7 Venture Capital Interview Questions and Answers

Introduction

This question tests your deal-evaluation rigor, market sizing skills, and ability to spot venture-backable DNA—critical for an India-focused VC analyst who must triage 200+ decks a month.

How to answer

• Start with a 30-second investment thesis: problem, solution, why now.
• Quantify TAM using both top-down (RedSeer, Bain India reports) and bottom-up (price × potential customers) methods; cite local comps like Zoho or Freshworks.
• Explain unit-economics hygiene: CAC payback < 12 months, net revenue retention ≥ 110 %, gross margin ≥ 70 % for SaaS.
• Discuss founder-market fit—highlight prior exits or unique insight (e.g., ex-Zoho product head solving SME credit).
• Address competitive moat in India context—distribution partnerships (Google/Facebook), language localization, or regulatory edge (GST data).
• End with clear go/no-go and next diligence steps (customer calls, tech architecture review).

What not to say

• Relying only on global benchmarks without India-specific adjustments.
• Ignoring churn or assuming 100 % revenue retention forever.
• Saying “great team” without concrete evidence or reference checks.
• Forgetting regulatory risks (RBI data-localization, DPIIT foreign-investment caps).

Example answer

“I’d open with the thesis: ‘AI-driven vernacular CRM for India’s 60-m SME exporters.’ TAM is $1.2 B using bottom-up ₹1,200 ARPU × 5 m potential users. Founders exited a logistics SaaS to Delhivery, showing repeat entrepreneurship. Metrics: ₹80 k CAC, 8-month payback, 115 % NRR. Moat is proprietary Indic-language NLP trained on 50 m WhatsApp export chats. Key risk—language model bias; I’d diligence with ten Kolar garment exporters next week before IC.”

Introduction

VC decisions are consensus-driven; this reveals your influence, storytelling ability, and comfort disagreeing with senior investors—vital for a female analyst in India’s still male-dominated IC rooms.

How to answer

• Use STAR: Situation (deal bias), Task (your stance), Action (data + story), Result (outcome).
• Quantify the partner’s objection—e.g., “concerned that ed-tech was post-pandemic overhang.”
• Present fresh data—DAU growth post reopening, government NIPUN teacher-training tenders, or MOOC subsidies.
• Frame a narrative arc: ‘From emergency tool to everyday pedagogy.’
• State the final vote count and follow-on milestones (e.g., 3× ARR in 9 months).

What not to say

• Blaming the partner for being outdated.
• Using only qualitative arguments without numbers.
• Taking sole credit—VC is team sport.
• Choosing a trivial disagreement (font color in deck).

Example answer

“At Accel, a partner passed on a D2C ethnic-foods brand citing ‘low repeat rates.’ I scraped 2-year Amazon India reviews and found 38 % repeat phrases around festive gifting. I built a cohort chart showing 45 % month-6 repeat among NRIs, projecting ₹18 Cr incremental GMV from Diwali hampers. I presented this plus a 5-minute customer video of an Indian-American family in New Jersey. The partner flipped to champion, we led the $4 m seed, and the company hit 2.2× YoY growth last Diwali.”

Introduction

Checks strategic vision and alignment with fund DNA—important when every analyst claims ‘AI + Bharat’ but few map it to portfolio construction.

How to answer

• Open with macro drivers: UPI 700 m users, $5 tn GDP target, PLI schemes, digital public goods (OCEN, Account Aggregator).
• Predict two themes—climate-tech (green hydrogen, EV infra) and SME SaaS (GST compliance data as wedge).
• Identify gaps—Series B capital flight, deep-tech talent retention versus Silicon Valley.
• Recommend fund posture: raise opportunity fund for follow-ons, partner with IITs for IP spin-outs, set up Singapore blocker for US LPs.
• Close with measurable KPI: capture 8 % of Series A climate-tech deals by 2029.

What not to say

• Generic statements like ‘India will be the next China.’
• Ignoring global capital cycles or Fed-rate impact on DPI flows.
• Over-optimism without risk acknowledgment (regulatory flip-flop).
• Copying last year’s VC conference slide verbatim.

