Seasonality

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What it is

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How the measured factor is computed

1. Monthly unit sales are taken from the tenant’s own history. At least 6 observed months are needed, otherwise nothing is measured and the profile default applies.
2. The long-term growth trend is removed first, so a company that is simply growing does not read every recent month as “high season”.
3. For each calendar month, the detrended ratio is averaged across all years observed. sample_size is that number of years — a month seen in two Novembers has sample_size 2.
4. The twelve ratios are normalised so their average is exactly 1.0 (measured_raw). 1.6 means the month sells 60 % above an average month; 0.7 means 30 % below.
5. The raw value is damped toward 1.0 when history is thin: measured_applied = 1 + min(1, k × years) × (measured_raw − 1), with k from Procurement Config. One year of history therefore counts only partially; three or more years count fully.
6. confidence follows the years: high = 3 or more years, medium = 2, low = 1.
7. A manual override in Procurement Config wins over the measurement (factor_source = override); a value of 1.0 in the config means “no override”.

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How it gets data

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Fields

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Query it

{
  "method": "tools/call",
  "params": {
    "name": "data_query",
    "arguments": {
      "view_slug": "v_seasonality_effective",
      "filters": { "month": 12 },
      "select_fields": ["profile", "factor", "factor_source", "confidence"],
      "limit": 25
    }
  }
}