App Review Competitive Report — Head-to-Head Comparison
Pricing
from $16,750.00 / 1,000 competitive reports
App Review Competitive Report — Head-to-Head Comparison
Pricing
from $16,750.00 / 1,000 competitive reports
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NexGen Watch
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App Review Competitive Report — Head-to-Head Sentiment, Themes, Complaints
Stop paying $50–100+/month for a review-intelligence subscription to compare your app against the competition. This actor delivers a full head-to-head competitive read across up to 5 apps — the same deep per-app analysis plus the positioning layer — per report, on demand, with no subscription. Apps in, one competitive intelligence report out.
| Typical review-intelligence SaaS | App Review Competitive Report | |
|---|---|---|
| Pricing | $50–100+/month, every month | $25.00 / report (FREE tier), pay only when you run |
| Scope | One seat, rate-limited comparisons | Up to 5 apps compared head-to-head, per report |
| Commitment | Annual/monthly lock-in | None — per report |
| Break-even | — | Run a competitive read every week (~$100/mo at FREE, less on volume tiers) — and only in the weeks you actually need it |
If a PM, ASO consultant, or agency pulls one competitive read per week, that's ~$100/month at the FREE tier (and less on BRONZE/SILVER/GOLD) — versus $50–100+/month for an always-on seat you rarely max out, per analyst. One report already covers a 5-app landscape that a single-app tool would bill you five runs for.
What you get in one report
Feed it 2 to 5 apps (each app_id + store, optional country/company_label). For every app it fetches up to 1,000 public reviews (logged-out, public data only) and runs the full ngd-lexicon-v1 deep analysis — then adds the head-to-head layer:
Per app (same depth as the single-app deep report):
- Full sentiment breakdown — positive / neutral / negative split, average sentiment score, average star rating
- Theme clustering — the terms and phrases reviewers actually use, ranked by mentions
- Complaint ranking — negative-review clusters ranked by frequency, each with its share of negatives and a real example quote
- Feature-request extraction — reviews that ask for something, clustered into the most-requested asks
- Trend vs prior period — automatic median split, with sentiment and rating deltas
Head-to-head positioning (across all apps):
- Relative sentiment leaderboard — apps ranked by sentiment score, positive %, negative %, and average rating
- Shared vs unique themes — what reviewers raise across the whole category vs what's specific to one app
- Shared vs unique complaints — the pain everyone shares vs the pain that's yours (or your competitor's) alone
- Winner by dimension — who leads on sentiment, rating, fewest complaints, developer responsiveness, and raised demand
- Overall composite positioning — a single ranked standing across the leaderboard dimensions
- Rendered markdown competitive brief — the whole comparison as a readable report (a dataset field and a key-value-store record), ready to paste into a deck, battlecard, or ticket
Output
- One
competitive_summarydataset record — the full head-to-head report (leaderboard, shared/unique diffs, winners, composite ranking, roster) plus the rendered markdown brief. - One
app_reportdataset record per compared app — the full deep analysis for that app. - Markdown briefs are also written to the key-value store (
COMPETITIVE_<id>for the comparison,REPORT_<store>_<app_id>_<id>per app).
Input
| Field | Required | Description |
|---|---|---|
targets | yes | Array of 2 to 5 apps. Each: app_id (Apple numeric id or Google Play package), store (apple or google_play), optional country (default us), language (Google Play, default en), company_label (display name) |
max_reviews | no | Cap on public reviews fetched per app (default/max 1000) |
max_themes | no | Max theme and complaint clusters per app (default 12) |
Method — deterministic, transparent, model-included
Analysis runs the ngd-lexicon-v1 engine: a transparent lexicon plus a rating prior — the identical engine used across the review-intelligence fleet, so scores are comparable app-to-app. It is fully deterministic — the same reviews always produce the same competitive report. No external LLM, no API key to bring, no "AI" black box. The model is included in the price.
Pricing
- Actor start: $0.05 (one-time, platform-reserved).
competitive_report: $25.00 per report at the FREE tier (BRONZE $22.50 · SILVER $20.00 · GOLD $16.75). Charged exactly once, only after the full competitive report over at least 2 apps is successfully built and delivered. If fewer than 2 apps yield reviews, or analysis can't run, the run fails and you are charged nothing.
Notes
- Public, logged-out data only. No login, no private endpoints.
- Cost-bounded: memory/time caps, a bounded per-page request-attempt budget, and a hard per-app review/output cap.
- An app that returns no public reviews is skipped and listed under
skipped_targets; the report still runs as long as at least 2 apps have data.