Search analytics

Turn search behaviour into a useful operating queue.

ParticleSearch shows what shoppers searched, where they refined or left, which product data needs attention, and what changed after a merchant reviewed it.

The evidence loop

A signal becomes useful when it leads somewhere.

The dashboard is organized around the movement from observed behaviour to an action you can review later.

Signal

Observe

Evidence

Explain

Priority

Choose

Change

Act

Outcome

Learn

The merchant answer

Analytics are valuable when they lead to a decision. The dashboard connects search activity to health checks, product readiness, query evidence, fixes, and revenue context so your team can decide what to investigate next.

Guides and field notes

Go deeper when the decision needs detail.

These articles stay in the blog and search index, but they work like practical guides: context, merchant decisions, and acceptance tests for the capability you are evaluating.

Analytics dashboard guide

Move from a signal to a reviewable merchant decision.

Metrics guide

Understand what each metric means and cannot prove.

Revenue attribution guide

Connect search journeys to order evidence responsibly.

Catalog health guide

Check operational trust before comparing search behaviour over time.

The path

Move from signal to a decision your team can defend.

Analytics should shorten the distance between an observed problem and the next useful investigation, not add another report to interpret.

See the shape of demand

Start with search activity, result engagement, zero-result patterns, refinements, exits, and the products shoppers interact with.

Separate symptoms from causes

Use catalog health, product readiness, sync review, and query evidence to understand whether a problem is language, data, visibility, or behaviour.

Measure the next change

After a correction, return to the same query and outcome signals. Revenue attribution adds context, with evidence boundaries kept visible.

Decision guide

Questions this capability should answer

Use these questions to decide whether this capability is the right next move for your store.

Which signal deserves attention first?

Start with the query, product, or storefront health issue that has enough evidence to justify a focused review.

Is this a data problem or a behaviour problem?

Compare query evidence with catalog health and product readiness before changing ranking or adding a rule.

What does attributed revenue actually prove?

It shows an observed search touchpoint in a purchase path. Read it as context, not as a causal lift claim.

What is included

One view from shopper signal to merchant action

You do not need another dashboard full of unexplained totals. Each surface exists to answer a question your team can act on.

Built around a merchant decision

Search activity and engagement

Review query volume, result interaction, product engagement, refinements, and exits to understand where intent continues or breaks.

Storefront and catalog health

Keep storefront status, catalog coverage, and delivery health visible when search behaviour needs an operational explanation.

Product readiness and fix review

Find records and query patterns that deserve attention, with evidence and a next action rather than an unexplained score.

Query and product analytics

Move from an aggregate trend to the exact query, product, or collection that needs a closer look.

Revenue context

Connect search touchpoints to captured checkout outcomes when available. Treat attributed revenue as evidence of a path, not a causal lift claim.

Before and after review

Keep the original query and the change together so a merchant can tell whether the repair improved the intended behaviour.

A useful boundary

Good product decisions include what the feature cannot solve.

ParticleSearch gives your team more evidence and control. It does not remove the need for accurate product data, a clear merchandising goal, or a review of the result on your own store.

Analytics describe observed store activity. They do not explain intent by themselves. A high-volume query still needs a merchant review.
Attribution depends on the available storefront and checkout signals. It should be read with the evidence and confidence context shown in the dashboard.
Prioritization helps a team choose where to start. It does not replace a controlled test or product knowledge.

Keep exploring

See how this fits with the rest of the product.

All capabilities

Search quality

Understand what can make a result fail.

Merchant controls

Turn a signal into a reviewable change.

Recommendations

Measure discovery after the first result.

See it on your store

Give your team a clearer way to improve search.

Start with the storefront experience, then use the merchant workflow to understand what deserves attention next.

Start free trial How it works