Member Segmentation Survey for Discord Communities

Classify new members into meaningful engagement segments during onboarding using a hidden multi-bucket scoring survey. Each segment receives a personalized welcome path, the matching Discord role, and an achievement badge, and moderators get a clean, exportable record of how their community is composed.

The scenario

You run a 2,000-member gaming community. New members self-select into the server but you have no structured picture of who they actually are: competitive grinders, casual players, lore enthusiasts, or people who are mainly there for the social side. That gap makes it hard to target announcements, design events, and understand what keeps people engaged.

This recipe instruments a 6-question onboarding survey that scores members across four hidden dimensions (Competitor / Creator / Explorer / Social) and uses argmax to assign each member to their dominant segment. The result:

1. For the member: a personalized welcome embed naming their segment, the matching Discord role, and a small XP bonus.
2. For the server: every member’s segment recorded in the Responses tab with the raw bucket scores, exportable as a structured dataset at any time.

Members never see the scoring logic. They answer six short questions. The segments emerge from their patterns.

Segment definitions

Define four segments with clear behavioral signatures before authoring:

Each segment needs a Discord role (for routing and mentions) and a Subo achievement (for the permanent profile record + role grant). Create these before authoring the survey.

Scoring design

Six questions, four options each. Each option distributes points across the four buckets. Unlike a right/wrong quiz, every option carries weight. The question is how points are distributed, not whether the option is correct.

Design principle: options should feel equally valid to the respondent. Avoid signalling which answer is “better”. If members can see the segments in the options, they’ll self-sort incorrectly. The scoring should be opaque to them.

Example question and weights:

"After a long session, what do you usually share in the server?"
  A) My match stats and rank progress          → Competitor +3, Social +1
  B) A clip or guide I made                    → Creator +3, Social +1
  C) Something interesting I found in the game → Explorer +3, Social +1
  D) Just hang out in chat with others         → Social +3

Repeating this across six questions, each framed around a different context (what you share, what you look forward to, how you help others, what kind of event excites you, etc.), produces reliable differentiation without making the underlying dimensions obvious.

Target score range: aim for a maximum of ~18-20 points per bucket (6 questions × weights of 1-3). This gives enough resolution for argmax to distinguish clear dominant segments while still allowing borderline members to appear meaningfully mixed.

Flow

  ┌──────────────────────────────────────────┐
  │ q1: Intro (content_block)                │
  │ "Welcome, [UserName]! Quick intro…"      │
  │ → [ Let's go ]                           │
  └──────────────────────────────────────────┘
                    │
                    ▼
  ┌──────────────────────────────────────────┐
  │ q2–q7: Six behavior questions            │
  │ (single_punch, no correct answer)        │
  │ Each option: score_values distributing   │
  │ hidden points across 4 buckets           │
  └──────────────────────────────────────────┘
                    │
                    ▼
  ┌──────────────────────────────────────────┐
  │ q8: Segment calculated_block             │
  │ argmax([score_competitor],               │
  │        [score_creator],                  │
  │        [score_explorer],                 │
  │        [score_social])                   │
  └──────────────────────────────────────────┘
                    │
                    ▼
  ╔══════════════════════════════════════════╗
  ║ q9–q12: Four reveal content_blocks       ║
  ║ One per segment — shows only when q8     ║
  ║ matches that segment name                ║
  ║ (personalized welcome + role description)║
  ╚══════════════════════════════════════════╝
                    │
                    ▼
  ╔══════════════════════════════════════════╗
  ║ q13–q16: Four give_achievement blocks    ║
  ║ One per segment — fires when q8 matches  ║
  ║ fire_scope: respondent                   ║
  ╚══════════════════════════════════════════╝
                    │
                    ▼
  ┌──────────────────────────────────────────┐
  │ Outro: welcome XP + closing message      │
  └──────────────────────────────────────────┘

Prerequisites

1. Score buckets (4 total)

Create these in the project’s scoring settings. The bucket display name drives the variable key (lowercased, spaces → _) and the string that argmax returns:

2. Achievements and roles

Create one achievement and one linked Discord role per segment in your community Rewards settings. Record each xp_role_id.

3. Project

POST /v1/communities/{communityId}/projects
{
  "name": "Welcome — Member Intro",
  "scoring_enabled": true,
  "settings": {
    "max_completes_per_user": 1,
    "is_anonymous": false
  }
}

Script payload (abbreviated)

{
  "blocks": [
    // q1 — intro
    {
      "type": "content_block",
      "prompt": "Welcome to the community, [UserName]! 🎮\n\nBefore you dive in — 6 quick questions to help us understand what kind of player you are.\n\nNo right or wrong answers. Just be honest.",
      "continue": { "after": "click", "label": "Let's go →" }
    },

    // q2 — first behavior question
    {
      "type": "single_punch",
      "prompt": "After a long gaming session, what are you most likely to share in the server?",
      "options": [
        { "value": "Stats",   "label": "📊 My match stats and rank progress",
          "score_values": { "competitor": 3, "social": 1 } },
        { "value": "Content", "label": "🎬 A clip or guide I made",
          "score_values": { "creator": 3, "social": 1 } },
        { "value": "Find",    "label": "🔍 Something interesting I discovered in the game",
          "score_values": { "explorer": 3, "social": 1 } },
        { "value": "Hang",    "label": "💬 I just hang out in chat",
          "score_values": { "social": 4 } }
      ]
    },

    // q3–q7 — five more questions, same structure …

    // q8 — segment calculated block
    {
      "type": "calculated_block",
      "prompt": "",
      "calculated_formula": "argmax([score_competitor],[score_creator],[score_explorer],[score_social])"
    },

