Viral Coefficient
The degree of exponential growth from referrals, derived from referrals sent per user, the conversion rate of those referrals and the total number of current users.
This one is not written up yet
The definition above is the short version. A full explanation — how it works, a worked example and the exam traps — is still being written. In the meantime the chapter below covers it in context.
Written up from the same chapter
- Churn RateThe percentage of customers who discontinue using a product or service over a given period — the metric that decides whether acquired customers are an asset or a leaking bucket.
- CLTV/CAC ratioCustomer Lifetime Value divided by Customer Acquisition Cost — how many rupees of customer revenue a start-up buys for every rupee it spends winning that customer.
- Cost approachValuing a business from its assets less its liabilities — by book value, by what it would cost to replace, or by what it would fetch if broken up and sold.
- Customer Lifetime ValueThe total revenue a start-up earns from one customer across the whole relationship — average purchase value multiplied by the average number of purchases that customer makes.
- Deal CompsRelative valuation using earnings based multiples — chiefly EV/EBITDA and EV/Sales — which the workbook also calls Transaction Comparables.
- Discounted Cash FlowA valuation method that estimates the cash a business will generate in future years and converts each year back to what it is worth today.
Where this is taught
- Series XIX-D · Chapter 11: Valuationintroduced here
- Series XIX-C · Chapter 14: Valuationintroduced here
Related terms
- Customer Acquisition CostThe average cost of winning one new customer — read against customer lifetime value, it says whether a start-up is buying revenue at a profit or at a loss.
- Churn RateThe percentage of customers who discontinue using a product or service over a given period — the metric that decides whether acquired customers are an asset or a leaking bucket.
- Net Promoter ScoreA customer-loyalty score from a single question — how likely are you to recommend this — computed as the percentage of promoters minus the percentage of detractors.
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