Business Metrics and Unit Economics Questions

Evaluate a candidates ability to analyze the financial drivers and per customer economics that determine business sustainability and growth. Core concepts include revenue streams and pricing, gross margin, contribution margin, operating margin, customer acquisition cost, lifetime value per customer, lifetime value to customer acquisition cost ratio, payback period, average revenue per user, churn and retention rates, and metrics for subscription or recurring revenue models such as annual recurring revenue, monthly recurring revenue, expansion revenue, and contraction effects. Candidates should be able to perform back of the envelope calculations and sensitivity analysis, interpret trade offs between growth and profitability, link marketing product and channel activities to financial outcomes, explain how metrics vary by customer segment or acquisition channel, and make strategic recommendations such as pricing adjustments, segmentation strategies, acquisition channel shifts, or investment versus efficiency decisions. Interviewers may request simple calculations, scenario analysis, and prioritized actions grounded in metric changes.

MediumTechnical

60 practiced

Write down a short plan (3–5 bullet points) for an analysis that attributes changes in LTV by product SKU when customers frequently hold multiple SKUs. What data joins, metrics, and attribution rules would you use to apportion LTV contributions to individual SKUs?

MediumTechnical

57 practiced

A product team proposes subsidizing acquisition by setting CAC target to 10 USD to hit rapid growth. Your current LTV per acquired user is 25 USD and current payback is 6 months. Using simple arithmetic, explain scenarios under which subsidizing acquisition is sustainable and when it is not. Discuss three financial or operational constraints that could make such a strategy risky.

Sample Answer

Short answer: Subsidizing to CAC = $10 can be sustainable if unit economics remain positive (LTV > CAC) and payback remains acceptable given cash/runway and operational capacity. With LTV = $25, LTV/CAC = 2.5 — superficially healthy. But sustainability depends on how payback and LTV change when scaling.

Arithmetic and scenarios- Key metrics: LTV = $25, target CAC = $10 → contribution per user = LTV − CAC = $15 lifetime gross profit. LTV:CAC = 2.5.- Payback scaling: if current payback is 6 months at your current CAC (call it CAC0), payback scales roughly linearly with CAC. New payback = 6 * (10 / CAC0). Example scenarios: - Example A (likely sustainable): CAC0 = $15 → new payback = 6 * (10/15) = 4 months. You recover CAC faster, keep $15 lifetime margin per user, growth is affordable if cash runway supports 4-month payback. - Example B (borderline): CAC0 = $10 already → payback remains 6 months, no change; growth only sustainable if operations scale and marginal LTV stays $25. - Example C (risky): scaling acquisition drives worse cohorts so effective LTV falls (e.g., to $9) → LTV < CAC → negative unit economics; irredeemable loss per user.

Three constraints that make subsidizing risky1. Cash/runway and payback tolerance: Short runway or requirement for very quick payback (e.g., <3 months) can make 4–6 month payback unaffordable even if LTV > CAC. Growth needs working capital to fund upfront CAC.2. Cohort quality & LTV leakage: Scaling through cheaper channels often brings lower-retention users. If churn increases or ARPU drops, LTV can fall below CAC. You must measure cohort-level LTV, not aggregate.3. Operational capacity and marginal costs: Increased volume can raise support, fulfillment, fraud, or infrastructure costs, reducing effective margin. Also auction dynamics can inflate CAC as you scale, eroding the $10 target.

What to measure before deciding- Cohort LTV by channel and the sensitivity of LTV to scale- Payback at channel and campaign level- Incremental operational cost per new user- Cash runway and required payback threshold

Conclusion: Numerically a $10 CAC with $25 LTV looks attractive (LTV/CAC=2.5). It’s sustainable only if payback stays acceptable, LTV is stable across scaled cohorts, and you have the cash and operational capacity to absorb upfront costs. Validate with cohort tests and unit-economics projections before full-scale subsidization.

MediumTechnical

51 practiced

A product with ARPU 15 USD and monthly churn 8% wants to raise price to 18 USD. You expect churn to increase by 1 percentage point and conversion rate for new trials to fall by 5%. Using a simple unit-economics model, calculate the new LTV and discuss whether a price increase could still be beneficial. Show your math.

Sample Answer

Approach: use a simple monthly unit-economics LTV ≈ ARPU / monthly churn (steady-state expected revenue per user). Then factor conversion impact on CAC separately.

