Build a Web3 Live Streaming App with Analytics Dashboard

TL;DR

• To build a live streaming app for Web3, you need more than video playback: wallet identity, token-gated access, live chat, moderation, real-time quality monitoring, and a post-stream operations dashboard.
• Use WebRTC live streaming for interactive rooms, co-hosting, low latency, and audience participation. Use HLS/CDN distribution when latency is less important than massive passive viewing scale.
• A production Web3 live room usually includes a mobile app, web client, live streaming SDK, chat SDK, wallet service, backend token service, analytics pipeline, moderation workflow, and admin dashboard.
• Your operations dashboard should track per-stream KPIs: unique viewers, peak concurrency, watch time, join-to-watch funnel, chat engagement, co-host invites, stream quality, moderation incidents, NFT/token purchases, and creator revenue.
• Tencent RTC can provide the real-time layer for live streaming and chat. Start with the Tencent RTC Live documentation and add Free Chat API — free forever: 1,000 MAU, no concurrency limits, push notifications included.

What a Web3 live streaming app needs beyond basic video playback

If your goal is to build a live streaming app for Web3, avoid treating it like a normal video player project. The stream is not only media. It is also identity, ownership, access control, community interaction, and transaction activity.

A Web3 live room may need to answer questions like:

• Is the viewer connected with a wallet?
• Does the wallet hold a required NFT, token, pass, or subscription?
• Which wallet joined, watched, chatted, tipped, purchased, or claimed rewards?
• Were there quality issues that affected creator performance?
• Did moderation events reduce harmful content or spam?

That is why “how to build a live streaming app” for Web3 is really a systems design problem. You are building an interactive media product plus a trust, identity, commerce, and analytics layer.

Core components of a Web3 live room

A production live room usually includes:

The key is to design these components together. If you only log “viewer joined” events but do not connect them to wallet addresses, you cannot measure token-holder retention.

Web3-specific live streaming requirements

A Web3 live streaming app usually needs at least five capabilities beyond basic video:

1. Wallet-based identity

Wallet login should become a first-class identity signal. The common approach is to support normal user accounts plus wallet binding. For Ethereum-compatible wallets, many teams use the Sign-In with Ethereum pattern defined by EIP-4361.

The app can store internal user ID, wallet address, chain ID, signature verification status, NFT/token ownership snapshot, and risk flags.

2. Token-gated access

A creator may want a stream to be public, subscribers-only, NFT-holder-only, DAO-member-only, or paid-ticket-only. Token gating requires backend verification. Do not trust the client to decide access by itself.

The backend should verify the user’s wallet, check token ownership or payment status, then generate a live room access credential.

3. Interactive video streaming

Web3 communities often expect participation: co-hosting, viewer-to-speaker promotion, AMA sessions, real-time reactions, live polls, and token-based rewards.

This is where interactive video streaming differs from passive broadcast. WebRTC is usually a better fit than delayed HLS when audience participation matters.

4. Live chat and community signals

Chat is not only a feature. It is a data source. Track messages per minute, unique chatters, reactions, moderation actions, spam rate, wallet-connected chatters, and token-holder chat participation.

For live chat implementation, Tencent RTC provides Tencent RTC Chat documentation and a Free Chat API with 1,000 MAU, no concurrency limits, and push notifications included.

5. Operations analytics

Web3 teams need per-stream reports because every live event may be tied to creator performance, token campaigns, NFT launches, or community growth.

Your dashboard should answer:

• How many users entered the stream page?
• How many successfully watched video?
• How many connected wallets?
• How many token holders watched?
• Did chat engagement correlate with purchases?
• Did poor network quality reduce conversion?

Without this dashboard, you are flying blind.

Architecture overview: mobile app, web client, live streaming SDK/API, chat, wallet, and backend services

A reliable Web3 live streaming architecture separates real-time communication, business logic, identity, analytics, and operations tooling.

