# Customer Followups — Category Frequencies + Date by Category Pivot

> Customer Followups — Category Frequencies + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-31).

Analyzes customer followup records to produce two reports: category frequencies by team group and a date-by-category pivot table for completed or due followups.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-operations-19-110?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-31
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/customer-followups-category-frequencies-date-by-category-pivot-a0546b7d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_7NOyFa3xt_wWnSMMcyeaI

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability customer-followups-category-frequencies-date-by-category-pivot-a0546b7d -d '<json body>'
```

Example prompt: Can you analyze these customer followup records for my team — I have up to 50 rows with row IDs, team groups, dates, and completed_followups counts — and give me both a category frequency breakdown by team group and a date-by-category pivot table for completed_followups?

## When to prefer this

Choose this endpoint when you have up to 200 customer followup records with team group and date dimensions and need both a category frequency summary and a date-by-category pivot in a single low-cost call ($0.01 USDC). It is ideal when data privacy matters since computation is local with no external lookup. Prefer it over general BI tools when you need a lightweight, pay-per-use analytical call that returns structured tabular reports without requiring a persistent data warehouse connection.

## Known failure modes

- Rows exceeding 200 items will be rejected — the endpoint enforces a maxItems:200 constraint
- Missing required fields (row_id, team_group, date, completed_followups, due_followups) will cause validation errors
- Date values not matching YYYY-MM-DD format will fail schema pattern validation
- Numeric values outside ±1,000,000,000,000 will be rejected
- An empty rows array (minItems:1) will fail validation
- Invalid field enum value (must be 'completed_followups' or 'due_followups') will cause errors
- Payment failure or insufficient USDC balance will block the request

## How this service works

Customer followups — Category frequencies + Date by category pivot: Category frequencies + Date by category pivot for supplied customer followups records (completed_followups, due_followups). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.

## Output

Returns two analytical reports: (1) a category frequencies table showing how often each team_group appears across the supplied rows, and (2) a date-by-category pivot table cross-tabulating the selected metric (completed_followups or due_followups) by date and team_group. Both reports are computed locally from the supplied data with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "team_group",
     "date",
     "completed_followups",
     "due_followups"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "team_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "due_followups": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "completed_followups": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "team_group": "group-a",
     "due_followups": 1,
     "completed_followups": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "team_group": "group-b",
     "due_followups": 2,
     "completed_followups": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "team_group": "group-a",
     "due_followups": 3,
     "completed_followups": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "team_group": "group-b",
     "due_followups": 4,
     "completed_followups": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "completed_followups",
    "due_followups"
   ],
   "type": "string",
   "default": "completed_followups"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/customer-followups-category-frequencies-date-by-category-pivot-a0546b7d/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)