Example answer

“By 2029 India will add 200 m new internet users from tier-3 towns and mandate ESG reporting for top 1,000 companies. I see a $12 B climate-tech TAM driven by 500 GW renewable target. Our early Series A focus should double down on grid-storage and carbon-accounting SaaS. We can reserve 25 % of Fund IV for follow-on rights, anchor a climate syndicate with Temasek, and set up an IIT-Madras incubator to secure first look at battery-tech IP. Goal: own 10 % of climate-tech Series A rounds and deliver 4× DPI within seven years.”

Introduction

This question tests your deal-sourcing eye, market analysis, and ability to articulate an investment thesis—core skills for any VC Associate expected to screen 100+ opportunities a month.

How to answer

• Pick a real, early-stage Indian or SEA startup (Seed–Series A) that is not yet a unicorn
• Open with a crisp one-sentence investment thesis (problem, solution, edge)
• Quantify market size with credible sources (IAMAI, RedSeer, Bain, etc.)
• Highlight the founding team’s unfair advantage (ex-Flipkart, IIT/ISB, domain patents, etc.)
• Show at least one traction metric (MoM growth, retention, CAC:LTV) and a pre-money valuation sanity check
• Close with the two biggest risks and how you would diligence them (tech, regulatory, GTM, follow-on capital)

What not to say

• Naming late-stage decacorns like BYJU’S or Swiggy that every fund already knows
• Generic statements like ‘huge market’ without numbers
• Ignoring valuation and suggesting you’d ‘pay any price’
• No mention of risks or exit pathways

Example answer

“I would write a ₹2 crore seed cheque in Pesto, a Gurugram-based B2B SaaS platform that turns offline restaurants into cloud kitchens. They’re growing GMV 35% MoM, CAC payback <45 days, and address India’s $40B food-delivery TAM (RedSeer 2023). Founders are ex-Zomato product and ex-Swig ops, giving them unique data on kitchen turn-times. Key risks: local FSSAI enforcement and thin margins—both testable via mystery kitchens and unit-economics cohort analysis.”

Introduction

VC is a people business; Associates must guard the fund’s criteria while maintaining relationships for future rounds or referrals.

How to answer

• Use STAR: Situation (deal type, stage, year), Task (your role in IC memo), Action (data that contradicted story), Result (decline & relationship upkeep)
• Show concrete IC thresholds you used (payback >18 mths, <20% IRR, churn >5% monthly)
• Explain how you delivered the pass—clear email, offered intros, kept them in CRM
• Share a follow-up event (they raised from XYZ, you stayed in touch, potential Series B look)

What not to say

• Bad-mouthing the founder or disclosing confidential metrics
• Saying ‘the partner over-ruled me’ without your own analysis
• Claiming you never feel emotional attachment—sounds inauthentic

Example answer

“Last year at Kalaari I sourced a D2C skincare brand whose founder was an HBS alum and compelling storyteller. My churn cohort showed 6.5% monthly, breaching our <4% threshold. I built a downside model with burn reaching zero in 11 months and presented it to the partner, recommending pass. I told the founder we’d monitor unit economics for six months; she later fixed logistics and raised from Fireside. We’re now tracking her Series A deck.”

Introduction

This situational question checks your hustle, process design, and understanding of the Indian startup ecosystem’s deal-flow channels.

How to answer

• Segment sources: accelerators (TLabs, YC India), angels (LetsVenture), co-investors (Blume, Elevation), universities (IITs, BITS), sector meet-ups, cold outbound via LinkedIn Sales Navigator
• Set KPIs: 50 intros/month, 10 first calls, 3 partners’ deep-dive, 1 term-sheet
• Propose lightweight tech: Notion CRM, Affinity auto-tag, Airtable scoring rubric
• Budget ₹10 lakh for founder events, demo-day travel, and one intern analyst
• Close with feedback loop: monthly source effectiveness report to partners, iterate channels

What not to say

• Only relying on inbound applications or banker decks
• Ignoring compliance (SEBI AIF rules on referrers)
• Suggesting spray-and-pray without qualification criteria

Example answer

“I’d run a bar-bell approach: 60% institutional partnerships and 40% outbound. Tie up with 8 accelerators for first-look rights, sponsor 2 sector hackathons, and use LinkedIn boolean search for ‘founder + B2B SaaS + <$5m raised’. Everything feeds into an Airtable scored on sector-fit, stage, and traction. Historical conversion tells me 400 qualified deals yield ~8 term-sheets, hitting our deployment goal.”