Here is a practical architecture for teams that want to build an app with live streaming on web and mobile.

iOS / Android App                 Web App
       |                              |
       | Live SDK + Chat SDK          | Live SDK + Chat SDK
       | Wallet adapter               | Wallet adapter
       v                              v
Live Streaming Network <------> Chat Service
       |                              |
       v                              v
Backend API Gateway  <------> Auth / Wallet Service
       |
       | emits events
       v
Event Collector --> Queue/Stream --> Analytics Warehouse
       |                                  |
       v                                  v
Moderation Service                 Operations Dashboard
       |
       v
Admin Console / Creator Reports

Client applications

You usually need both App and Web clients:

• Mobile app for creators, fans, push notifications, and high-retention community use.
• Web client for discovery, wallet-native interactions, NFT drops, SEO landing pages, and desktop watching.

Both clients should share the same room model:

{
  "roomId": "stream_2026_0421_001",
  "hostUserId": "creator_123",
  "hostWallet": "0x123...",
  "visibility": "token_gated",
  "status": "live",
  "streamMode": "interactive",
  "chatGroupId": "chat_stream_2026_0421_001"
}

The room model should not be owned by the live SDK alone. Your backend should own the business state: scheduled, live, ended, replay processing, report ready.

Live streaming SDK/API

The live streaming SDK handles real-time audio/video. It should support host publishing, viewer playback, role switching, co-hosting, camera/microphone controls, network quality callbacks, device switching, screen sharing for web, and room entry/exit events.

Tencent RTC offers live streaming documentation for implementation details in Tencent RTC Live overview. For SDK downloads and platform-specific packages, use the Tencent RTC SDK download documentation.

Chat service

Live chat should be modeled separately from video because chat has different persistence, moderation, search, and notification requirements.

Tencent RTC Chat supports live chat room use cases such as group chat, message types, reactions, moderation, and push workflows. If your MVP needs chat plus notifications without stitching multiple vendors together, start with Tencent RTC Free Chat API.

Free Chat API — free forever: 1,000 MAU, no concurrency limits, push notifications included.

Wallet service

A wallet service verifies signatures and maps wallet identities to app users. A basic flow looks like this:

1. Client requests a nonce.
2. User signs a message with a wallet.
3. Backend verifies the signature.
4. Backend binds wallet address to user ID.
5. Backend checks token/NFT access rules.
6. Backend issues live room credentials.

For Ethereum-compatible apps, review the EIP-4361 Sign-In with Ethereum specification.

Backend services

Your backend should handle room creation, host authorization, access control, token-gating rules, SDK credential generation, chat group creation, webhook ingestion, moderation decisions, analytics events, and post-live reports.

Do not put SDK secrets, private keys, or privileged role logic in the client.

Analytics warehouse and dashboard

Your analytics layer receives events from the web app, mobile app, live SDK callbacks, chat service, wallet service, and smart contract indexer.

Common storage choices include PostgreSQL for operational dashboards, ClickHouse, BigQuery, Snowflake, or Apache Druid for event analytics, Redis for real-time counters, and object storage for raw archives.

The dashboard should support both real-time monitoring and post-live reports.

Choosing the live streaming stack: WebRTC live streaming vs RTMP/HLS vs interactive streaming APIs

Before writing code, choose the right streaming model. The best live stream SDK depends on your latency, interactivity, scale, and cost requirements.

Option 1: WebRTC live streaming

WebRTC live streaming is designed for real-time audio/video communication. The WebRTC project describes it as an open framework for real-time communication in browsers and native apps (WebRTC.org). Browser APIs are standardized through groups such as the W3C WebRTC Working Group.

WebRTC is best when you need low latency, co-hosting, live Q&A, audience-to-speaker promotion, real-time auctions, social live rooms, interactive gaming or creator events, and real-time quality adaptation.

