Analytics for Startups

Volodarsky says analytics helps founders find problems in acquisition, engagement, or monetization and focus the team. He recommends mapping the steps from discovering a product to getting value and paying, then choosing metrics for each stage. For a Netflix example, those steps include signing up, watching videos, and upgrading after a trial.

Volodarsky demonstrates tracking events such as user signups, video plays, and subscription upgrades, with properties like invite type, video progress, and monthly recurring revenue. He recommends tracking weekly signups, retention by signup cohort, and revenue. For one cohort example, only 6.25% returned in week four; he suggests investigating why users are not finding value and improving retention.

Volodarsky recommends putting a company metrics dashboard where the team can review it regularly and connect projects to changes in the numbers. He also suggests sending advisors concise updates on performance and plans, so they can understand the business and offer relevant advice. Retention periods should match how often users naturally need the product; for travel, that may be monthly or quarterly rather than weekly.

Volodarsky describes a path from MVP to private beta, broader launch, and then scaling. For early product work, he recommends tools such as Google Analytics for website acquisition, Amplitude for feature usage, and live chat or customer Slack channels for feedback. Later, teams can add a warehouse such as BigQuery and a BI tool such as Mode to let more people explore data.

Volodarsky says early products often have usability problems that only appear when customers try them. In one Personas example, FullStory recordings showed users getting stuck on a confusing button; after the team fixed it, the metrics improved. He also describes sending new users a personal-feeling email about 43 minutes after signup, automated with Customer.io, and cautions against spending too long choosing analytics tools because teams often switch as they grow.