Glossary: Funnel Analytics
Funnel analytics shows how users or wallets move through a sequence of steps, from visiting an app to completing an action such as a deposit or swap. It highlights where they convert or drop off.
What is Funnel Analytics?
Funnel analytics follows a defined sequence of app or protocol events and reports how many distinct identities reach each step. Specify event order, identity unit, conversion window, and whether a blockchain step requires a confirmed transaction.
Funnel Analytics Explained
Funnel analytics helps you understand where people drop off before completing something.
Imagine 100 people visit a website. Then 60 create an account. Then 30 finish onboarding. Then 10 become paying users.
That step-by-step path is called a funnel because the number of people usually gets smaller at each step.
Funnel analytics shows which step is losing the most people, so teams know where the experience may be confusing, too long, or not valuable enough.
What Funnel Analytics Means For
Audience | Use Case |
|---|---|
Growth teams | Find where users drop off between awareness, signup, activation, and conversion. |
Product teams | Improve onboarding, checkout, or feature adoption flows by identifying weak steps. |
Marketing teams | Measure how campaigns turn visitors into leads, signups, customers, or active users. |
Examples
A SaaS company tracks the path from landing page visit to signup to onboarding completion to paid subscription. It finds that most users drop off during onboarding, so the team simplifies the setup process.
An e-commerce brand studies its checkout funnel and sees that many shoppers abandon their carts at the payment step. The team adds more payment options and removes unnecessary form fields.
A crypto app tracks users from wallet connection to first deposit to first transaction. It finds that many users connect a wallet but never make a deposit, showing where education or incentives may be needed.
A mobile app tracks install, account creation, profile setup, and first completed action. The team discovers that profile setup is too long and shortens it to improve activation.
The web-to-onchain journey
A common crypto product funnel is first visit → wallet connect → signature → first confirmed transaction → repeat transaction. Each step answers a different question: reach, intent, authorization, successful activation, and retained behavior. Teams can insert product-specific events, but the sequence should reflect the real user journey.
Connection and transaction states are different
A wallet connection is not a signature. A signature is not a submitted transaction. A submitted transaction is not a confirmed transaction, and a failed or reverted transaction is not a successful outcome. Track these states separately so the funnel shows the actual source of friction instead of collapsing every attempt into one step.
Related reading
Explore product analytics, Conversion Rate and Conversion Event, Time to First Transaction, Wallet Activation, and the DeFi growth funnel guide.
Crypto and DeFi example
A DeFi app can measure the steps from landing-page visit to wallet connection, transaction signature, and confirmed swap. Keeping connection, submission, and confirmation as separate events reveals whether users drop off before signing or encounter failed transactions after submission.
FAQs
What is funnel analytics used for?
Funnel analytics helps teams find where users drop off before completing an important goal.
What is an example of a funnel?
A signup funnel could be: visit website, create account, complete onboarding, become active user.
Why is it called a funnel?
It is called a funnel because fewer users usually continue at each step, creating a narrowing shape.
How is funnel analytics different from growth analytics?
Growth analytics studies overall growth. Funnel analytics focuses on step-by-step user conversion paths.
Who uses funnel analytics?
Product, growth, marketing, sales, and analytics teams use funnel analytics to improve conversion.
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