Introduction

This question tests your ability to apply a disciplined investment framework to a high-growth sector that is currently flooded with look-alike companies in China.

How to answer

• Begin with market sizing: TAM in China vs. global, CAGR, and policy tailwinds like ‘New Infrastructure’
• Explain your tech diligence approach: model architecture novelty, data moat, GPU supply chain risk, and compliance with China’s algorithm filing rules
• Detail founder assessment: prior exit track record, technical pedigree (Tsinghua, Peking, BAT alumni), and alignment with CCP tech priorities
• Describe competitive mapping: benchmark against ByteDance, SenseTime, Baichuan, and emerging open-source models
• Finish with unit-economics and exit scenarios: payback <18 mo, 3× revenue-valuation multiple discipline, and likely acquirers (Alibaba, Tencent, Huawei)

What not to say

• Generic ‘big market, great team’ without quantifying TAM or founder credentials
• Ignoring regulatory risks (algorithm filing, data export bans, US sanctions)
• Failing to mention how you would source proprietary deal flow in China’s crowded VC landscape
• Overlooking downstream Series B/C investor appetite and HK vs. STAR board exit timing

Example answer

“I’d start by sizing the vertical AI SaaS TAM for Chinese manufacturing at RMB 120 bn growing 35 % CAGR under the 14th Five-Year Plan. The startup must show a transformer-based model fine-tuned on proprietary factory data unreachable by BAT. I’d verify the founder’s PhD from Tsinghua plus two exits to Alibaba, and confirm they’ve already filed algorithms with CAC. With 150 % net-dollar retention and 12-month payback, I can underwrite a 10× MOIC if Tencent acquires at 20× ARR in 2026.”

Introduction

VC in China is fiercely competitive; this question gauges your resilience, self-reflection, and ability to upgrade your personal deal-winning toolkit.

How to answer

• Set the scene: company, round size, competing funds (Sequoia China, Qiming, Hillhouse), and why it was attractive
• Explain the exact reason you lost: speed, brand, value-add, or terms
• Detail the concrete process change you implemented (e.g., 48-hour IC, founder-friendly term-sheet, portfolio-CEO reference ring)
• Quantify the result: next 3 deals won, reduced closure time by X days
• Reflect on what you still monitor today to avoid repeat losses

What not to say

• Blaming the founder for being ‘irrational’ or the rival for ‘overpaying’
• Saying you changed nothing—indicating lack of adaptability
• Giving a generic answer without naming specific funds or metrics
• Claiming you’ve never lost a deal (signals inexperience or dishonesty)

Example answer

“We lost Series A of a Shenzhen robotics company to Legend Capital because they could syndicate with their portfolio’s supply-chain partners within 24 hours. I built a ‘value-add map’ of 50 CEOs who take my calls and now attach a signed intro letter to every term-sheet. Using this, I closed the next two robotics deals in 30 days each, cutting our average time-to-close from 70 to 38 days.”

Introduction

RMB-denominated fundraising increasingly requires SOE participation; this question tests your political savvy, structuring creativity, and ability to align commercial VC returns with state mandates.

How to answer

• Map SOE strategic priorities to fund thesis: dual circulation, import substitution, energy security
• Show how the LP stake counts toward SOE’s R&D intensity KPIs and mixed-ownership reform metrics
• Propose a separate advisory committee with veto rights on sensitive export-control technologies to address security concerns
• Offer preferred return structure: 1× liquidation preference plus 6 % coupon to protect state capital
• Provide case studies of prior SOE-backed funds (e.g., China Merchants + GLP logistics tech fund) that delivered both policy wins and 20 %+ IRR

What not to say

• Treating the SOE like a purely financial investor and ignoring policy objectives
• Promising guaranteed returns, which violates SAMR and Ministry of Finance rules
• Failing to address CIC/SAFE approval pathways for overseas portfolio exits
• Using Western ESG jargon instead of China-specific policy language

Example answer

“I’d anchor the pitch around State Grid’s 2025 smart-grid roadmap. Our fund targets SiC power semis that reduce 10 % energy loss, directly supporting their carbon KPI. We would create a 10 % side-car for State Grid’s research arm to co-develop pilots, while giving them a 1×+6 % preferred return to satisfy SASAC capital-preservation rules. This structure mirrors the 2019 CGN-Silk Road nuclear-tech fund that returned 1.8× in four years.”

