> ## Documentation Index
> Fetch the complete documentation index at: https://docs.ocular.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Search Term

> What users actually typed when your ad showed — for negative-keyword discovery, match-type optimization, and budget-waste elimination.

The actual queries users typed when your ad triggered — the gap between what you bid on (keywords) and what they searched (search terms).

## What this data model represents

**Grain:** one row per `date × ad_account × campaign × adset × search_term`.

**Metrics, grouped by category** — every number you can compute on this data model. Expand below for examples in each.

```mermaid theme={null}
flowchart LR
    R1["Spend & revenue"]:::cat --- S
    R2["Clicks & impressions"]:::cat --- S

    S(["Metrics"]):::root

    S --- R3["Cost efficiency"]:::cat
    S --- R4[Conversion]:::cat

    classDef root fill:#0f172a,color:#f8fafc,stroke:#0f172a,stroke-width:2px
    classDef cat fill:#2563eb,color:#fff,stroke:#1d4ed8,stroke-width:1.5px
```

<Accordion title="Show sample metrics in each category">
  ```mermaid theme={null}
  flowchart LR
    sr1[Ad Spend]:::leaf --- SR["Spend & revenue"]
    sr2[Conversion Value]:::leaf --- SR
    sr3[ROAS]:::leaf --- SR
    sr4[Conversions]:::leaf --- SR

    ci1[Clicks]:::leaf --- CI["Clicks & impressions"]
    ci2[Impressions]:::leaf --- CI
    ci3[CTR]:::leaf --- CI

    SR:::cat --- S
    CI:::cat --- S

    S(["Metrics"]):::root

    S --- CE["Cost efficiency"]:::cat
    S --- Cv[Conversion]:::cat

    CE --- ce1[CPC]:::leaf
    CE --- ce2[CPM]:::leaf
    CE --- ce3[CPA]:::leaf
    CE --- ce4[RPC]:::leaf

    Cv --- cv1[Conversion Rate]:::leaf

    classDef root fill:#0f172a,color:#f8fafc,stroke:#0f172a,stroke-width:2px
    classDef cat fill:#2563eb,color:#fff,stroke:#1d4ed8,stroke-width:1.5px
    classDef leaf fill:#eff6ff,color:#1e3a8a,stroke:#bfdbfe,stroke-width:1px
  ```
</Accordion>

**Dimensions, grouped by category** — every way you can split, filter, or group those metrics. Expand below for examples in each.

```mermaid theme={null}
flowchart LR
    D1["Search term"]:::cat --- M
    D2["Campaign hierarchy"]:::cat --- M

    M(["Dimensions"]):::root

    M --- D3[Time]:::cat
    M --- D4["Account & brand"]:::cat
    M --- D5["Creative & platform"]:::cat

    classDef root fill:#0f172a,color:#f8fafc,stroke:#0f172a,stroke-width:2px
    classDef cat fill:#9333ea,color:#fff,stroke:#7e22ce,stroke-width:1.5px
```

<Accordion title="Show sample dimensions in each category">
  ```mermaid theme={null}
  flowchart LR
    st1[search_term]:::leaf --- ST["Search term"]
    st2[search_term_status]:::leaf --- ST
    st3[match_type]:::leaf --- ST

    ch1[campaign_id]:::leaf --- CH["Campaign hierarchy"]
    ch2[adset_id]:::leaf --- CH
    ch3[campaign_type]:::leaf --- CH

    ST:::cat --- M
    CH:::cat --- M

    M(["Dimensions"]):::root

    M --- Ti[Time]:::cat
    M --- AB["Account & brand"]:::cat
    M --- CP["Creative & platform"]:::cat

    Ti --- t1[date]:::leaf
    Ti --- t2[week_start_date]:::leaf

    AB --- ab1[ad_account_id]:::leaf
    AB --- ab2[brand]:::leaf

    CP --- cp1[ad_platform]:::leaf
    CP --- cp2[final_url]:::leaf

    classDef root fill:#0f172a,color:#f8fafc,stroke:#0f172a,stroke-width:2px
    classDef cat fill:#9333ea,color:#fff,stroke:#7e22ce,stroke-width:1.5px
    classDef leaf fill:#faf5ff,color:#581c87,stroke:#e9d5ff,stroke-width:1px
  ```
</Accordion>

**Source:** Google Ads API, daily refresh.

<Warning>
  Primarily available for **Search and Shopping** campaigns. Limited in Performance Max; **not available** for Display, Video, or App campaigns. Very low-volume queries may roll up as `(other)`.
</Warning>

## Slice by

Unique to this data model:

| Dimension            | Type   | Values                                             |
| -------------------- | ------ | -------------------------------------------------- |
| `search_term`        | String | The actual query typed by the user                 |
| `search_term_status` | String | `Added as keyword`, `None`, `Excluded`, `Negative` |
| `match_type`         | String | `Exact`, `Phrase`, `Broad`                         |

Plus the standard campaign hierarchy, time, and account dimensions — documented once on the [Google Ads Overview](/data-models/google-ads/overview).

## Use it to answer

* Which terms burn budget with zero conversions — candidates for the negative-keyword list?
* Which terms convert well but aren't yet exact-match keywords — promote them?
* Are broader match types pulling in irrelevant queries — tighten or loosen?
* Are competitor brand names appearing — conquest opportunity or wasted spend?

<Tip>
  **Statistical significance by click volume:** under 10 = monitor only; 10–50 = consider as negative; 50–100 = sufficient to decide; 100+ = act with confidence.
</Tip>

## Available metrics

Everything you can compute on this data model. Need a metric not listed? See the [Google Ads metric availability matrix](/data-models/google-ads/overview#metric-availability-matrix).

| Metric                   | Formula                             |
| ------------------------ | ----------------------------------- |
| **Spend & revenue**      |                                     |
| Ad Spend                 | Sum of daily spend                  |
| Conversion Value         | Sum of reported revenue             |
| ROAS                     | Conversion Value ÷ Ad Spend         |
| Conversions              | Sum of attributed conversion events |
| **Clicks & impressions** |                                     |
| Clicks                   | Sum of clicks                       |
| Impressions              | Sum of impressions                  |
| CTR                      | Clicks ÷ Impressions × 100          |
| **Cost efficiency**      |                                     |
| CPC                      | Ad Spend ÷ Clicks                   |
| CPM                      | Ad Spend ÷ Impressions × 1,000      |
| CPA                      | Ad Spend ÷ Conversions              |
| RPC                      | Conversion Value ÷ Clicks           |
| **Conversion**           |                                     |
| Conversion Rate          | Conversions ÷ Clicks × 100          |

<Accordion title="Raw fields (for custom calculations)">
  `ad_spend` · `conversion_value` · `conversions` · `clicks` · `impressions`
</Accordion>