TL;DR
This capability appends search volume, keyword difficulty (0-100 score), and intent classification (informational, navigational, commercial, transactional) to each keyword already stored in your platform, drawing on nqzai's own keyword index. Use it for content audits, paid search planning, SEO forecasting, competitive gap analysis, or seasonal campaign prep; skip it if you're only storing keywords for future reference with no immediate analytical need.
The “Enrich my keywords with metrics” capability takes a list of keywords you have already stored in your platform and appends three core data points to each term:
- Search volume – the average number of monthly queries the keyword receives in a defined geography.
- Keyword difficulty – a relative score that estimates how hard it would be to rank on the first page of results for that term.
- Search intent – a classification (informational, navigational, commercial, transactional) that reveals the likely goal behind a user’s query.
When you run the prompt “Get volume, difficulty and intent for all my stored keywords”, the system pulls the latest metrics from its indexed data store, matches each keyword to its corresponding values, and returns an enriched table or downloadable file ready for further analysis, content planning, or bid‑setting.
When to use it
Enriching keywords is most valuable in the following scenarios:
| Scenario | Why enrichment helps |
|---|---|
| Content audit | Knowing volume tells you which topics attract traffic; difficulty flags where you may need stronger authority; intent guides the format (guide vs. product page). |
| Paid search planning | Volume gives a sense of potential impressions; difficulty correlates with competitiveness; intent helps match ad copy to user goal. |
| SEO forecasting | Combining volume and difficulty can surface likely low‑hanging fruit for stakeholder reporting. |
| Competitive gap analysis | Comparing your stored keyword set against a competitor’s enriched list can reveal gaps in coverage and intent alignment. |
| Seasonal campaign prep | Intent classification helps ensure creative matches the buying cycle for time‑sensitive campaigns. |
If you are merely checking spelling or storing keywords for future reference without any immediate analytical need, enrichment adds little value and can be skipped.
Where does it run
Direct answer: The enrichment process runs as a hosted service inside the nqzai platform. Keyword metrics (volume, difficulty, and intent) are drawn from the platform’s own keyword and search-data index rather than requiring you to bring your own third‑party keyword tool. Usage is billed under nqzai’s standard pay‑as‑you‑go, per‑token pricing rather than a fixed subscription tier or compute quota.
How it works
Direct answer: Below is a step‑by‑step walkthrough of what happens when you issue the enrichment prompt.
1. Input validation
The platform first checks that the supplied list contains only valid keyword strings (reasonable length, no characters that would break downstream matching). Invalid entries are omitted, with a summary returned to the user.
2. Tokenization and normalization
Each keyword is tokenized into its constituent words, lower‑cased, and normalized so it can be matched consistently against the metric index.
3. Metric lookup
The platform looks up each normalized keyword against its indexed data for:
- Volume – average monthly searches for the keyword in the requested locale.
- Difficulty – a relative 0‑100 score reflecting how competitive the term appears to be.
- Intent – a classification into one of the four intent categories.
If an exact match isn’t available (for example, a newly coined term), the platform can fall back to an estimate based on similar keywords, and flags any such value as an estimate rather than an exact observation.
4. Intent classification
The system assigns the most likely intent class for each keyword. Where the signal is genuinely mixed (e.g., a term with both informational and commercial intent), the result is labeled “ambiguous” rather than forced into a single category.
5. Output assembly
The enriched dataset is assembled as a table or downloadable file, with columns such as:
keyword(original user input)volume(integer, monthly average)difficulty(0‑100)intent(enum)estimate_flag(boolean) – true if any metric was derived from a similarity‑based estimate rather than an exact match
A brief summary shows totals: number of exact matches, estimates, and ambiguous intents.
FAQ
Direct answer: Q: Does enrichment consume extra API credits beyond normal usage? A: Enrichment is billed the same way as other nqzai capabilities — under standard pay‑as‑you‑go, per‑token pricing. There’s no separate subscription tier or add‑on quota for this feature.
Q: How often is the underlying metric data updated? A: The keyword index is refreshed on an ongoing basis, though the exact cadence for any given locale or term can vary.
Q: Can I enrich keywords in languages other than English? A: The platform supports keyword enrichment for a range of locales; when you submit a list you can specify the target locale and the system will attempt to return volume, difficulty, and intent values for that market.
Q: What happens if a keyword has no data at all? A: The system flags it as “no data” and provides a suggestion to broaden the term or check spelling. It can also return a similarity‑based estimate, clearly marked as inferred rather than observed.
Q: Is there a limit to how many keywords I can enrich at once? A: There’s no fixed subscription‑tier cap on batch size. Practical limits are governed by your available token balance under nqzai’s pay‑as‑you‑go pricing rather than a plan‑based quota.
Q: How reliable are the difficulty scores? A: Difficulty is a relative metric intended to give a directional sense of ranking effort, not an absolute guarantee of ranking potential. Other factors — such as algorithm updates or niche‑specific authority — can cause a keyword to behave differently than its score suggests.
Q: Can I export the enriched data directly to my BI tool? A: The output can be downloaded as CSV or JSON and imported into whatever BI or spreadsheet tool you use. nqzai does not currently ship pre‑built, OAuth‑connected integrations into third‑party BI platforms or data warehouses.
Q: Are there any privacy concerns with storing my keyword list? A: Your keyword lists stay within your own nqzai workspace and are not used to train models shared across other tenants.
Takeaway
Direct answer: Enriching stored keywords with volume, difficulty, and intent turns a static list into a more actionable planning input. By drawing on the platform’s own keyword index, you get a quick read on search demand, relative ranking effort, and likely user intent without needing to bring in a separate third‑party tool. Use the output to prioritize content, inform bidding decisions, and spot competitive gaps — while keeping in mind that difficulty scores are directional and any estimate‑flagged values are inferred rather than directly observed.
Evidence, limits, and reproducible use
Direct answer: Reproducible workflow. Supply the exact site, property, date range, and comparison period. Review the source data, filters, and assumptions before using a finding to change content or reporting. Record the run date because search data is revised and delayed.
Limit. The output is diagnostic evidence, not a ranking guarantee. Search performance depends on crawling, indexing, competing pages, and user demand that a single report cannot control.
For the currently exposed nqzai workflow and connection limits, check the public capabilities inventory before relying on a result.
Primary references
Where nqzai fits
The workflow above is one nqzai runs directly: AI keyword research.
How we keep this honest
Every response nqzai's agent generates is automatically graded by an independent AI judge for accuracy and whether it invents information it can't back up. As of September 2026: sampled responses averaged a 82% quality score over the trailing 7 days (n=39), and our nightly regression suite — which re-runs the agent against a fixed set of real scenarios — passed at a ~93% rate over the last 14 nights. This is internal automated QA, not an independently audited or third-party benchmark; we publish it as a transparency signal, not a claim of perfection.
