Metrics that matter
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1) The document discusses key metrics that matter for startups and businesses, including actionable metrics, customer acquisition cost (CAC), lifetime value (LTV), and cohort analysis. 2) It defines CAC as the cost of acquiring a new customer divided by the number of customers acquired, and notes mistakes like failing to include all acquisition costs. 3) LTV is defined as the predicted net profit from the future relationship with a customer. 4) Cohort analysis breaks users into groups based on acquisition date to analyze engagement over time. This provides insight into how the business and product are evolving.
Metrics that matter
- 2. #Innovation Consultant @Talent Garden # Start-ups and Growth Hacking # Founder @Skillando Digital Volunteering Filippo Scorza
- 3. 🦶 My journey Engineering Design Startup Amyko Startup Whataform Digital Volunteer Skillando Faculty Talent Garden Corporate Innovation Molti side projects - Blogging @filipposcorza.com
- 4. Vanitymetric? Nothanks! 💎 Metrics that matter
- 5. Actionablemetric! 💎 Metrics that matter
- 9. 💎 CAC Marketing investment: 100$ Customers acquired: 100 Customers CAC: 1 $/customer
- 10. 💎 CAC commons’ mistakes •Consider the cost per lead and not cost per acquisition •Failing to include all the costs incurred in user acquisition such as referral fees, credits, or discounts
- 11. 💎 CAC valuation •Great Business = CAC Payback < 6 months •Nice Business = CAC Payback equal to 1 year •Low Business = CAC Payback > 1 Year •Unstable business = CAC Payback never reached
- 13. LTV is a prediction of the net profit attributed to the entire future relationship with a customer (Avg Monthly Revenue per Customer * Contribution Margin per Customer) ÷ Monthly Churn Rate 💎 LTV
- 14. 💎 LTV Monthly Customer Revenue: 100$ Customer Gross Margin: 25% margin Customer Churn Rate: 5% LTV: 500$
- 15. 💎 CAC vs LTV •Instable businesses: CAC > LTV •Nice Business: LTV / CAC > 3x •Good Business: LTV/CAC >5x •Great Business: LTV/CAC >7x
- 17. Is a subset of behavioral analytics that takes the data from a given data set (e.g. an e- commerce platform, web application, or online game) and rather than looking at all users as one unit, it breaks them into related groups for analysis. 💎 Cohort
- 18. A good cohort analysis helps reveal how users engage with the product over time 💎 Cohort
- 19. Investors especially appreciate this because it gives a clear picture of the evolution of engagement, repetition, product, business 💎 Cohort
- 20. • Pick the right set of metrics rather than a vanity metric (like app downloads) • Pick the right period for a cohort — this will be typically be a day, a week, or a month depending on the business (shorter time periods typically make sense for younger businesses, and longer ones for more mature businesses) • Period 1 (day, week, or month) — 100% of install base takes some action that is a leading indicator for revenue, such as buying a product, listing a product, sharing a photo, etc. • Period 2 — calculate the % of install base that is still engaging in that action a week or month later • Repeat the analysis for every subsequent cohort to see how behavior has evolved over the lifetime of each cohort 💎 Cohort
- 21. What if we don’t have enough data? 💎 Cohort
- 22. If you are developing a new product or service you should start with what you have: research, interviews, competitive analysis and assumptions. 💎 Cohort
- 23. 👋 That’s all folks: hello@filipposcorza.com