Introduction

This question probes your end-to-end investment craft—deal sourcing edge, due-diligence depth, competitive positioning, and value-creation track record—critical for a Principal expected to lead rounds independently at a top-tier VC like Sequoia China or Qiming.

How to answer

• Begin with the non-obvious sourcing channel (founder network, hackathon, outbound thematic deep-dive) and why you prioritized the space.
• Explain your investment hypothesis, TAM expansion insight, and early KPIs that gave you conviction pre-benchmark.
• Detail diligence steps: customer calls, expert interviews, tech deep-dive, regulatory mapping, and competitive scoring.
• Describe how you built founder trust, structured a preemptive term sheet, and beat rival funds (name them).
• Quantify fund-level outcome: MOIC, IRR, and strategic exits; connect to personal carry contribution.

What not to say

• Centering only on luck or brand-name co-investors without personal alpha generation.
• Vague market sizing or ignoring China-specific regulatory risks.
• Claiming sole credit if you were a supporting associate—fund partners will reference-check.
• Skipping post-investment value add; Principals must show portfolio operator muscle.

Example answer

“In 2019 I led our Series A in an industrial-AI chip company headquartered in Shenzhen. I mapped 200 semiconductor start-ups, then cold-emailed the founder after reading a Zhihu post. My thesis: GPU shortages from US export controls would force domestic substitution. Over six weeks I completed 38 customer calls with leading server OEMs, hired two TSMC veterans for tech diligence, and modeled a 5 nm tape-out cost path 30 % below market. We issued a pre-emptive ¥120 m term sheet at ¥400 m pre-money, beating Hillhouse by 24 h. I took a board seat, helped secure SMIC as fab partner, and guided the CFO through STAR-Market listing rules. At IPO two years later our position was valued at 18× cost, returning 1.4× the fund.”

Introduction

Principals must show intellectual honesty and risk calibration; Chinese VCs have seen high-profile implosions (tutoring, ride-hailing). This behavioral question tests discipline under FOMO pressure.

How to answer

• Set the scene: sector hype, internal excitement, and your personal time sunk.
• Identify the red flag (regulatory, unit-economics, founder integrity) with concrete data.
• Explain stakeholder management: how you socialized concerns with champions and secured a ‘no-go’ memo.
• Share post-mortem validation—did the company struggle? Highlight learning for future pattern recognition.
• Demonstrate emotional neutrality; show you can walk away without ego damage.

What not to say

• Blaming regulation after the fact without prior analysis—partners look for forward risk flags.
• Using hindsight alone; focus on reasoning available at decision date.
• Bad-mouthing rival funds that did the deal; keep it professional.
• Revealing confidential company data—shows poor judgment.

Example answer

“In late 2020 I brought a K-12 live-streaming platform at Series B. Initial metrics were stellar—20 % monthly burn-to-revenue improvement. I owned the deal and wanted it badly. During diligence I commissioned a policy scan; our legal advisor flagged draft rules requiring non-profit conversion. I built a downside model showing 70 % valuation haircut if the draft passed, presented sensitivity tables to the IC, and recommended we pass. The partnership agreed. Six months later the government issued the restriction and the competitor who led the round wrote down 90 %. The experience sharpened my regulatory scenario-planning and reinforced that downside protection trumps FOMO.”

Introduction

Tests strategic thinking, policy alignment, and portfolio construction—core for a Principal who may run a sub-sector practice within a large RMB/USD vehicle like CDH or Gaorong.

How to answer

• Define the policy scope: Ministry of Industry classifications, tax incentives, local government subsidies.
• Map value-chain gaps—advanced materials, precision optics, industrial software—citing import-dependency stats.
• Outline sourcing funnel: partnerships with Torch High-Tech Centers, SME bureaus, research institutes.
• Explain investment criteria: gross margin >40 %, global addressable niche >$2 bn, defensible IP, state-customer validation.
• Detail exit matrix: STAR Market, Beijing Stock Exchange, strategic M&A with SOEs; show projected DPI timeline.

What not to say

• Ignoring geopolitical export-control risks (e.g., US Entity List) that can cap scale.
• Treating ‘专精特新’ as a monolith; granularity on sub-sectors is expected.
• Over-relying on government guarantees; VCs must show commercial discipline.
• Forgetting ESG angles—environmental compliance is increasingly enforced.