Tradeoffs:

• More complex than playing an HLS URL
• Requires a real-time network and room infrastructure
• Needs careful permission and role management
• Large passive audiences may need hybrid distribution

For Web3, WebRTC is often the default for interactive creator rooms, token-holder AMAs, NFT launches, and community town halls.

Option 2: RTMP ingest plus HLS playback

RTMP/HLS is a classic broadcast architecture:

1. Host pushes RTMP to an ingest server.
2. Server transcodes and segments video.
3. Viewers play HLS or DASH through a CDN.

This is best when you need massive passive viewership, CDN-based scale, compatibility with existing encoders, replays, VOD workflows, and lower infrastructure cost for non-interactive events.

Tradeoffs:

• Higher latency than WebRTC
• Co-hosting is not native
• Real-time audience participation is harder
• Chat and video may feel out of sync

For Web3, RTMP/HLS can work for keynote-style broadcasts, but it is less ideal for interactive token-gated rooms.

Option 3: Interactive streaming APIs

A managed video live streaming API or live streaming API for website abstracts much of the networking complexity. Vendors such as Agora, GetStream, ZEGOCLOUD, and Tencent RTC offer SDKs/APIs for real-time engagement use cases.

When evaluating interactive streaming APIs, compare latency, platform support, co-hosting limits, chat integration, moderation, recording, analytics hooks, pricing, concurrency limits, global infrastructure, and developer documentation.

Tencent RTC is a strong fit when you need to combine live streaming with real-time chat, large-scale audience interaction, and multi-platform support. The broader Tencent RTC platform serves 1 billion+ monthly active users, and the Chat product supports 550 billion+ daily peak messages with >99.99% message success rate.

Selection matrix

For most Web3 products, the practical path is hybrid: use WebRTC for interactive rooms and optionally use CDN/HLS for overflow passive viewing or replays.

Building the live room experience for App and Web: host publishing, audience viewing, co-hosting, low latency, and live chat

The live room experience has five core states:

1. Scheduled
2. Pre-live waiting room
3. Live
4. Ended
5. Replay/report ready

Your product should make these states explicit in both the frontend and backend. A user should not join a room as a viewer if the host has not started. A creator should not publish if their wallet or role is not authorized.

Host publishing flow

A secure host flow:

1. Creator logs in.
2. Creator connects wallet.
3. Backend verifies host permission.
4. Backend creates or loads room.
5. Backend issues SDK credentials for host role.
6. Client initializes the live SDK.
7. Client starts camera/mic preview.
8. Creator taps “Go Live.”
9. Backend marks room as live.
10. Analytics records stream_started.

Audience viewing flow

A secure audience flow:

1. User opens stream page.
2. Client records stream_page_viewed.
3. User logs in or connects wallet if required.
4. Backend checks access.
5. Backend issues viewer credentials.
6. Client joins live room.
7. Client subscribes to host stream.
8. Client joins chat group.
9. Analytics records viewer_joined and video_first_frame.

Web example: join a Tencent RTC live room

The exact API surface may vary by SDK version and product mode, so always verify with the Tencent RTC Live documentation. The following snippet shows the key client-side pattern: initialize, enter a room, publish as host or subscribe as viewer, and clean up on exit.

import TRTC from 'trtc-sdk-v5';

const sdkAppId = Number(import.meta.env.VITE_TENCENT_RTC_SDK_APP_ID);
const userId = window.currentUser.id;
const userSig = window.currentUser.userSig;
const roomId = "web3-live-room-1001";

const client = TRTC.create();

export async function joinLiveRoom(role: "host" | "viewer") {
  await client.enterRoom({
    sdkAppId,
    userId,
    userSig,
    roomId,
    scene: "live",
    role: role === "host" ? "anchor" : "audience"
  });

  if (role === "host") {
    const localStream = await TRTC.createStream({
      audio: true,
      video: true
    });

    await localStream.initialize();
    localStream.play("local-preview");
    await client.publish(localStream);
  }

