Growing
How to measure whether your Telegram bot is actually working
By the Botable team
Telegram gives bots no analytics, so you record your own. Four numbers cover most of it: how many people start, how many reach the first useful outcome, how many return after a week, and where conversations stop.
The short version
Telegram provides no analytics for bots, which means every number you have is one you chose to record. That is an advantage if you choose well, because four metrics answer almost everything worth asking. Starts count how many people open the bot at all and are mostly a measure of your distribution. Activation counts how many reach the first genuinely useful outcome — the first reminder set, the first alert delivered — and is the number that predicts whether anyone stays. Retention counts how many return after a week, which is the only honest measure of whether the bot is a habit or a novelty. Drop-off shows where multi-step flows are abandoned, which is where the fixable problems concentrate. All four come from one event log: user id, event name, timestamp. The temptation to log everything produces a table nobody queries.
Step by step
What should be logged?
One row per meaningful event: user id, event name, timestamp, and a small amount of context. Meaningful means it would change a decision. Logging every message produces volume rather than insight and makes the useful events harder to find.
What is activation for a bot?
The first moment the bot delivered on its promise — the first alert received, the first reminder that fired, the first purchase. Define it explicitly per bot. The gap between starts and activation is almost always the largest and most fixable loss in the funnel.
How do you measure retention?
Group users by the week they started and count how many are still active one, two and four weeks later. Cohorts show whether changes actually improved things; a single overall active-user number hides a leaky bucket behind new arrivals.
How do you find where people give up?
Log each step of a multi-step flow and compare the counts. The step with the largest fall is your problem, and it is usually a question that was unclear or asked too early rather than anything technical.
What catches people out
- Logging everything produces a table nobody queries; log decisions, not traffic
- A single active-user total hides churn behind new sign-ups — use cohorts
- Event logs contain personal data and belong in your privacy policy and retention rules
Questions
Can I use a normal analytics product?
Yes, by sending events server-side. Client-side web analytics does not apply, since there is no page. Many bots find that querying their own database is enough and avoids sharing user behaviour with a third party.
What is a good retention number for a bot?
It depends entirely on the category — a daily habit bot and an annual tax reminder cannot be compared. Measure against your own previous cohorts, which is the only benchmark that means anything.
Want a bot that does this?
Describe it in plain language and Botable writes the code, gives the bot its own database, deploys it and keeps it running. Everything on this page is handled for you — the token, the webhook, the storage, the hosting.