Example answer

“I would anchor the thesis on import substitution of 35 critical sub-sectors highlighted in the 14th Five-Year Plan, prioritizing high-precision reduction gears and specialty fluoropolymers. My team will co-host demo-days with 15 provincial SME bureaus, targeting 200 ‘小巨人’ enterprises annually. Screening filters: 30 % revenue CAGR, >10 % R&D intensity, and at least two Tier-1 multinational customers proving global competitiveness. We will write $15–30 m tickets for 15–20 % stakes, reserve 50 % for follow-ons, and target IPO on STAR within 4 years where median PE is 45× vs 12× for A-share industrials. Stress-testing includes Entity-List probability model and dual-use export simulations. My model portfolio delivers 3.5× TVPI and 28 % gross IRR under conservative exit multiples.”

Introduction

This reveals your conviction-driven investing style, ability to synthesize non-obvious insights, and track record of influencing senior ICs and the IC committee—core to a VP’s value in venture.

How to answer

• Begin with the market ‘hair’ that scared others (e.g., pre-revenue, crowded space, non-obvious founder profile)
• Explain your proprietary data or customer calls that reframed the risk/reward
• Detail how you built a bottoms-up TAM model and stress-tested unit economics
• Describe the exact objections from partners and the evidence package you assembled to overturn them
• Close with hard metrics: MOIC, IRR, follow-on dynamics, and strategic exit interest to date

What not to say

• ‘I just really liked the founder’ without quantified conviction drivers
• Blaming the partnership for being ‘too conservative’
• Claiming a unicorn outcome that is still illiquid and unverified
• Ignoring downstream ownership dilution or follow-on reserves in your return math

Example answer

“At Bain Capital Ventures, the majority of the team passed on a seed-stage vertical-SaaS company serving nail salons because TAM appeared tiny. I mapped 17 analogous SMB verticals, proved 4参考 customer cohorts with >120% net dollar retention, and built a 50-city salon-density model showing a $4B TAM. I pre-wired two co-investors to validate pricing power and presented a reserves strategy for the Series A. The partnership approved a $3M seed at $12M pre; two years later it’s tracking $20M ARR with Sequoia leading the B at $200M pre, giving us a 12x partial markup and 70%+ ownership on a blended basis.”

Introduction

This situational case tests capital strategy, portfolio construction, and risk-adjusted return thinking expected of a VP who will sit on the investment committee and mentor associates.

How to answer

• State a clear return target (e.g., 3x net DPI by year 10) and required gross IRR
• Break down allocation: % in pre-seed/seed vs. A/B vs. growth, with rationale tied to fund size
• Choose a check-size ladder ($1–3M seeds, $5–8M As, $10–15M growth) and ownership targets (10–15% blended)
• Show reserve math: 60–65% for follow-ons to defend pro-rata in winners
• Include sensitivity analysis: what happens if 30% of seeds fail vs. one breakout drives 70% of returns

What not to say

• Equal-weighting every stage with no concentration logic
• Ignoring recycling or management fees in deployable capital
• Setting reserves below 50%—signals misunderstanding of dilution
• Failing to mention cross-fund strategy or LP expectations on pacing

Example answer

“Targeting 3.5x net, I’d allocate 25% to seeds ($0.5–2M, 12% ownership), 45% to A/B ($3–8M, 10%), 30% to growth ($10–15M, 5%). That implies ~35 core bets with 65% reserves. Monte-Carlo shows a 0.8x floor if zero unicorns, but 4.2x if two companies hit $1B+ and we defend pro-rata. Pacing: 8 investments/year for first 3 years, leaving $20M recycling buffer. This matches our LP’s expectation of early DPI from growth co-leads while seed shots-on-goal drive upside.”

Introduction

Great VPs differentiate through repeatable edge—networks, data, or operating chops. This leadership question probes self-awareness and your ability to build firm-wide capability, not just personal brand.

