Video summary

Setting KPIs and Goals | Startup School

Main summary

Key takeaways

Business

Goal of the talk

Help early-stage founders set KPIs and use them for prioritization to reach product-market fit faster—avoiding “busy work” and vanity metrics that don’t move the business.

Core definitions and why they matter

  • KPI (Key Performance Indicator): Metrics you track internally/externally to determine if what you’re doing is working.
  • Prioritization: Ordering work by impact—given finite time, focus on the few items that move your top KPIs toward product-market fit.
  • Key warning: Don’t optimize for vanity metrics (metrics that feel good / are brag-worthy but don’t drive revenue or growth).

Framework: KPI → Bottleneck → Task prioritization (execution loop)

  1. Identify your top KPI(s)
    • Post-launch: Revenue growth is usually the primary KPI.
    • Pre-launch: Use short-term proxies like:
      • # of user conversations
      • # of conversations until launch
  2. Set a KPI goal for the week
    • Example: “10 more paying customers by next week.”
    • Weekly goals create urgency because early growth compounds.
    • Example playbook (YC founders): weekly KPI goals were made highly visible (e.g., Airbnb founders used a bathroom mirror).
  3. Find the biggest bottleneck blocking that KPI
    • Example: Super Daily (India grocery subscription; sold to Swiggy in 2018)
      • After launching V1, growth was bottlenecked by conversion → churn of high-intent users.
      • Root cause: users wanted a specific milk brand that wasn’t carried.
      • Action: onboarded the milk brand.
      • Result: +50% increase in conversion rate (by fixing the highest-impact drop-off).
  4. Rank tasks and test
    • Process:
      • Write ideas
      • Rank by probability of success
      • Sub-rank by complexity/time
      • Pick a couple to try
    • If the KPI isn’t moving: ask “why” multiple times until you find the real cause.
    • Operationalize learning:
      • Run weekly retros: Did you do the tasks you planned? If not, break them down, reduce context switching, and improve sprint execution.
      • If experiments fail: don’t repeat the same thing—fail fast and switch.
      • If growth isn’t happening: talk to users fast to recycle toward better ideas.

“Do” vs “Don’t” list for early-stage task selection

Should be on the list (usually):

  • Talk to users and iterate based on feedback (directly supports revenue growth)
  • Build/iterate on what users actually need

Should generally NOT be primary focus (examples of “fake progress”):

  • Passive fundraising / coffees / meetings without active fundraising
  • Conference attendance (except a few targeted industries)
  • Arbitrary technical milestones (e.g., launching an Android app) unless users say it’s a burning pain
  • Perfectionism / over-optimizing features users aren’t using
  • Paperwork/administrative optimization (incorporation/equity structure) beyond standard compliance
  • “Cool hard features” that haven’t been validated by user needs

Mental traps to avoid (execution risks)

  • Low-leverage busywork: check-box tasks that don’t move product-market fit
  • Self-deception about what’s working: mistaking slow growth for true PMF
  • Perfectionism/indecision: slowing down because decisions feel high-stakes—make “pretty good” decisions quickly, then iterate
  • Downside protection over upside exploration: too much fixing small problems vs chasing upside via creative risk-taking
  • Chipping away at small problems while a large existential issue is present
    • Example: 150 users requesting a small feature while churn/signups are failing

Choosing the right KPIs: primary vs secondary

Primary KPI (most startups)

  • Usually Revenue growth
  • Exceptions:
    • Marketplace: may use signups or GMV as primary
    • Early Enterprise with long cycles: may use letters of intent (LoIs)

Secondary KPIs (keep small: ~3–5)

  • Purpose: avoid “cheating” the primary KPI and provide early signals.
  • Examples:
    • Retention / churn
    • Unit economics (are you making money per user?)
    • CAC / payback period (especially early; often more reliable than complex LTV)

Vanity metrics (when they creep in)

  • If a metric isn’t directly on the path to revenue growth—or isn’t the biggest bottleneck—it’s likely vanity. Cut it.

Growth targets / KPI goal setting (metrics & timelines)

  • YC-associated reference:
    • 5–7% week-over-week growth = good
    • ~10% week-over-week growth = exceptional
  • Targets should be compounded weekly, especially early.
  • Growth rate factors:
    • Latent demand (can boost early growth, but may be harder later)
    • Sales cycle length (Enterprise may require different process metrics)
    • Organic vs paid acquisition:
      • Prefer organic early
      • Run paid acquisition tests later once payback period is understood

Retention vs acquisition (how to balance)

  • You must do both, but first ensure churn isn’t destroying payback.
  • Focus on:
    • Bringing new users into a product that can sustain them long enough to pay back CAC
    • Ensuring users can share the product (word-of-mouth)
  • Case example (Super Daily metric change):
    • Switched from tracking signups (too gameable via promos) to tracking customers who placed 5+ orders
    • Why: a leading indicator of long-term revenue users; better aligned with top-line goals.

Two KPI target-setting approaches (playbooks)

  1. Top-down goals
    • Start from a future milestone, then work backward to weekly growth needs
    • Example: $5,000 MRR by end of Startup School → convert into weekly growth required
  2. Bottoms-up goals
    • Determine what’s realistic next week given current constraints
    • Thought experiment: “What could we do with unlimited funding/resources?” then adapt with limited resources
  3. Recommendation: Use both periodically to avoid “underwhelming but consistent growth” (the “no man’s land” risk).

Non-revenue KPI guidance (what to use now vs later)

  • CAC → LTV ratios
    • Mostly a concern post–product-market fit when scaling reliably
    • Early-stage guidance: focus on payback period
      • Aim for ~0 CAC spend so customers are profitable on day one
  • Free signups / DAU
    • Paying users behave differently; free feedback may mislead
    • Exception: marketplaces/network effects where volume is required for utility (e.g., Uber—drivers needed for rider experience)
  • Exceptions where revenue is hard to measure early
    • Hardware, biotech, Enterprise long sales cycles:
      • Use LoIs, contracts, or select process/technical indicators only if they truly predict growth—audit frequently.

Concrete example: Scribd (timing of charging)

  • Scribd grew ~4 years with a free product, afraid of losing users.
  • After switching to charging:
    • Lost >90% of customers but revenue grew dramatically (“Infinity percent” in subtitles).
  • Takeaway: charging later can delay learning about paid user needs; revenue metrics can be necessary to understand real product value.

Actionable “homework” / requested founder outputs

  • Write down:
    • Your primary and secondary KPIs
    • Ambitious targets
  • Then:
    • Audit your task list for the week
    • Ensure tasks are laser-focused on moving those KPI targets

Presenter / sources

  • Presenter: Divya (YC visiting group partner; two-time YC founder)
  • Named external references/examples:
    • Y Combinator (YC)
    • Paul Graham (growth-rate guidance; “growth” essay)
    • Airbnb (weekly KPI mirror anecdote; growth-rate context)
    • DoorDash and Rickshaw (order volume comparison; Rickshaw acquired by DoorDash)
    • Super Daily (India grocery subscription case)
    • Swiggy (referenced via acquisition)
    • Scribd (charging-timing case)
    • Uber (network effects exception)

Original video