Search Query Trends

Learn how to interpret rising, falling, and lost search queries using comparable periods, demand, ranking, CTR, intent, and page-level evidence.

Screpy combines three query-comparison views:

Rising Queries shows searches gaining performance between equal periods.
Falling Queries shows searches losing performance between equal periods.
Lost Queries shows searches present in the historical period but absent from the current period.

Together they explain how the market and the site's search footprint are changing. A query trend can come from demand, ranking, CTR, page selection, result features, technical changes, or normal data variation.

Read current, previous, and change values

For rising and falling queries, compare current and previous clicks, impressions, CTR, and position. Lost Queries shows the historical metrics for queries that no longer appear in the current result set.

Change pattern	First hypotheses to test
Impressions up, position stable	Demand may be growing
Impressions up, position improves	Demand and visibility may both be contributing
Clicks down, impressions stable	CTR, position distribution, or result layout may have changed
Impressions down, position stable	Demand, seasonality, or query coverage may have fallen
Position down, impressions and clicks down	Ranking or relevance loss is plausible
Query disappears	Visibility may be lost, demand may be tiny, or data may be below the reporting threshold

These are hypotheses, not automatic diagnoses.

Make periods comparable

Use equal-length, adjacent periods for short-term change. Use year-over-year comparisons for seasonal businesses, holidays, recurring events, and annual topics. Avoid comparing a launch week with a normal month and interpreting the difference as an SEO trend.

The shorter the range and smaller the query, the more random variation matters. Increase the period or aggregate related queries when the signal is unstable.

Analyze rising queries

Determine whether impressions, position, CTR, or all three drove the gain.
Identify the page receiving the growth.
Confirm that the query fits the page and the business.
Protect what is working before editing the page.
Expand only when the adjacent user need is supported by data.

Rising visibility can expose a new content cluster, but it can also be temporary news or seasonal demand. Do not rewrite a stable high-performing page merely because growth appears.

Analyze falling queries

Find the date and shape of the decline.
Compare related queries to separate one-term movement from topic-level decline.
Check whether the ranking URL changed.
Review technical releases, indexing, canonicals, redirects, and internal links.
Compare current result intent and competitors.
Decide whether the issue is demand, ranking, CTR, page selection, or reporting noise.

Google's traffic-drop debugging guide provides a useful framework for distinguishing technical, algorithmic, seasonal, security, and reporting causes.

Analyze lost queries carefully

A lost query is absent from the current data set, not necessarily removed from the index. Low-volume queries can move in and out of reported data. Check the historical impression volume, related queries, intended page, and a longer current range before escalating.

Prioritize lost queries that previously produced meaningful qualified clicks, belonged to a valuable topic cluster, and disappeared alongside page-level or technical evidence.

Example

Clicks for “technical SEO checklist” fall 35%. Impressions remain stable, average position changes from 5.2 to 5.5, and CTR declines. This pattern does not strongly support a ranking-loss diagnosis. Review the live result layout, title and snippet, device segments, and competitor presentation before rewriting the whole article.

If impressions and position had both deteriorated after a site migration, technical and relevance checks would move ahead of snippet work.

Turn trends into a content strategy

Group query changes by topic and page. Several rising queries around one problem may justify expanding a hub or creating a dedicated resource. Several falling queries across one template may indicate a systemic change. One isolated query usually deserves less confidence than a consistent cluster.

Verify actions

Annotate releases and content changes. Compare the same metrics over the same period length. Confirm that gains occur on the intended page and do not come from brand traffic or unrelated query expansion. Evaluate qualified clicks and business outcomes alongside search metrics.