How to answer

• Name a concrete edge (e.g., outbound customer-discovery engine, technical due-diligence playbook, or talent network)
• Give a one-sentence metric proving the edge (e.g., 45% of portfolio CXOs came via my intro)
• Describe a lightweight system or playbook you’ve documented
• Explain how you’ll train associates (workshops, shadowing, OKRs) and measure adoption
• Close with how this scales dealflow or reduces loss ratio

What not to say

• Vague strengths like ‘hard-working’ without quantified evidence
• Keeping methodology in your head—signals poor leadership
• Over-engineering a 100-page playbook no one will read
• Ignoring culture fit or existing firm processes

Example answer

“My super-power is hyperspeed customer diligence—within 48 hours I can map a startup’s TAM by cold-calling 10 enterprise buyers and produce a 5-slide pain-killer memo. I’ve codified the outreach script, incentive structure, and scoring rubric into a two-hour workshop. At Foundry, I ran quarterly ‘Customer Sprint Days’ where each associate sourced three reference calls; within a year the team adopted the playbook, doubling our pre-deal customer data points and cutting false-positive seed investments by 25%.”

Introduction

This question tests your end-to-end investment acumen, ownership mindset, and ability to reflect and improve—critical for a Partner expected to generate DPI for LPs.

How to answer

• Use the SC (Situation-Choice) framework: market gap, your sourcing channel, diligence edge, value-add post-investment, and exit path
• Quantify gross MOIC, IRR, and cash returned to LPs; benchmark against fund size and vintage
• Highlight proprietary angles: founder relationship, sector thesis built before others, or unique deal structure
• Own mistakes candidly: e.g., dilution timing, board seat leverage, or follow-on sizing
• Close with forward-looking tweaks: sharper follow-on reserves, earlier secondary partial exits, or ESG value-creation levers

What not to say

Example answer

“At Sequoia India Fund VI I sourced a seed-stage SaaS startup through a founder I had backed twice before. We led a $4 m round at a $16 m post-money, took 20 %, and I took a board seat. Over five years we helped them expand to SEA, introduced 40 % of their Series B investors, and implemented a key hire for US GTM. We exited via a $450 m strategic sale to Salesforce, returning 11× cash and $88 m to the fund. Today I would reserve more pro-rata for Series C to avoid 18 % dilution and negotiate a 1× non-participating liquidation preference to protect downside in a tighter exit market.”

Introduction

This situational query assesses strategic capital deployment, risk calibration, and LP communication under volatile macro conditions specific to Indian venture markets.

How to answer

• Segment the corpus: reserve ratio, follow-on versus first-check, and stage mix (pre-seed/seed/Series A)
• Incorporate sector tailwinds: DPIIT’s AI mission, ONDC, EV infra, and SaaS to US
• Address valuation discipline: target entry multiples, partial secondary purchases, and milestone-based tranches
• Show LP alignment: DPI targets, distribution pace, and recycling limits under SEBI AIF regulations
• Include downside protection: pro-rata rights, board control thresholds, and early warning KPIs

What not to say

• Planning to deploy >70 % in first 18 months without reserves
• Ignoring SEBI’s 25 % recycling cap or 1-year deployment extension rules
• Dismarking capital for non-VC assets just to reduce J-curve
• Stating ‘we will wait for better valuations’ without a deployment trigger plan

Example answer

“I would deploy 45 % in first-check seed/Series A over 24 months, targeting 25 core investments with average cheque of $4.5 m for 12-15 % ownership. A 40 % reserve fund supports follow-ons through Series C, protecting against dilution. The remaining 15 % is a opportunistic pool for secondaries at 30-40 % discounts. Sector focus: 40 % enterprise SaaS, 25 % fintech infra, 20 % climate tech, 15 % digital health. Entry EV/revenue multiple ceiling of 8× for seed and 15× for Series A. Board seat on 60 % of portfolio, and quarterly DPI reporting to LPs. Recycling capped at 20 % to meet 3× gross target by year seven.”

Introduction

This leadership question evaluates your governance judgement, ability to balance fiduciary duty with founder relations, and skill in steering tough recap decisions—key for a Partner accountable to both LPs and entrepreneurs.

