Week over Week (WoW)

YAML type: wow | Category: Periodic

Compares the current week aggregate to the previous week.

Description

WoW rolls daily values into weeks (sum or average) and compares consecutive weeks.

How it works

Week over Week (WoW) illustration

Week over Week first rolls daily values into a week using aggregateMode (sum or average), then compares the current week to the previous week.

If the percentual change exceeds the threshold in the allowed direction, a WoW anomaly is created. Data Preview can show the aggregated weekly series so you see the same grain the detector uses.

Setup

Choose aggregateMode to match how the business reads weekly KPIs.

Configure detectors on the data view Analysis tab or in YAML. Validate with Data Preview before enabling production schedules.

Settings

Parameter	Default	Description
`percentualChange`	`50`	Minimum absolute % change
`mode`	`both`	Direction -- see Allowed values
`aggregateMode`	`sum`	Period aggregation -- see Allowed values

Allowed values

`mode`

Value	Meaning
`above`	Flag increases / values above the comparison (or high side of a band)
`below`	Flag decreases / values below the comparison (or low side of a band)
`both`	Flag either direction

`aggregateMode`

Used when the detector compares period totals (week / month / quarter), not raw daily points.

Value	Meaning
`sum`	Compare sums of daily values in the period (default)
`average`	Compare averages of daily values in the period

Shared series filters

Most detectors also accept optional series filters in params:

Parameter	Purpose
`maxGapAmount`	Skip series when gap amount is too high (`null` = no limit). Catalog create-default is often `5`.
`minValue`	Skip series whose average value is below this (`null` = no limit). Catalog create-default is often `1000`.
`maxValue`	Skip series whose average value is above this (optional; omit/`null` = no limit)
`useSpecialDates`	When `true`, suppress anomalies that overlap special dates

When a filter skips a series, Data Preview shows the reason.

Configuration example

analysis:
  detectors:
    - type: wow
      params:
        percentualChange: 40.0
        mode: both
        aggregateMode: sum

Using the detector

Data Preview shows aggregated weekly series for these detectors when applicable.

Use cases

Weekly revenue and orders
Support ticket volumes
Campaign week comparisons

Specifics

YoY week: wpy.