12 Make.com Automations for Your Telegram Accounts, Built With Entergram

Entergram's Make.com app, included on the Pro plan, lets a Make scenario act on the same personal Telegram accounts your team already uses, instead of on a separate bot. Below are 12 scenario ideas, ordered from simplest to most involved, such as a Stripe payment that triggers a thank-you from the rep's own account and an Airtable row change that updates a chat's custom field. Each one names the upstream trigger and the Entergram action it drives.

For years the automation story on Telegram was 'build a bot.' Bots can do a lot, but they cannot act on your real chats, cannot see the messages your personal account sees, and cannot reply from your own identity. That is a hard ceiling for any serious customer workflow. The moment your automation needs to touch the conversations your humans actually have with customers, the bot story breaks.

Entergram's Make.com app removes that ceiling. Scenarios in Make.com can act on the same Telegram accounts your team uses, each of which runs through its own unique proxy. That means a Stripe payment can trigger a thank-you message from your real account. A Typeform submission can tag the corresponding Telegram chat. An Airtable row change can update a custom field. The inbox becomes part of the same workflow graph your other tools already live in.

The trigger side of each scenario uses the other app's own Make module (Stripe, Typeform, Calendly and so on). The Entergram side is the step that sends a message, writes a custom field, adds a comment or opens a ticket. Check the Entergram app inside Make for the exact actions it exposes before you design around one. For connecting Make to Entergram's MCP server, see the Make.com Telegram MCP page.

Trigger: a completed Stripe checkout. Action: an Entergram step that sends a message to the customer's Telegram chat, keyed by the Telegram username or ID you stored on the Stripe customer metadata. The point is that the customer receives the message from the same human account they chatted with pre-sale, not from a generic @StoreBot. Stripe's webhook docs are the reference for the event itself; Make's Stripe module means you do not handle the raw payload.

The pattern generalizes. Any billing event (subscription started, trial ending, refund issued, invoice paid) can fire a targeted message from the right rep's account. Each connected account runs on its own unique proxy, but pacing still matters: if a billing run produces many messages at once, spread them out rather than sending them in one burst from one account.

Inbound-lead teams live and die on this one. The Typeform trigger fires when a qualification form is submitted. Make passes the username or phone number the prospect entered to Entergram, which can resolve a contact by either, then writes a 'qualified' value and sets the lead stage to 'Demo-scheduled.' The rep sees an already-classified chat in their inbox without doing the data entry. Our lead management product page has the full pipeline primer.

Calendly fires an event when a meeting is booked. Make records the meeting time, and a scheduled scenario uses Entergram to send a reminder message through the rep's account the day before. The reminder comes from the person the prospect was going to meet, not a robot, which is the whole reason to send it from a personal account.

Teams that keep a source of truth in Airtable run into sync hell fast. With Make, a change to a row (deal size, contract stage, renewal date) can be written into the corresponding Telegram chat's custom field. The chat table then reflects the Airtable state without a manual update. Airtable's automation docs are a good primer for the trigger side; the receiving side is one Entergram step that writes the field.

A scenario runs every morning, reads your chats through Entergram, and picks out every chat where the customer sent the last message more than 24 hours ago. Make then posts the list to the owner of each chat, or writes a 'needs-reply' value to a custom field so the chats surface in a filtered view. Nobody has to remember to check.

When a support teammate drops a customer name in Slack with a specific emoji reaction, Make picks up the Slack event, finds the matching Telegram chat, and creates a ticket in Entergram with priority High. The hand-off that used to be 'who's on this?' in Slack becomes a tracked SLA ticket in the support queue. Our ticketing product page explains the ticket fields. If you only need a record of Telegram conversations in Slack, the native Slack integration already relays every chat a seat can access into one channel, one way, without Make.

A scheduled Make scenario pulls yesterday's new Telegram chats from Entergram, with their stage and tags, and posts a short digest to an internal Slack channel. Your morning standup starts from one list, not a scroll through four inboxes. If what you want is a record in Notion rather than a digest, skip Make: Entergram's native Notion integration writes new Telegram chats to your Notion database automatically.

When Shopify reports an abandoned checkout, Make filters for customers who previously opted in on Telegram, then sends a conversational message from the store's concierge account: 'Hey, noticed the cart timed out, anything I can answer?' The message lands in the same channel the customer was chatting on pre-purchase, from an account they already know.

If an inbound form is known to attract spam, pipe its submissions through an LLM filter (Make has OpenAI and Anthropic modules) and classify each as spam or real. Spam submissions get a 'spam-filtered' value on the matching chat, so it drops out of your working views. Real submissions follow the normal qualified-lead flow from Scenario 2.

A scheduled scenario reads open tickets from Entergram and checks their SLA state. For any ticket already in breach, Make sends a Telegram message to the support manager and a Slack mention in #support-urgent. Breached tickets stop sitting unnoticed until someone opens the queue. The ticket fields and SLA doc covers how SLA state works.

When a Zoom recording is ready, Make sends the transcript through an LLM for a five-bullet summary, then adds the summary to the matching Telegram chat as an internal comment for teammates. The next person on the account sees the context without rewatching the recording.

A scheduled scenario, every Monday morning, pulls last week's message events and ticket data from Entergram, has an LLM module compute message volume, response times and tickets resolved, formats the numbers into a short block, and posts it into a leadership-only Telegram channel. There is no fixed report endpoint to call: the AI does the analysis over Entergram's data, the same way it does through the MCP. See Telegram analytics for what the built-in dashboard covers.

Make's scenario graph (conditional branches, iterators, routers, error handling) suits Telegram workflows because real customer journeys are branchy. Most of the scenarios above have at least one 'if the tag exists, skip' or 'if the chat is dormant, route differently' branch, and Make handles that visually.

The short version: Make.com is the automation layer to try first if your team is Telegram-first, and Entergram is what lets that layer act on the real accounts in your inbox. Pick three from the list, build them, and keep the ones that earn their place.