How to answer

• Present a 13-week cash-flow model and unit-economics deep-dive to frame urgency
• Lay out strategic options: inside round, structured equity, venture debt, or orderly M&A
• Quantify dilution impact on existing investors and ESOP refresh needs
• Explain how you would negotiate recap terms—liquidation preference reset, anti-dilution, and board control
• Communicate transparently with co-investors and LPs, documenting decision rationale for audit

What not to say

• Immediately pushing for a pay-to-play without exploring softer alternatives
• Promising bridge capital without fund-reserve confirmation
• Ignoring employee morale or customer perception during recap
• Making solo decisions without involving the full partnership

Example answer

“I convened an emergency board, shared a revised cash model showing 8.3 months runway at current burn. We benchmarked CAC/LTV and realised payback had doubled to 22 months. I guided the founders to cut burn 30 % by rightsizing GTM spend, extending runway to 12 months. Simultaneously, I negotiated a $6 m insider Series B-1 at a flat ₹640 cr pre-money but with 1.5× non-participating preference and 15 % option-pool expansion to keep talent. Existing Series A investors who joined pro-rata maintained anti-dilution; non-participants converted to common. I secured board majority for governance and monthly KPI reviews. Communication to LPs highlighted downside protection and path to profitability by Q4 FY25, aligning everyone to a new value-creation plan.”

Introduction

This question assesses your crisis-management skills and ability to create value under pressure—critical for a Managing Partner accountable for fund performance.

How to answer

• Use STAR format: Situation (runway, burn, market context), Task (your mandate), Action (hands-on interventions), Result (quantified survival & growth metrics)
• Specify your personal involvement: board pivots, management changes, follow-on syndication, customer introductions
• Highlight co-investor alignment and LP communication to show stakeholder management
• Close with lessons you embedded in the firm’s post-investment playbook

What not to say

Example answer

“In 2021 our Series B investment in a Madrid fintech had 4 months runway and 60 % monthly churn. As deal lead I replaced the CMO, re-negotiated 30 % of SaaS contracts to annual upfront, and arranged a €8 m bridge with two co-investors at Index Ventures. We cut burn 40 %, reached break-even in 9 months, and achieved a €120 m exit to BBVA last year, returning 4.2× to the fund.”

Introduction

This tests your end-to-end fund stewardship—capital deployment, reserves, valuation discipline, and exit timing—expected of a Managing Partner answering to institutional LPs.

How to answer

• Segment the portfolio: core positions, follow-ons, reserves for pro-rata
• State target ownership (15-20 %), entry valuations (<€20 m), and check sizes
• Model reserves: 50 % for follow-ons, 20 % for secondaries, 10 % emergency
• Define exit pathways: IPO vs trade-sale windows, minimum 5× MOIC, 25 % IRR
• Address ESG and D&I commitments demanded by European LPs

What not to say

• Relying on one mega-hit to return the fund
• Ignoring Spanish fiscal nuances or withholding tax on exits
• Underestimating follow-on dilution in competitive rounds
• Promising unrealistic timelines or IRRs unsupported by market data

Example answer

“I would deploy €120 m across 25 companies, maintaining 18 % average ownership. Reserving €60 m allows me to double-down on 8 category leaders. With historical data showing 3× DPI requires ≥2 exits above €500 m, I would seed deeptech and fintech verticals where Spain has clear advantages, map strategic acquirers like Santander, Telefónica, and Amadeus, and enforce disciplined secondaries at Series C to lock in early DPI. Monte-Carlo modelling forecasts 3.4× DPI and 26 % net IRR, exceeding LP hurdle.”

Introduction

This evaluates your leadership in advancing inclusion—an LP priority—and your ability to source non-obvious dealflow, differentiating the fund.

How to answer

• Set measurable KPIs: 30 % female-founded companies in next portfolio
• Build sourcing channels: partnerships with IESE, Conector, and Women Angels
• Offer term-sheet incentives: reduced board seats or enhanced ESOP for diverse co-founders
• Create a female-founder council for portfolio support and branding
• Report progress transparently in annual ESG letters to LPs

What not to say

• Treating diversity as charity instead of alpha generation
• Lowering investment criteria for female founders
• Ignoring pipeline-building and blaming “supply” issues
• Failing to cite successful precedents like Glovo or Cabify initiatives

Example answer

“At my previous fund I launched the ‘FoundHER’ program: we reserved 10 % of the fund for startups with female CEOs or CTOs, partnered with 14 Spanish accelerators, and hosted quarterly reverse-pitch days. Over three years we tripled female-founded investments to 27 %, and those companies showed 18 % higher revenue growth, helping us raise a successor fund 30 % faster by showcasing differentiated dealflow to European LPs.”