Set up a webhook using a HTTPS endpoint with a valid SSL certificate. Long polling is fine for development, but production bots should always use webhooks through a reverse proxy (Nginx or Caddy). Choose a hosting region close to Telegram's DC: Frankfurt and Amsterdam give the lowest latency for EU and CIS audiences.

Phase 2

Build the conversation engine. Use a state machine library — Node.js teams typically use Telegraf or grammY, Python teams use aiogram. Avoid raw HTTP wrappers for anything beyond simple notifications. The framework should handle: command routing, callback queries, inline keyboards, session storage, and graceful error recovery.

Implement a queue for outbound messages. Telegram enforces a 30 messages-per-second limit globally, and 1 message per second per chat. For broadcasts to 100k users, naive sendMessage loops will hit rate limits within minutes. Use a Redis-backed queue with exponential backoff on 429 responses. Nakrut.pro's internal broadcaster handles 1M+ sends with a p95 delivery time of 14 seconds.

Phase 3

Layer in payments and analytics. Telegram's native Payments API supports Stripe, YooKassa, and 10+ regional processors. For SMM funnels, the killer feature is the inline checkout button — users pay without leaving Telegram, increasing conversion by 25-40% compared to redirect-based flows.

Forward all bot events to your analytics stack. Every /start, button click, payment, and unsubscribe should land in a warehouse. Nakrut.pro pushes these to ClickHouse, which lets clients segment subscribers by LTV, source, and last-active date. This data feeds back into the broadcasting logic — high-value users get different content cadence than cold leads.

Results

| Metric | Before | After | Change | |---------|--------|-------|--------| | Subscribers | 1,200 | 87,000 | +7150% | | Delivery rate | 71% | 99.6% | +40% | | Broadcast CTR | 1.4% | 8.9% | +536% | | Paid conversion | 0.3% | 7.2% | +2300% | | Cost per lead | $4.10 | $0.62 | -85% |

What Worked

• Webhook-first architecture with strict allowed_updates cut server costs by 60% and reduced silent failures to near zero. The team could scale horizontally without rewriting the dispatcher.
• Redis-backed broadcast queue with per-chat rate limiting eliminated 429 errors entirely. Even viral growth spikes (50k joins in 24 hours) were absorbed without manual intervention.
• Native Telegram Payments inline button delivered the largest conversion lift. Removing the redirect step recovered users who would have abandoned at the browser handoff.

What Didn't Work

• Initial attempt to use Firebase Realtime Database for session storage hit write throttling at 20k concurrent users. Switching to Redis resolved it, but the migration cost three days of downtime.
• Sending media groups (albums) via synchronous calls caused timeouts on mobile networks. Async batching with retry logic fixed it, but not before a holiday broadcast failed mid-send.

Takeaways

Treat the Bot API as infrastructure, not a script. Invest early in queueing, observability, and segmentation — these are the layers that separate a toy bot from a marketing channel that drives revenue. For SMM teams without engineering capacity, platforms like Nakrut.pro provide pre-built Telegram funnels with payment and analytics integration, cutting time-to-launch from weeks to hours. Always test broadcasts on a 1% segment before sending to the full list, and monitor unsubscribe rate as your primary health metric.