WebCarrots™ Smart Gap Analysis™ — User Guide

1) What this report is (and isn’t)

The Smart Gap Analysis combines your target page with two or more external pages (competitors or cross‑industry references) to measure topic and offering coverage, surface actionable Opportunities, and validate interest via normalized query (NormQ) diagnostics and 30‑day trend charts. Treat it as decision support—always confirm against the raw source data WebCarrots stores for you.

2) Ideally* you should use it after

*Some processes like running the platform’s AI Content Gap Analysis, Agency‑Grade; Competitor Comparison, and Validate Website URL (as target) are prerequisites.

• You’ve screened competitors (or other benchmark sites) with WebCarrots’ tools and want a precise, prioritized “what to add / improve” list.
• You manage an ongoing, multi‑gap content program and need prioritization and progress visibility.
• You intentionally compare different industries or page types to import winning content patterns (the system neutralizes industry bias to surface structural/content similarities).

3) Best practice before you study & implement

Work left‑to‑right across the WebCarrots stack so you already know what you’re looking at when you land here:

1. MetaCarrots — raw meta title, description, H1, on‑page copy.
2. IntelCarrots — how search engines/platforms surface the domain to harvest topic ideas (even from channels you don’t run, e.g., LinkedIn).
3. AI Content Gap Analysis — per‑competitor gap lists you’ll see blended inside Smart Gap Analysis.
4. Agency‑grade; Target web page synopsis — and if you’re not familiar with the page, skim the target’s raw scraped data.
5. Agency‑grade; Competitor Analysis Report — overlaps / non‑overlaps at a glance.

Only after this intel can you make the best out of Smart Gap Analysis: measure, prioritize, then move to Project Management to create tasks to close gaps.

4) Anatomy of the grid

Rows = Topics

Each row is an exact or close semantic topic cluster. A topic can appear more than once (worded differently on purpose). The system keeps them separate so you can decide whether to consolidate or cover both angles.

Columns = Entities you’re comparing

Columns can be A–E (or fewer/more), corresponding to the group you submitted to the WebCarrots content gap engine. If you followed best practice, they’re usually the same page type (same industry / service model).

If you combined industries or page types (e.g., service vs. eCommerce, another vertical), treat the column that naturally shares no topics with the rest as a configurable contrast slot.

Even within the same industry, some rows may show only one competitor’s data—useful, but not always fully encapsulated.

Inside each competitor block

• Offering — what that page actually says/does for that topic.
• Opportunity — system logic + AI + rules‑based recommendation on how your target should close or outplay that gap. Includes NormQ labels used to test real‑time search demand (last 30 days) and seasonality.

5) The Score Bars (topics vs. offerings)

• Topic score bar: how well the topic itself is covered on the target vs. competitors.
  • Green / long = largely closed content gap
  • Brownish / short = material content gap remains
• Offering score bar: how strong the granular execution is (what users care about). Often the topic “looks covered,” but the offer mechanics are thin—fixing offering depth usually fixes both. Track and remediate both levels.

6) NormQ (Normalized Query) & Trend Charts

For each high‑priority opportunity, the system attaches a normalized query (e.g., “[core / priority / relevant concept] + [industry/service]”) and checks, in real time, the last 30 days of demand from the report’s processing date. If demand passes threshold, you’ll see a sparkline/trend chart—hover to inspect dates and seasonality. No chart ≠ low priority: close the gap if business value or future demand justifies it.

7) Multi‑industry / cross‑type comparisons

If you mix industries or page types, the engine down‑weights labels and hunts for structure / intent similarity (e.g., guarantees, onboarding flows, support models). Use these as building blocks for copy, UX, packaging—not just SEO. Sometimes, shared topics will also surface and can be leveraged per your strategy.

8) Keyword ≠ Topic (and keyword gaps ≠ content gaps)

Placing a keyword inside another section doesn’t make it a topic. If the report flags a gap while you “know you used the word,” it’s usually because:

• It’s buried under a stronger headline/section, so AI/search helpers treat it as a sub‑detail, not a topic. Keyword gaps matter for standard search engines, but this report targets content gaps.
• You used a synonym people don’t search for. Example: users want “PDF” but the page says “digital content.” Explicit user language often wins benchmarks.

Scientifically QA doubts: verify via MetaCarrots raw competitor text vs. Target Synopsis before you dismiss a flagged gap.

9) Prioritize like a pro

• Gap Size — how short the topic/offering score bars are.
• Competitor Density — how many competitors already nail it vs. the target.
• NormQ Demand — is the 30‑day chart lively?
• Strategic Fit — does it advance differentiation or revenue?
• Execution Effort — copy tweak vs. net‑new productized service.

Rank, then move to Project Management to formalize tasks.

10) Close the gaps — end‑to‑end workflow

1. Brief yourself in MetaCarrots and IntelCarrots.
2. Open AI Content Gap Analysis to see per‑competitor deltas.
3. Open Target Synopsis to see topics, how AI/SE may frame the page (features, info). If the content is direct competitive text, verify with the available description; grab suggestions.
4. Open Competitor Comparison to check content sharing density. If many competitors share it, that’s a must‑cover alert.
5. Enter Smart Gap Analysis to see the combined picture and scores.
6. Note priorities by gap size + NormQ demand.
7. Open Project Management (per competitor of interest) to pick angles, plan deliverables, owners, timelines.
8. Use Content Gap Management Task Guide (industry common tactics) to pick exact remediation patterns.
9. Track execution in Progress Hub for cross‑project visibility; use Global Notes to micromanage context.
10. Fix content / productize offers.
11. Recrawl → remove previous Target Synopsis → Rerun Smart Gap Analysis to verify closure (expect slight natural AI variance run‑to‑run).
12. The re‑run completely re‑evaluates competitor vs. target, re‑establishes measurements, re‑ranks, re‑checks NormQs in real time, and regenerates 30‑day trend graphs (where applicable).
13. Rinse & expand: once obvious gaps are shut, keep the same competitors list for fresh data next cycle (to detect new moves) or confirm you’re on track to outrank them. Also, validate a fresh multi‑industry URL list for the upcoming scrape/report date to leapfrog, not just catch up.

11) “Duplicated but different” topics

Similar offers may split across different topical angles (e.g., accessibility vs. hours‑of‑operation). Don’t auto‑merge—decide if both framings matter for how search helpers and users phrase intent. Covering both can grant extra visibility.

12) Common pitfalls to avoid

13) Disclaimer

This report merges generative AI semantic analysis with programmatic logic and smart algorithms. Outputs can vary slightly between runs on identical data—like two experts phrasing the same conclusion differently. Always pair recommendations with the verbatim sources stored in the system (MetaCarrots, Scraped Target) before committing.