  client.on("stream-added", async (event) => {
    const remoteStream = event.stream;
    await client.subscribe(remoteStream);
    remoteStream.play("remote-player");
  });

  client.on("network-quality", (event) => {
    window.analytics.track("stream_quality_sample", {
      roomId,
      userId,
      uplink: event.uplinkNetworkQuality,
      downlink: event.downlinkNetworkQuality,
      ts: Date.now()
    });
  });
}

export async function leaveLiveRoom() {
  await client.exitRoom();
}

This is not a full app. It is the minimum pattern your engineering team needs to validate a WebRTC live streaming demo: enter, publish, subscribe, track network quality, and exit.

Live chat integration

Live chat should start when the viewer joins the room, not after video playback. If chat fails, the room feels empty even when video works.

Track chat events such as:

• chat_joined
• message_sent
• reaction_sent
• message_deleted
• user_muted
• moderator_action_created

Tencent RTC Chat supports text, image, audio, video, file, custom messages, read receipts, group chat, live chat rooms, reactions, translation, and content moderation. For implementation details, use Tencent RTC Chat overview.

Co-hosting and role switching

Co-hosting is where many live apps become complicated. A viewer may request to speak, the host approves, and the user changes from audience to co-host.

Your backend should control this state:

viewer_requested_cohost
host_approved_cohost
viewer_role_upgraded
cohost_published_stream
cohost_left
viewer_role_downgraded

Do not rely only on client UI state. Store role transitions in your backend so analytics can calculate how co-hosting affects retention and revenue.

Low latency considerations

For interactive rooms, optimize:

• Use the closest media access region when available.
• Track first-frame time.
• Track freeze duration.
• Track audio/video packet loss.
• Provide fallback UI for weak networks.
• Use adaptive resolution and bitrate.
• Keep chat and video timestamps aligned.

The user experience goal is simple: when the host asks a question, the audience can react immediately.

Designing the operations analytics dashboard: per-stream KPIs, viewer funnel, engagement, quality metrics, and revenue signals

The operations dashboard helps your team answer whether each stream performed well, why it performed that way, and what to improve next time.

A good dashboard has four layers:

1. Executive summary
2. Viewer funnel
3. Engagement and community
4. Quality, moderation, and revenue diagnostics

Per-stream KPI summary

At the top of each stream report, show:

Viewer funnel

Your funnel should show each step:

1. Stream page viewed
2. Login completed
3. Wallet connected
4. Access verified
5. Room joined
6. First video frame rendered
7. Watched 30 seconds
8. Sent chat or reaction
9. Completed Web3 transaction
10. Returned for another stream

This funnel reveals product issues. For example:

• High page views but low room joins may indicate wallet friction.
• High joins but low first-frame success may indicate streaming quality problems.
• High watch time but low transactions may indicate weak offer design.
• High chat activity but low watch time may indicate drama, spam, or poor moderation.

Engagement metrics

Track both volume and quality:

• Messages per minute
• Reactions per minute
• Unique chatters
• Questions asked
• Poll participation
• Co-host requests
• Token-holder engagement
• New follower/subscriber events

For Web3 communities, segment by wallet status:

Quality metrics

Streaming quality directly affects revenue and retention. Include join success rate, first-frame time, freeze rate, bitrate, resolution, packet loss, reconnect count, device type, browser/app version, and region/network type.

For every stream, your dashboard should show whether performance issues came from host uplink, viewer downlink, device compatibility, or regional network conditions.

Revenue and Web3 signals

For Web3 live streaming, revenue may not be only fiat subscription income. Track token tips, NFT mint events, paid access passes, creator subscription purchases, airdrop claims, DAO membership conversions, on-chain transaction attempts, transaction failures, gas-related drop-offs, and wallet signature failures.

Use transaction hashes where appropriate, but avoid exposing sensitive user-level financial data in broad admin views.

