Pricing Rules

Pricing rules are what turn store activity into actionable recommendations. They allow you to define the conditions under which a product should be considered for a price rise, a price reduction or a sale.

Rules are built around the signals tracked by Pricing Analyser, such as sales, interest, conversion, trending and stock level. Each rule checks one signal against a condition, then recommends a pricing action when that condition is met. In practical terms, a rule says:

“If this signal meets this condition, recommend this pricing action for these products.”

e.g.

“If the Trending signal is greater than +5, increase the price by 10% across the Dining Tables category”.

Where to find Pricing Rules

Go to WooCommerce → Analytics → Pricing Analyser and open the Pricing Rules section.

This is where you can create, edit, enable, disable, export and import rules.

How a rule works

Each rule has four main parts:

  • a name
  • a condition
  • an action
  • a scope

Rule condition

The condition defines when the rule should match.

A condition includes:

  • the signal to evaluate
  • the operator, such as greater than, less than or equal to
  • the threshold value

For example:

  • If Sales (7d) is greater than 20
  • If Conversion Rate (%) is less than 5
  • If Trending is greater than 4
  • If Stock level is greater than 30

The available signals are described in detail in the Signals Reference section.

Rule action

The action defines what Pricing Analyser should recommend when the condition is met.

Available action types include:

  • raise the price
  • lower the price
  • create or apply a sale when reducing the price

Actions can be based on:

  • a percentage change
  • a fixed amount
  • an absolute target price, where supported

For example:

  • raise the price by 5%
  • lower the price by £2
  • reduce the price by 10% and apply it as a sale price

Rule scope

The scope determines which products the rule applies to.

A rule can be limited to:

  • all products
  • selected categories
  • selected products

This lets you create broad catalogue rules or highly targeted rules for a specific area of the store.

Cooldowns

Rules can include a cooldown period. This prevents the same rule from repeatedly recommending changes for the same product immediately after a price has already been adjusted.

Cooldowns are useful because they:

  • reduce repeated noise in the dashboard
  • give a price change time to take effect
  • make recommendations easier to review

Once a rule enters cooldown for a product, that rule will not trigger further recommendations for the same product until the cooldown period has passed.

Rounding

Rules can use store-wide or rule-specific rounding behaviour so that recommended prices look commercially sensible.

Depending on your settings, Pricing Analyser can round prices using:

  • fractional endings such as .99
  • whole-unit steps
  • no rounding

This helps produce cleaner suggested prices without having to edit every recommendation manually.

Sale-based reductions

When lowering a price, you can choose whether the reduction should be applied as a normal price change or as a sale price.

This is useful when you want a recommendation to create a promotional reduction rather than permanently change the regular price.

Where relevant, Pricing Analyser indicates on the dashboard when a recommendation would apply a sale price.

How matched rules become recommendations

When a product matches a rule, Pricing Analyser calculates the suggested new price and checks whether the recommendation is valid within the current pricing context.

This includes factors such as:

  • floor and ceiling boundaries
  • rounding settings
  • cooldowns
  • whether the product is already on sale, where relevant

A recommendation may be discarded if it would breach floor or ceiling boundaries, a current cooldown, or not create an actual price change after rounding is taken into account.

If more than one rule matches a product, Pricing Analyser highlights the strongest matched recommendation while still allowing you to inspect the other matched rules (by clicking on the coloured recommendation chip).

Example rules

Here are some typical examples of how rules can be used:

  • raise the price when recent sales are unusually strong
  • reduce the price when conversion rate is weak
  • raise the price when stock is low
  • reduce the price when a product is overstocked
  • create a sale when a product is underperforming

The best rules are usually simple, easy to understand and clearly tied to a commercial objective.

Best practice

When starting out, it is usually better to create a small number of rules and refine them over time rather than trying to cover every possible case immediately.

A good starting approach is:

  1. begin with two or three simple rules
  2. review the recommendations they generate
  3. check the supporting charts and explanation panels
  4. adjust thresholds if needed
  5. add more rules only once the first set is behaving as expected

Next step

Next, see the Signals Reference to understand the data available when building rules.

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