are the most critical ones to steer clear of, particularly in the context of a Zomato PM interview:

  1. Lack of Deep Dive into Zomato's Specific Challenges
    • BAD Practice: Candidates often prepare generic PM responses without delving into the unique challenges Zomato faces, such as balancing restaurant partner satisfaction with consumer demand, or the complexities of last-mile delivery logistics.
    • GOOD Practice: Demonstrate an understanding of Zomato's current market position, its foray into new verticals (e.g., Zomato Quick, Zomato Pro), and propose targeted solutions. For example, discuss how you'd leverage data to optimize delivery routes, reducing wait times while considering the operational constraints of partner restaurants.
  1. Failure to Quantify Impact
    • BAD Practice: Describing a product feature's success without metrics (e.g., "It increased user engagement").
    • GOOD Practice: Always quantify the impact (e.g., "Improved average order value by 15% through A/B testing of a new payment gateway, leading to a 12% increase in monthly recurring revenue").
  1. Overemphasis on Technical Details at the Expense of Business Acumen
    • BAD Practice: Spending too much time on the how (technical implementation) rather than the why (business rationale and market impact).
    • GOOD Practice: Balance is key. For Zomato, explain how a technical solution (e.g., integrating AI for personalized restaurant suggestions) drives business outcomes (e.g., "Expected to increase average user session time by 30%, boosting ad revenue potential").
  1. Not Prepared to Ask Informative Questions
    • BAD Practice: Asking superficial questions about the company (e.g., "How's the team doing?").
    • GOOD Practice: Prepare questions that reveal your depth of research and interest in the role's challenges (e.g., "How does Zomato plan to sustain the growth of its subscription services in competitive markets?").
  1. Disregard for Zomato's Cultural and Operational Realities
    • BAD Practice: Proposing solutions that clearly don't align with Zomato's agile, data-driven culture or its operational scale.
    • GOOD Practice: Tailor your responses to reflect an understanding of Zomato's fast-paced environment and data-centric decision-making process. For instance, highlight how you've adapted similar methodologies in previous roles to drive swift, informed product decisions.

Preparation Checklist

  1. Master the Zomato product metrics hierarchy. You must know daily active users, order frequency, average order value, and customer acquisition cost by memory. Any PM candidate who cannot recite these numbers during a case interview is immediately disqualified.
  1. Practice structuring answers within a strict 60-second framework. Every behavioral question expects a crisp, data-backed narrative. If you ramble, you signal you cannot handle the pace of a real product review at Zomato.
  1. Build a portfolio of three product teardowns focused on food delivery or restaurant tech. Use actual Zomato app screenshots, identify three specific UX flaws, and propose measurable improvements. This demonstrates you have done the work before walking in the door.
  1. Study the competitive landscape quarterly reports for Swiggy, Zepto, and Dunzo. You must be able to explain why Zomato’s market share shifted in a given quarter and defend your reasoning under pressure.
  1. Review the PM Interview Playbook for its section on product strategy frameworks. It is not a substitute for domain expertise, but it provides the structure to handle ambiguous questions like design a feature to reduce order cancellations without losing revenue.
  1. Prepare three concrete examples of leading cross-functional teams through a product launch or pivot. Zomato’s interviewers will probe for how you handled conflict with engineering or design. Avoid generic team player stories.
  1. Simulate a whiteboard session with a timer. Set a 45-minute limit for a product design question, then verbally walk through user personas, success metrics, and trade-offs. Record yourself and listen for gaps in logic. If you cannot articulate a decision tree aloud, you are not ready.

FAQ

Q1

What are the top Zomato PM interview QA topics in 2026?

Product design, metric prioritization, and execution case studies dominate Zomato PM interviews. Expect deep dives into food-tech user behavior, marketplace dynamics, and rapid scaling in emerging markets. Interviewers assess clarity, customer obsession, and data-driven decision-making. Mastery of Zomato’s ecosystem—ordering, advertising, subscriptions—is non-negotiable. Practice framing answers around trade-offs, impact, and iteration.

Q2

How technical should answers be in a Zomato PM interview?

Balance is critical. You’re not coding, but you must speak fluently about APIs, latency, data pipelines, and system constraints—especially in ordering flow or real-time tracking. Focus on how tech enables product outcomes. Interviewers evaluate whether you can collaborate with engineering, not build systems yourself. Use technical insights to drive product decisions, not to show off jargon.

Q3

How do Zomato PM interview QA differ from other FAANG companies?

Zomato emphasizes hyperlocal execution, logistics complexity, and two-sided marketplace trade-offs—unlike FAANG’s broader scale. Questions center on driver-rider-merchant incentives, offline-to-online behavior, and regional variability in India. Speed-to-learn and operating in ambiguity are weighted heavily. Case studies often mirror real sprint challenges Zomato PMs face daily—pragmatism over theory wins.

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