Recommended dashboard pages

Build these pages first:

1. Live Monitor: real-time viewers, host status, stream quality, chat rate.
2. Stream Report: post-live KPIs, funnel, engagement, revenue.
3. Creator Performance: creator-level trends across streams.
4. Moderation Review: deleted messages, muted users, flagged content.
5. Quality Diagnostics: network, device, region, SDK version.
6. Web3 Conversion: wallet connect, token gating, purchases, claims.

Data pipeline tutorial: collecting live events, stream quality data, chat events, and Web3 transaction events

The dashboard is only as good as your event model. Before building charts, define a clean event taxonomy.

Event naming model

Use consistent event names:

Every event should include:

• event_id
• event_name
• timestamp
• stream_id
• room_id
• user_id
• wallet_address_hash where applicable
• session_id
• platform
• app_version
• device
• region
• Event-specific properties

Avoid putting raw wallet addresses into every analytics table. Hash or tokenize them when user-level attribution is not required.

Backend event collector example

The following Node.js example shows a minimal event collector that receives live events from web/mobile clients, validates the payload, stores it, and leaves room for streaming the same event into a queue or warehouse.

import express from "express";
import crypto from "crypto";
import { Pool } from "pg";

const app = express();
app.use(express.json());

const db = new Pool({ connectionString: process.env.DATABASE_URL });

function hashWallet(address?: string) {
  if (!address) return null;
  return crypto.createHash("sha256")
    .update(address.toLowerCase() + process.env.WALLET_HASH_SALT)
    .digest("hex");
}

app.post("/events/live", async (req, res) => {
  const {
    eventName, streamId, roomId, userId, walletAddress,
    sessionId, platform, properties = {}
  } = req.body;

  if (!eventName || !streamId || !userId || !sessionId) {
    return res.status(400).json({ error: "Missing required fields" });
  }

  await db.query(
    `insert into live_events
     (event_name, stream_id, room_id, user_id, wallet_hash,
      session_id, platform, properties, created_at)
     values ($1,$2,$3,$4,$5,$6,$7,$8,now())`,
    [
      eventName,
      streamId,
      roomId,
      userId,
      hashWallet(walletAddress),
      sessionId,
      platform,
      JSON.stringify(properties)
    ]
  );

  res.json({ ok: true });
});

app.listen(3000, () => console.log("event collector on :3000"));

For production, add authentication, rate limits, schema validation, idempotency keys, batching, retry logic, and a queue such as Kafka, Pub/Sub, Kinesis, or RabbitMQ.

Table design for analytics

Start with three tables:

streams

stream_id
creator_id
creator_wallet_hash
title
scheduled_at
started_at
ended_at
visibility
status
chat_group_id
created_at

live_events

event_id
event_name
stream_id
room_id
user_id
wallet_hash
session_id
platform
properties
created_at

stream_quality_samples

sample_id
stream_id
room_id
user_id
role
uplink_quality
downlink_quality
bitrate
packet_loss
rtt
freeze_duration_ms
created_at

You may later add specialized tables for transactions, moderation, and creator payouts.

Joining streaming and Web3 data

The key is to join by stable identifiers:

• stream_id for stream-level analysis
• user_id for app-level behavior
• wallet_hash for Web3 segmentation
• transaction_hash for on-chain confirmation
• session_id for funnel analysis

Example analytics questions:

select
  stream_id,
  count(distinct user_id) filter (where event_name = 'viewer_joined') as viewers,
  count(distinct user_id) filter (where event_name = 'message_sent') as chatters,
  count(distinct user_id) filter (where event_name = 'wallet_connected') as wallets,
  count(distinct user_id) filter (where event_name = 'mint_confirmed') as minters
from live_events
where created_at >= now() - interval '7 days'
group by stream_id
order by viewers desc;

Real-time dashboard counters

For the live monitor, avoid querying a large warehouse every second. Use Redis or another low-latency store for current viewers, peak viewers, chat messages per minute, error rate, first-frame failures, active moderators, and host network status.

