Create a Map Feedback Bot for Arc Raiders: Collect, Aggregate, and Share Player Input

Hook: Turn post-match noise into developer-ready insight — fast

If you run an Arc Raiders community or work on dev-rel, you know the problem: players leave rich, actionable feedback in Discord after a match, but it lives in scattered messages, screenshots, and heated threads. Devs need structured, prioritized, and trustworthy reports — not a long log of opinions. This spec describes a Discord feedback bot that polls players after matches, aggregates map-focused input, and exports developer-ready reports optimized for Arc Raiders' 2026 map updates and community QA workflows.

Why this matters in 2026

Embark Studios confirmed new Arc Raiders maps will arrive in 2026, spanning multiple sizes and playstyles. That creates a rare opportunity: community QA can influence map tuning early. At the same time, community programs are more formalized; devs expect quantitative feedback, rapid reproduction, and prioritized issue lists. Bot-driven post-match surveys are now an essential bridge between players and design teams.

Core goals

• Capture timely, contextual feedback from players immediately after matches.
• Aggregate and normalize responses so triage is fast and defensible.
• Format output into developer-ready artifacts: CSV/JSON exports, heatmaps, triage lists for Jira/GitHub, and a summary dashboard.
• Respect privacy, rate limits, and Discord platform policies while maximizing response quality.

High-level architecture

Event-driven — the game server or matchmaking service emits a match_end webhook to a backend that then triggers a Discord interaction to the matched players. The pipeline has four layers:

1. Match telemetry source: game servers, matchmaking, or client SDK emits match_end events with context (map_id, match_id, duration, teams).
2. Feedback dispatcher: backend service processes the event, builds a per-player survey, and calls Discord interactions API.
3. Response store & processor: database for raw responses, enrichment (player stats, role, squad), and aggregation jobs.
4. Report exporter & integrations: CSV/JSON, dashboards, heatmap generator, Jira/GitHub webhook to create issues, and optional LLM summarization services.

Tech stack suggestions (2026)

• Runtime: Node.js 20+ or Python 3.12 for Discord API libraries updated for 2026 interaction features.
• Web framework: Fastify/Express or FastAPI.
• DB: Postgres for transactional data + ClickHouse or BigQuery for analytical aggregation if volume is high.
• Storage: S3-compatible for attachments and raw export artifacts.
• Queue: Redis streams or Kafka to decouple match events and survey sends.
• Visualization: Grafana or Superset for dashboards; custom heatmap generator for map spatial data.

UX spec: player journey and message flows

Design the survey to be short, contextual, and rewarding. Timing and copy matter: send the survey within 30–90 seconds after the match ends, when the experience is fresh but players aren’t alt-tabbed.

Opt-in & consent

• Ask users to opt into post-match surveys via a slash command or persistent message in the server: '/opt-in-feedback'.
• Show a short consent card that clarifies data use: 'Anonymized feedback helps tune maps. We share aggregated reports with Embark Studios.' Offer an opt-out command.

Survey format (Discord interaction components)

• Send an ephemeral message (visible only to the user) containing components: buttons, select menus, and a modal for freeform comments.
• Primary quick questions (1–3 clicks):
  • Overall map experience: 1–5 star buttons
  • Was the map balanced? (Yes / No / Unsure) — select menu
  • Top issue type: Spawn / Chokepoint / Objective / Pathing / Performance / Other — select menu
• Optional modal for details: 'Briefly explain where and why you had trouble (max 500 chars)'.
• Contextual ask: include match metadata in the payload so the player knows which map and match they're reporting about (map name, match duration, time).
• Reward micro-incentives: a role mention, kudos, or a small in-server currency for completing 3+ surveys/week to maintain response rates.

Example interaction copy

'Thanks for playing! Quick 30s survey about Stella Montis — help us make this map better for everyone.'

Data model and example schemas

Design schemas to link match telemetry, player identity (with privacy controls), and feedback. Keep personally identifiable information optional and encrypted.

Core tables

matches
- match_id PK
- map_id
- map_name
- mode
- start_time
- end_time
- match_meta JSON

players
- player_id PK (internal, hashed Discord ID)
- discord_id (nullable; only if user consents)
- role_tags JSON

feedback
- feedback_id PK
- match_id FK
- player_id FK (nullable)
- rating INT (1-5)
- issue_type VARCHAR
- comment TEXT
- map_coords JSON (optional spatial point / bbox)
- created_at
- anonymous BOOLEAN

Enrichment fields

• player_performance: kills, deaths, objective_time
• squad_size
• replay_url: link to match replay (if available)

Aggregation & analytics

Turn raw responses into answers devs can act on. Use these aggregation steps:

1. Normalize issue_type tags and run basic NLP to cluster freeform comments.
2. Calculate map-level metrics: mean rating, distribution, issue frequency per 100 matches, average time to failure (e.g., objective loss time).
3. Spatial aggregation: if players provide coords, bin into a grid and produce heatmaps for spawns, choke points, and objective hotspots.
4. Confidence score: weight feedback by sample size and match representativeness. Add a 'confidence' metric: sqrt(n) / (1 + variance) to favor consensus.
5. Prioritization score formula (example):

   priority = severity_weight * frequency * confidence

   where severity_weight maps issue_type to a severity (e.g., Spawn=1.5, Performance=2.0).

Sampling & bias handling

• Active players yield response bias. Use telemetry to stratify samples by skill bracket, time-of-day, and match outcome.
• Limit repeated surveys per player per day to avoid spam; use session-based sampling to ensure diverse respondents.

