Unit Economics: Track Cost Per Business Metric

Unit Economics

Unit economics lets you answer questions like “How much does it cost to serve one customer?” or “What’s our cost per API call this month?” Instead of looking at raw cloud spend, you track cost relative to business output.

Why Unit Economics

Raw cloud cost going up isn’t necessarily bad — it might mean your business is growing. What matters is whether your cost per unit is stable, improving, or degrading.

Scenario	Raw Cost	Customers	Cost/Customer	Verdict
January	$8,000	200	$40	Baseline
February	$12,000	350	$34	Improving
March	$15,000	360	$42	Degrading

In this example, March’s cost increase is a real problem — you’re spending more per customer. February’s increase was healthy growth.

Supported Metric Types

Type	Description	Example
api_calls	API request volume	2.4M calls/day
transactions	Business transactions	50K orders/day
customers	Active customer count	1,200 active
requests	HTTP requests served	10M requests/day
custom	Any numeric metric	Deployments, builds, etc.

How It Works

1. You send unit data — Push your business metrics to Xplorr via API (daily values).
2. Xplorr matches with cost — Each day’s unit count is joined with that day’s total cloud cost.
3. Cost per unit is calculated — daily_cost / unit_count = cost_per_unit.
4. Trends are tracked — Xplorr compares the first half vs. second half of any period to detect whether cost-per-unit is increasing, decreasing, or stable.

Ingesting Metrics

Push unit data via the REST API. You’ll typically run this from a cron job, CI pipeline, or data pipeline.

# Push today's customer count
curl -X POST "https://api.xplorr.io/api/v1/unit-economics/metrics" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Active Customers",
    "metric_type": "customers",
    "value": 1247,
    "date": "2026-03-21"
  }'

// Node.js example — push daily from a scheduled job
const response = await fetch('https://api.xplorr.io/api/v1/unit-economics/metrics', {
  method: 'POST',
  headers: {
    'Authorization': `Bearer ${process.env.XPLORR_TOKEN}`,
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    name: 'API Calls',
    metric_type: 'api_calls',
    value: 2_400_000,
    date: new Date().toISOString().split('T')[0],
  }),
});

# Python example
import requests
from datetime import date

requests.post(
    "https://api.xplorr.io/api/v1/unit-economics/metrics",
    headers={"Authorization": f"Bearer {token}"},
    json={
        "name": "Transactions",
        "metric_type": "transactions",
        "value": 48500,
        "date": str(date.today()),
    },
)

Upsert behavior: If you push the same (name, date) combination twice, the second value replaces the first. This makes retries safe.

Rate limit: 30 requests per minute.

Querying Cost Per Unit

# Get cost per unit for the last 30 days
curl -H "Authorization: Bearer $TOKEN" \
  "https://api.xplorr.io/api/v1/unit-economics?metricName=Active%20Customers"

# Custom date range
curl -H "Authorization: Bearer $TOKEN" \
  "https://api.xplorr.io/api/v1/unit-economics?metricName=API%20Calls&startDate=2026-02-01&endDate=2026-03-01"

Response:

[
  {
    "date": "2026-03-20",
    "metric_name": "Active Customers",
    "metric_type": "customers",
    "unit_count": 1247,
    "daily_cost": 412.50,
    "cost_per_unit": 0.33,
    "currency": "USD"
  }
]

Trend Analysis

Check whether cost-per-unit is improving or degrading:

curl -H "Authorization: Bearer $TOKEN" \
  "https://api.xplorr.io/api/v1/unit-economics/trend?metricName=Active%20Customers&period=30"

Response:

{
  "trend": {
    "direction": "decreasing",
    "percentChange": -8.2,
    "avgCostPerUnit": 0.31
  }
}

Direction	Meaning
decreasing	Cost per unit is improving (good)
increasing	Cost per unit is degrading (investigate)
insufficient_data	Not enough data points to determine trend

The trend compares the average cost-per-unit in the first half of the period against the second half.

MCP & Slack Access

Unit economics data is also accessible via:

• MCP Server — Use the get_cost_summary tool and correlate with your own metrics.
• Slack Bot — Ask questions like “What’s my cost per customer this month?” (if you’ve ingested customer metrics).

Best Practices

• Push daily — Unit economics works best with daily granularity. A daily cron job is the simplest approach.
• Pick 2-3 metrics — Don’t track everything. Pick the metrics that matter most to your business: customers, API calls, or transactions.
• Automate ingestion — Pull from your application database, analytics platform, or Stripe/billing system. Don’t rely on manual entry.
• Review weekly — Check the trend endpoint weekly. A gradual increase in cost-per-unit is easy to miss if you only look at raw spend.
• Correlate with anomalies — If cost-per-unit spikes, check the anomaly detection page to see if a specific service is the cause.