Then write final events to durable storage for post-live reporting.

Privacy and compliance notes

Even if your app is Web3-native, privacy still matters. Follow data minimization principles:

• Store only the wallet data you need.
• Hash wallet addresses in analytics views.
• Separate operational access from financial data access.
• Keep audit logs for admin actions.
• Provide deletion/export workflows where required.
• Review guidance such as the OWASP Logging Cheat Sheet for secure event logging.

Pricing and vendor selection checklist: live streaming API costs, SDK limits, concurrency, moderation, and analytics support

Pricing for a live streaming app is rarely one line item. You may pay for video minutes, audio minutes, recording, transcoding, CDN delivery, chat MAU, push notifications, moderation, analytics, storage, and bandwidth.

When comparing Tencent RTC, Agora, GetStream, ZEGOCLOUD, or other providers, use a checklist instead of looking only at the headline price.

Vendor comparison dimensions

For competitor research, review official vendor pages such as Agora, GetStream, and ZEGOCLOUD. Always verify pricing on vendor pricing pages because live streaming costs can change by region, media type, and usage profile.

Chat and push cost considerations

If your live app includes chat, push notifications, and audience engagement, chat pricing matters. Tencent RTC Chat has a permanent free tier for up to 1,000 MAU, full feature access, unlimited concurrent connections, and a free Push plugin covering APNs, FCM, Huawei, Xiaomi, OPPO, and vivo.

Use Tencent RTC Chat pricing for detailed packaging and Tencent RTC Free Chat API for the free tier.

This matters because live streaming apps often have spiky concurrency. A creator event can bring many users into the same room at the same time. If your chat provider limits concurrent connections aggressively, your “free” or low-cost plan may not support a real live event.

Analytics support

Ask each provider:

• Can I receive network quality callbacks?
• Can I export usage data per room?
• Can I identify host-side versus viewer-side quality issues?
• Can I track first-frame time?
• Can I track stream interruptions?
• Are there webhooks for room lifecycle events?
• Can I combine SDK events with my own business events?

Even if a vendor has a dashboard, you still need your own operations analytics if you want to connect media performance with wallet behavior and revenue.

Build versus buy

Build your own stack if you need deep custom infrastructure, have real-time media expertise, expect unusual protocol requirements, or want full control over every network layer.

Use a managed live streaming sdk or video live streaming api if you want to ship faster, have a small team, need mobile and web support, need global reliability, or want integrated chat, moderation, and analytics hooks.

For most Web3 startups, managed infrastructure is the faster and safer path.

Launch checklist: testing a WebRTC live streaming demo, scaling for peak traffic, moderation, compliance, and post-live reporting

Before launch, test the app like a live operations team, not only like a frontend team.

1. Validate the WebRTC live streaming demo

Your demo should prove:

• Host can start stream on web and mobile.
• Viewer can join on web and mobile.
• First frame appears reliably.
• Chat works while video plays.
• Host can invite a co-host.
• Viewer can request co-hosting.
• Weak network conditions show graceful UI.
• Leaving and rejoining works.
• Analytics events arrive correctly.
• Post-live report is generated.

Use the Tencent RTC Live documentation as your implementation reference.

2. Test wallet and token-gated access

Test these cases:

• User without wallet
• User with wallet but no token
• User with correct NFT/token
• User whose token state changes during the session
• Expired signature
• Wrong chain
• Replayed signature
• Denied region or compliance state

Never assume wallet connection equals access permission.

3. Test peak traffic

Peak traffic can break systems that look fine in development.

Load test stream page load, backend credential generation, chat room join, event collector ingestion, dashboard queries, wallet verification, and transaction callback handling.

For the live room, test realistic concurrency patterns: a large spike at stream start, chat bursts after announcements, and transaction bursts during drops.

4. Prepare moderation

Moderation should include host controls, admin controls, keyword filters, spam detection, link controls, user mute/ban, message deletion, report user flow, and moderator audit log.