Baseline:- ARPU = $15- monthly churn = 8% = 0.08LTV_baseline = 15 / 0.08 = $187.50

After price increase:- ARPU_new = $18- churn increases by 1 ppt → churn_new = 9% = 0.09LTV_new = 18 / 0.09 = $200.00

Percent change in LTV:- (200 − 187.5) / 187.5 = 12.5 / 187.5 = 0.0667 → ≈ +6.67%

Impact of conversion drop on acquisition economics:- New-trial conversion falls by 5% (relative). If original conversion = C, new = 0.95C.- CAC is cost per paid user = CAC_trial / conversion. Holding trial acquisition cost constant, CAC_per_paid_user increases by factor 1 / 0.95 ≈ 1.0526 → ≈ +5.26%.

Net effect on LTV/CAC:- LTV increases ≈ +6.67%- CAC (per paid user) increases ≈ +5.26%- So LTV/CAC ratio improves slightly (roughly +1.3 ppt), assuming no other changes.

Qualitative caveats and further considerations:- This simple model assumes churn and ARPU uniformly apply across cohorts and months; real life has retention curve nuances and ARPU may vary by plan/add-ons.- Conversion drop may also reduce top-of-funnel volume, harming growth even if unit economics improve.- Higher price could change mix (fewer low-value users), affecting average usage, support costs, or churn beyond the +1ppt assumed.- Customer acquisition costs may rise if marketing must work harder to acquire trials at the higher price.

Recommendation:- The simple math shows LTV rises to $200 and unit economics modestly improve, so a price increase can be beneficial if CAC and growth objectives tolerate a ~5% conversion drop and potential lower volume.- Run a controlled A/B test (country or cohort split) to measure actual changes in conversion, churn, ARPU, CAC and compute cohort LTV and payback period before full rollout.- Monitor leading indicators (trial starts, conversion rate, churn by cohort week 1/4/12) and update CAC assumptions; model downside scenarios (larger conversion or churn impacts) to ensure payback remains acceptable.

EasyTechnical

58 practiced

Marketing spent 150,000 USD in a quarter and acquired 1,200 new customers during that quarter. Calculate CAC (customer acquisition cost). Then describe two ways you would adjust the CAC calculation if 1) acquisition has a long funnel (takes multiple campaigns) and 2) there are significant offline acquisition channels.

HardTechnical

57 practiced

A B2B SaaS firm has LTV:CAC target of 3.0. You discover one channel has LTV:CAC of 1.2 but is scaling quickly and responsible for 50% of new signups. Draft a one-page recommendation: should the company pause, optimize, or scale the channel? Include two analyses you would run immediately to reduce uncertainty and one short-term operational change.

Sample Answer

Recommendation: Optimize and cautiously scale the channel—not pause, not full-scale—while running two immediate analyses to reduce risk and implementing one short-term operational control.

Rationale:- Channel drives 50% of new signups; cutting it risks growth and revenue momentum.- Current LTV:CAC = 1.2 (< target 3.0) indicates unprofitable customer economics today, so unguarded scale will destroy value.- We should treat this as a high-priority optimization + controlled ramp: preserve acquisition volume while improving unit economics and measuring impact before further scale.

Two analyses to run immediately:1) Cohort LTV and CAC decomposition (SQL + BI): compute LTV (net margin per customer) and full CAC by cohort (by acquisition week/source) over 12–24 months. Break LTV into ARR, churn, expansion, gross margin, support costs. Purpose: identify whether poor LTV is universal or concentrated in specific cohorts, product tiers, geos, or campaign creatives.2) Incremental value and attribution test (causal analysis): run uplift modeling / matched cohort analysis and, if possible, randomized holdout (5–10% holdout) to estimate incremental MRR and downstream retention attributable to the channel versus organic. Purpose: measure true incremental ROI vs. cannibalized or low-value signups.

Short-term operational change:Implement an acquisition gating & experiment: route 100% of channel traffic through optimized landing/qualification flows and split test (A/B) two treatments—(A) higher qualification (pricing transparency, product fit quiz, gated trials) and (B) value-centric onboarding plus nudges for higher-tier signups. Simultaneously impose a temporary spend cap with weekly review: allow holdout to measure uplift, pause low-performing campaigns, and reallocate budget to variants that improve LTV:CAC above 2.0 within 8–12 weeks.

Success metrics and exit criteria:- Primary: Cohort LTV:CAC moves toward ≥2.5 within 3 months and ≥3.0 within 6 months (or clear upward trajectory with statistical confidence).- Secondary: Higher-maturity KPIs: 6- & 12-month net revenue retention, CAC payback period <12 months.If analyses show persistently low incremental LTV or inability to improve economics, then progressively phase down spend and reallocate to higher-ROI channels.

As data analyst I will owner the cohort and uplift analyses, build dashboards for weekly reviews, and partner with growth/product to implement gating tests and qualify progress against the metrics above.

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