Signals are the measurements used by Pricing Analyser to decide whether a rule should match. Each rule tests one signal against a condition such as greater than, less than or equal to a specified value.

Signals are based on product performance data already available within the store, including sales, interest, conversion, trend and stock level.

This page explains what each signal means and how it is intended to be used.

Sales (24h)

Sales (24h) measures units sold over a rolling 24-hour window.

Unlike the other sales signals, this is not tied to complete calendar days. It is designed to surface very recent movement and is the most responsive sales signal available in Pricing Analyser.

This signal is best used when you want to react quickly to a sudden burst of demand.

Typical uses include:

• raising prices when very recent sales are unusually strong
• spotting sudden short-term surges
• reacting more quickly than a calendar-day sales signal would allow

Sales (Yesterday)

Sales (Yesterday) measures units sold during the previous complete day.

This signal is simple and easy to reason about because it uses a full calendar day rather than a rolling window. It can be useful where a merchant wants explicit control over what counts as a meaningful one-day sales level.

Typical uses include:

• raising prices when yesterday’s sales were unusually strong
• reducing prices when yesterday’s sales were very weak
• building simple one-day rules without using rolling 24-hour logic

Sales (7d)

Sales (7d) measures total units sold over the last 7 complete days.

This is often a useful short-term sales signal because it smooths out the noise of a single day while still reacting to recent change.

Typical uses include:

• identifying products with strong recent demand
• identifying products with weak recent demand
• supporting simple price rise or reduction rules

Sales (30/60d)

Sales (30/60d) measures total units sold over the active sales history window.

The exact period depends on the store’s configured history window:

• 30 days if the history window is set to 30 days
• 60 days if the history window is set to 60 days

This is the broadest sales signal in Pricing Analyser and is useful when you want rules based on more established product performance rather than short-term movement.

Typical uses include:

• identifying slow long-term sellers
• identifying products with consistently strong demand
• supporting slower-moving pricing decisions

Conversion Rate (%)

Conversion Rate (%) measures the relationship between sales and interest. In practical terms, it shows how effectively product interest is turning into purchases.

Interest reflects product view activity. It is a measure of attention rather than demand. A high Interest value means a product is attracting views, but that does not necessarily mean it is converting into sales.

A low conversion rate may suggest that a product is attracting views but failing to convert strongly. A high conversion rate may suggest that the current price and offer are working well.

This signal is typically most useful when read alongside Interest and Sales rather than in isolation.

Typical uses include:

• reducing prices on products with weak conversion
• raising prices where conversion remains strong
• identifying products that may be drawing attention but not commitment

Trending

Trending is a score from -9 to +9 that compares the average daily sales of the last complete 7 days with the average daily sales of the earlier part of the available 14 to 60 day sales window.

A positive score means recent sales are stronger than the earlier baseline. A negative score means recent sales are weaker than the earlier baseline. A score near zero means recent sales are broadly in line with the earlier pattern.

This signal is intended to provide a clear directional view of recent sales movement rather than a raw volume measurement.

Typical uses include:

• raising prices on products that have recently strengthened
• reducing prices on products that have recently weakened
• spotting changes in momentum that may not be obvious from total sales alone

Stock Level

Stock Level measures the currently available stock quantity for the product or variation being evaluated.

For products that manage stock at variation level, Pricing Analyser can treat each variation separately. For products using product-level stock management, the product-level stock value is used.

This signal is often useful in conjunction with boundary pricing and margin protection.

Typical uses include:

• raising prices when stock is low
• reducing prices when stock is high
• creating sale-price reductions for overstocked items

Where supported in the rule builder, stock can also be evaluated relative to the product’s low stock threshold.

Choosing the right signal

Different signals are suited to different pricing objectives.

As a rough guide:

• use Sales (24h) or Sales (Yesterday) for very recent sales behaviour
• use Sales (7d) for short-term performance
• use Sales (30/60d) for broader sales behaviour
• use Conversion Rate to assess sales efficiency
• use Trending to capture recent direction of movement
• use Stock Level when stock position should influence pricing

Using signals well

In practice, signals are most useful when combined sensibly through separate rules rather than overcomplicated logic in a single rule.

For example, a merchant might use:

• a trend rule to identify products strengthening in demand
• a conversion rule to spot hesitation
• a stock rule to protect margin when availability is limited

The strongest Pricing Analyser setups usually come from a small number of clear rules built around signals that are easy to interpret.

Next step

Next, see the Settings guide to understand how store-wide options affect the way these signals are used and displayed.