For chat safety and community operations, see Tencent RTC Chat documentation and plan your own policy layer around it.

5. Prepare compliance and security

Review terms of service, creator monetization rules, age restrictions, regional availability, token sale restrictions, data retention, wallet data handling, admin permissions, and incident response.

For browser security basics, the MDN Web security guide is a useful reference.

6. Generate post-live reporting automatically

After stream_ended, your backend should:

1. Close the room state.
2. Stop accepting co-host role upgrades.
3. Finalize viewer watch sessions.
4. Aggregate engagement metrics.
5. Pull transaction confirmations.
6. Calculate quality summaries.
7. Generate creator report.
8. Notify operations team.
9. Make replay available if enabled.

A strong post-live report helps creators improve and helps your team prioritize product work.

Accelerate integration with Tencent RTC AI Agents Skills

Instead of reading documentation page by page, point your AI coding assistant at the official Tencent RTC AI Agents Skills repository. Skills are markdown-based instruction packs that teach Claude, Cursor, CodeBuddy, Copilot, and other AI agents how to scaffold Tencent RTC integrations correctly the first time.

Setup:

git clone https://github.com/Tencent-RTC/agent-skills.git

Then load the relevant skill into your AI assistant’s context, such as live-streaming-setup, chat-sdk-quickstart, or a web integration skill. The agent inherits Tencent RTC SDK conventions, code patterns, and credential placement rules, reducing the risk of hallucinated APIs or outdated snippets.

Example prompts:

• “Create a Web3 live streaming room using Tencent RTC Web SDK with host and viewer roles.”
• “Add live chat to my React live streaming page with message history and moderation hooks.”
• “Generate a Node.js backend for live room credentials, wallet verification, and analytics events.”
• “Create an operations dashboard schema for per-stream live streaming analytics.”

For a complete implementation path, combine the Skills repository with Tencent RTC Live documentation, Tencent RTC Chat documentation, and Tencent RTC SDK downloads.

FAQ

What is the best way to build a live streaming app for Web3?

The best approach is to use a managed live streaming SDK for real-time audio/video, a chat SDK for audience interaction, wallet verification for identity, backend access control for token gating, and an analytics pipeline for per-stream operations reporting.

Should I use WebRTC or HLS for a Web3 live streaming app?

Use WebRTC for interactive video streaming, co-hosting, live Q&A, and low-latency community events. Use HLS/CDN delivery for large passive broadcasts or replays where latency is less important.

What analytics should a live streaming dashboard include?

Track unique viewers, peak concurrency, watch time, first-frame success, chat engagement, wallet connect rate, token-holder participation, stream quality, moderation actions, and revenue events such as tips, NFT mints, or paid access purchases.

How do I connect wallet activity with live streaming analytics?

Use stable identifiers such as user_id, stream_id, session_id, and a hashed wallet address. Emit wallet events like wallet_connected, access_verified, mint_confirmed, and tip_sent, then join them with live viewing and chat events.

Do I need a separate chat SDK for live streaming?

In most production apps, yes. Chat has different requirements from video: message history, moderation, push notifications, reactions, search, and offline handling. Tencent RTC provides Free Chat API with 1,000 MAU, no concurrency limits, and push included.

How do I reduce latency in a live streaming app?

Use WebRTC for interactive rooms, choose the closest available media region, track first-frame time, monitor packet loss, use adaptive bitrate, avoid unnecessary transcoding, and collect quality samples from both host and viewer clients.

What should I test before launching a Web3 live event?

Test host publishing, viewer playback, co-hosting, wallet login, token-gated access, chat, moderation, transaction events, analytics ingestion, peak concurrency, weak network behavior, and post-live report generation.

Where should I start with Tencent RTC?

Start with Tencent RTC Live documentation for live streaming, add Tencent RTC Chat overview for audience interaction, and create an account through Tencent RTC registration when you are ready to build.