Read your search demand by intent.

Search Console tells you what people search, never why. We classify every query — Informational, Commercial, Navigational, Transactional — with an LLM in your own warehouse, then report clicks, impressions, and CTR by intent instead of one row at a time.

Classified by
LLM, in your warehouse
Lives in
Your own BigQuery
Source
Search Console

Every query reads the same in Search Console

A Search Console row is just a phrase with clicks and impressions. It can’t tell you whether the person was learning, comparing options, looking for you by name, or ready to buy — so demand that converts sits in the same list as demand that only researches, weighted identically.

Sort by clicks and the informational queries — the ones with the most volume — dominate the top, while the smaller commercial and transactional searches that actually drive revenue stay buried. Without the why, the report flatters the wrong queries.

Classified by intent, joined to your numbers

Not a manual tagging pass you redo each quarter — an LLM labels every query where your data already lives, so the four intents read as cleanly as the head terms.

  1. Step 1

    An LLM labels every query

    Each query Search Console reports is read by an LLM and assigned one of four intents — Informational, Commercial, Navigational, or Transactional — inside your own BigQuery. Phrasing and context decide the label, not a brittle keyword rule.

  2. Step 2

    Joined to your performance

    The intent sits next to the raw clicks, impressions, CTR, and position for every query — past the 1,000-row cap — so each metric carries the intent behind it. The mapping is yours, and fully reviewable.

  3. Step 3

    Reported by intent

    Performance rolls up by intent across the reporting you already get — which intents earn the impressions, which earn the clicks, and where the CTR gap sits — with no pivoting by hand.

Performance, split four ways

Each period your queries collect into four intents — and the clicks, impressions, and CTR for each tell you which demand is research and which is ready to act.

Performance by intent last 28 days
  • Informational 58% of queries
    Clicks
    4,210
    Impressions
    182,400
    CTR
    2.3%
  • Commercial 22% of queries
    Clicks
    1,980
    Impressions
    38,600
    CTR
    5.1%
  • Navigational 12% of queries
    Clicks
    3,140
    Impressions
    9,800
    CTR
    32.0%
  • Transactional 8% of queries
    Clicks
    1,260
    Impressions
    14,200
    CTR
    8.9%

Example rollup. Your intents are classified by an LLM against your own Search Console queries.

What reading by intent changes

Because the intent lives in your data layer, the split shows up everywhere your numbers do.

  1. See the intent behind your impressions

    A high-impression, low-CTR query looks like a problem until you see it’s people learning, not buying. Reading clicks and CTR by intent tells you which demand is research and which is ready to act.

  2. Catch intent mismatches

    When commercial or transactional queries land on a page written to inform, CTR sags and the visit bounces. Performance per intent makes the mismatch obvious, so you can point the right page at the right intent.

  3. Find the gaps that convert

    If commercial and transactional intent is only a thin slice of your queries, the demand that turns into revenue is under-served. Sizing each intent shows where a new page is worth writing.

  4. Classification you can see and tune

    The LLM’s labels live in your own BigQuery next to the raw metrics — so you can review them, adjust the edge cases, and trust what rolls up. Not a black box inside someone else’s dashboard.

More search data than the Search Console interface shows you

Every solution here runs on the same foundation: the full Search Console API, kept in your own warehouse — far more rows than the interface returns, and history that never expires.

API access
50× more data than GSC

Up to 50× more data than GSC

Insightlytics taps into Google Search Console’s API to give you 50× more search data than GSC’s interface — 50,000 rows per query instead of 1,000. Get the complete picture of your site’s search performance, not just the tip of the iceberg.

GSC interface
1,000 rows
With Insightlytics
50,000 rows
Unlimited history
no 16-month limit

Extended historical Search Console data

Say goodbye to Google’s 16-month data limit. Insightlytics keeps an unlimited history of your Search Console data in your own warehouse — so you can identify long-term trends, measure algorithm impacts, and show clients real progress over time. Whether you’re tracking seasonal patterns or proving the value of your work, the historical depth is there when you need it, and crucial data never slips away.

Google
16 months
Insightlytics
Unlimited

The difference from doing it by hand

You can tag intent yourself in a spreadsheet — until the row cap, the hours, and the inconsistency catch up. Here’s what changes when an LLM classifies it in your warehouse instead.

Tagging every query
Hand-label ~1,000 rows, 2–4 hrs
An LLM labels every query
Coverage
The top rows you can export
Every query, no row cap
Consistency
Subjective, drifts per person
One model, one rubric
Ambiguous phrasing
Keyword rules guess wrong
Read in context by the LLM
Performance by intent
Re-pivot the export by hand
Joined into every report
Keeping it current
A manual pass each quarter
Re-classified automatically

Frequently asked questions

Still wondering about something? A discovery call clears it up fast.

Informational (learning something — “how to”, “what is”, guides), Commercial (comparing before deciding — “best”, “review”, “X vs Y”), Navigational (heading for a specific site or brand by name), and Transactional (ready to act — “buy”, “price”, “free trial”, “download”). Every query is sorted into one of the four.

See the intent behind every search.

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