# Customer Followups — String Normalisation + Date by Category Pivot

> Customer Followups — String Normalisation + 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 2026-11-02).

Runs two local analytical reports (string normalisation and date-by-category pivot) on up to 200 rows of customer followup data (completed_followups, due_followups) for $0.01 USDC.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-operations-19-035?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/customer-followups-string-normalisation-date-by-category-pivot-90fb8e31
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_YrzKRz_OxmhODbQ1BQTyy

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-string-normalisation-date-by-category-pivot-90fb8e31 -d '<json body>'
```

Example prompt: Can you run string normalisation and a date-by-category pivot on these customer followup records for my team groups? I have up to 50 rows with completed_followups and due_followups values — use the completed_followups field for the pivot.

## When to prefer this

Choose this endpoint when you need two lightweight analytical transformations — string normalisation and a date-by-category pivot — on a batch of customer followup records (up to 200 rows) in a single cheap call ($0.01 USDC). Ideal when you already have the data in hand and need local computation rather than live CRM lookups or predictions. Best suited for CRM operations, sales team reporting, or followup tracking dashboards where you want clean labels and a grouped date pivot without standing up your own analytics pipeline.

## Known failure modes

- Exceeds 200-row limit — request rejected
- Missing required fields (row_id, team_group, date, completed_followups, due_followups) — validation error
- Invalid date format (must match YYYY-MM-DD) — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — rejected
- Empty rows array — minimum 1 item required
- Invalid field enum value — must be 'completed_followups' or 'due_followups'

## How this service works

Customer followups — String normalisation + Date by category pivot: String normalisation + 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 independent analytical reports: (1) a string normalisation report cleaning team_group and other text fields, and (2) a date-by-category pivot table aggregating the selected followup metric (completed_followups or due_followups) across team groups and dates — all computed locally on 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-string-normalisation-date-by-category-pivot-90fb8e31/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)