Developer-ready reports & exports

The goal is a package designers can act on in under 15 minutes. Each report should include:

• Executive summary: 3–5 bullet points (top issues, map rating, recommended next steps).
• Aggregate metrics: counts, mean rating, issue frequency, confidence bands.
• Top 10 freeform comments with metadata (anonymized) and link to replay where available.
• Spatial heatmaps: downloadable PNG/SVG and underlying grid CSV.
• Triage-ready tickets: prefilled JSON for Jira/GitHub issues with tags, priority, steps-to-reproduce, and attachments.

Sample deliverables

• map_report_StellaMontis_2026-02-01.zip containing report.pdf, heatmap.png, raw_responses.csv
• jira_payload.json ready to POST into dev backlog with title, description, and labels: map:StellaMontis, severity:high, verified:true

Automation & integrations

Integrations reduce friction between community and studio. Prioritize:

• Webhook export to Jira/GitHub for auto-raising potential issues when priority > threshold.
• Slack or MS Teams notifications to devs with one-click access to the report package.
• Embed dashboards in a Confluence page or a community portal used by the dev-rel team — consider edge-friendly publishing for low-latency dashboard access.
• Optional LLM summarization (2026): run batched summaries of comments using an internal LLM or vendor API to generate concise 'what, where, why' bullets. Use safety filters to remove PII and toxic language.

Privacy, moderation, and safety

Always design for user trust:

• Default responses to be anonymized. Store Discord IDs only if user explicitly consents.
• Implement rate limits and an appeals process. Provide users '/feedback-erase' to delete their submissions.
• Auto-moderate comments: profanity filters, spam detection, and a human review queue for flagged submissions.
• Comply with GDPR and CCPA: data retention policy (e.g., 12 months for raw comments, aggregated indefinitely), export and deletion endpoints.

Operational considerations

• Monitoring: track webhook success rate, survey open/completion rates, and response latency.
• Scaling: shard event processing by match region or map to avoid hotspots during large updates or events.
• Logging: preserve raw telemetry for reproducibility but keep logs encrypted.
• Fallbacks: if Discord interactions fail, fall back to a DM or a short link to a web survey prefilled with match metadata.

Quality and engagement tactics

Design for high-quality responses, not just high volume.

• Keep surveys under 60 seconds. Short questions and one optional comment field increase completion.
• Contextual prompts: show a mini-map screenshot or replay thumbnail to prompt precise feedback.
• Batch respondents for follow-up: select a small sample of users for deeper interviews or playtests, and reward them with access or swag.
• Publish change logs: when feedback leads to an actionable change, show the community 'you spoke, we shipped' posts — this boosts future participation.

Advanced strategies & 2026 predictions

Use modern tooling to turn feedback into continuous improvement.

• LLM-assisted triage: automatic summarization and suggested repro steps can cut developer triage time by 40% in our estimates. Always surface the raw comments with summaries for verification.
• Vector search for comment clusters: store embeddings of comments to quickly surface similar issues across maps and seasons.
• Real-time map heatmaps: integrate with replay telemetry to overlay player deaths, objective fail points, and pathing on the same heatmap as subjective player pain points.
• Adaptive sampling: increase survey frequency on new or heavily changed maps and lower it on stable ones to reduce fatigue.

Mini case study: Arc Raiders community dev-rel

Imagine the Arc Raiders community server running the bot during the 2026 map rollout. Within two weeks, the bot collected 8,200 responses across three new maps. Aggregation surfaced one persistent choke in a mid-size map where 27% of players reported 'spawn camping' in the first 90 seconds. The dev-rel team triaged the issue, attached replay clips, and the level designer shipped a tuning tweak in 10 days. The team then published a 5-bullet summary in Discord and the official patch notes — response rates increased for the next survey by 38%.

Implementation checklist (30/60/90 day)

• 0-30 days: Build match_end webhook consumer, Discord interaction for survey, and a basic Postgres schema. Launch opt-in in a single test channel.
• 30-60 days: Add enrichment (player stats), aggregation jobs, and CSV/JSON export. Hook up a basic dashboard and Jira export.
• 60-90 days: Add spatial heatmaps, LLM summarization, advanced sampling, and automated issue creation with confidence thresholds. Run a pilot with dev-rel and iterate on copy and incentives.

Sample slash commands & admin tools

• /opt-in-feedback — opt into post-match surveys
• /survey-stats map:StellaMontis period:7d — get quick aggregated metrics
• /export-report map:BlueGate format:zip — generate and DM a developer-ready package
• /retrain-embeddings — admin tool to cluster new comments

Wrap-up: turn community passion into actionable map improvement

A well-designed Arc Raiders feedback bot closes the loop between players and devs. In 2026, with new maps rolling out, there's no better time to build a structured pipeline that captures timely player input, de-noises it with aggregation, and hands developers prioritized, reproducible reports. The combination of Discord interactions, match telemetry, and modern analytics lets dev-rel teams move from anecdote to action.

Actionable takeaways

• Ship an opt-in, ephemeral post-match survey within 30–90 seconds.
• Collect structured answers + one optional comment and link to replay.
• Aggregate with confidence weighting and generate triage-ready tickets automatically.
• Respect privacy: anonymize by default and provide deletion tools.
• Iterate: publish wins back to the community to boost participation.

Call to action

Ready to build a feedback bot for your Arc Raiders community? Start with a 30-day pilot: deploy the webhook consumer, a short survey, and an export to CSV. If you want a starter kit or a reference implementation, join the discords.space community QA channel and grab our open-source scaffold tailored to Arc Raiders 2026 workflows.

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