    // q9 — Competitor reveal (hides when q8 ≠ Competitor)
    {
      "type": "content_block",
      "prompt": "## You're a Competitor 🏆\n\nYou're here to win, improve, and prove it. You'll find your people in **#ranked-chat** and **#tournament-announcements**.\n\nWelcome to the grind.",
      "precondition": "NOT((q8=\"Competitor\"))",
      "continue": { "after": "pause", "pause": 3 }
    },

    // q10 — Creator reveal
    {
      "type": "content_block",
      "prompt": "## You're a Creator 🎨\n\nYou make things — guides, clips, art, builds. Head to **#creator-showcase** and **#feedback-wanted** — that's your home base.",
      "precondition": "NOT((q8=\"Creator\"))",
      "continue": { "after": "pause", "pause": 3 }
    },

    // q11 — Explorer reveal
    {
      "type": "content_block",
      "prompt": "## You're an Explorer 🗺️\n\nYou go deep. Lore, hidden mechanics, secrets. You'll love **#theory-craft** and **#deep-dives**.",
      "precondition": "NOT((q8=\"Explorer\"))",
      "continue": { "after": "pause", "pause": 3 }
    },

    // q12 — Social reveal
    {
      "type": "content_block",
      "prompt": "## You're a Social 💬\n\nThe community IS the game for you. You'll feel right at home in **#general** and **#events** — and we'll probably see you helping newcomers soon.",
      "precondition": "NOT((q8=\"Social\"))",
      "continue": { "after": "pause", "pause": 3 }
    },

    // q13–q16 — achievement grants (one fires, three hide)
    {
      "type": "action_block",
      "action_kind": "give_achievement",
      "action_config": { "xp_role_id": 2001, "fire_scope": "respondent" },
      "precondition": "NOT((q8=\"Competitor\"))",
      "prompt": "The **Competitor** role is yours. 🏆",
      "continue": { "after": "pause", "pause": 2 }
    },
    {
      "type": "action_block",
      "action_kind": "give_achievement",
      "action_config": { "xp_role_id": 2002, "fire_scope": "respondent" },
      "precondition": "NOT((q8=\"Creator\"))",
      "prompt": "The **Creator** role is yours. 🎨",
      "continue": { "after": "pause", "pause": 2 }
    },
    {
      "type": "action_block",
      "action_kind": "give_achievement",
      "action_config": { "xp_role_id": 2003, "fire_scope": "respondent" },
      "precondition": "NOT((q8=\"Explorer\"))",
      "prompt": "The **Explorer** role is yours. 🗺️",
      "continue": { "after": "pause", "pause": 2 }
    },
    {
      "type": "action_block",
      "action_kind": "give_achievement",
      "action_config": { "xp_role_id": 2004, "fire_scope": "respondent" },
      "precondition": "NOT((q8=\"Social\"))",
      "prompt": "The **Social** role is yours. 💬",
      "continue": { "after": "pause", "pause": 2 }
    }
  ]
}

Using the data

Segment distribution over time

Export the Responses tab to CSV. The four bucket score columns (score_competitor, score_creator, score_explorer, score_social) are included. The argmax result is available as the q8 column (the calculated field’s stored value).

Filter by join_date to see whether your server’s composition is shifting: for example, whether a content creator recruitment campaign actually brought in more Creators.

Cross-tabulation with engagement

Join the segmentation export with your engagement data (XP totals, message frequency, event attendance) on Discord handle. Research questions:

• Do Competitors retain longer than Socials?
• Are Creators the primary source of content but a minority of the member base?
• Do Explorers engage with deep-dive content at a higher rate than their population share?

Targeted event invites

Because segment membership is stored as a Discord role, you can @Creator or @Explorer when announcing events relevant to that segment, without manually curating lists.

Borderline members

Members whose top two bucket scores are within 2-3 points of each other are behaviorally mixed. In the raw export, you can identify these by comparing score_competitor against score_creator etc. You might communicate to them differently (e.g., highlight events that straddle two segments).

Variations

Add a secondary segment

Instead of assigning a single role, assign two: the primary and the closest runner-up. Compute the runner-up with a second calculated field:

"calculated_formula": "argmax([score_creator],[score_explorer],[score_social])"

… where the argmax arguments deliberately exclude the primary segment bucket. The result is the dominant secondary segment. Use skip logic to grant a second, secondary role.

Resurface segment in later surveys

Once a member has been segmented, their segment is stored as an achievement on their profile. Later surveys can reference it by piping the result of a lookup question, or simply by designing surveys that are sent to a specific @Role Discord mention.

Longitudinal re-segmentation

Run the same survey again after 6 months (use a new project, not a retake). Join both exports on Discord handle to see which members drifted between segments. Segment drift is an early signal of engagement trajectory.

When this recipe doesn’t fit

• You want self-reported segments: if members should explicitly choose their identity (e.g., “I’m a developer / designer / manager”), use a plain single_punch question and give_achievement blocks per answer. Hidden scoring is for cases where the classification is behavioral, not declared.
• You want more than 4 segments: argmax supports any number of buckets, but cognitive coherence of segments degrades beyond 5-6. If you need more, consider hierarchical segmentation: a first survey splits into 2 broad groups, a second survey (separate project) splits each group into 3 sub-segments.
• You need statistically validated scales: this recipe produces behavioral segment assignments, not psychometrically validated construct scores. For validated scales (Big Five, engagement frameworks), design the item battery externally, then encode the validated weights into score_values. The scoring machinery handles any weight scheme you provide.

Related

• Hogwarts House Sorting Hat: same multi-bucket argmax pattern, community-entertainment framing
• Pre/post attitude assessment: longitudinal change measurement using two-wave scoring surveys
• Welcome quiz: self-reported onboarding without hidden scoring
• Scoring variables reference