The Problem
App developers and product managers need to track competitor app reviews and sentiment across app stores. Direct App Store and Google Play scraping is fragile and violates ToS. Review aggregator APIs charge $50-200/mo for limited coverage. Teams resort to manual review reading, which does not scale past 2-3 competitor apps.
The Scavio Solution
Search Google for app reviews and extract review sentiment from organic results, People Also Ask questions, and Reddit discussions. Google indexes app store reviews and surfaces them in search results alongside user discussions on Reddit and forums. This captures the public review sentiment without directly scraping app stores.
Before
Before the pipeline, a product team manually read competitor app reviews once per month. They tracked 3 competitors across iOS and Android -- 6 app store pages, skimmed 50 reviews each, noted themes in a spreadsheet. The process took 4 hours monthly and missed sentiment shifts between review sessions.
After
After automating with Scavio, daily searches for each competitor app's reviews surface the latest sentiment from Google-indexed reviews and Reddit discussions. 10 searches/day (5 competitors x 2 platforms) at $0.05/day. Sentiment shifts detected within 24 hours instead of monthly. Identified a competitor's major bug (mentioned in 30+ reviews) 3 weeks before the monthly manual check would have caught it.
Who It Is For
Product managers, app developers, and competitive intelligence teams who need automated competitor app review monitoring without scraping app stores directly.
Key Benefits
- Daily competitor app review monitoring at $0.05/day
- Google-indexed reviews plus Reddit discussions in one search
- Detects sentiment shifts within 24 hours
- No app store scraping or ToS violations
- 10 daily searches cover 5 competitors across both platforms
Python Example
import requests, os, json
H = {'x-api-key': os.environ['SCAVIO_API_KEY']}
def app_review_signals(app_name: str) -> dict:
# Google for indexed reviews
g = requests.post('https://api.scavio.dev/api/v1/search', headers=H,
json={'platform': 'google', 'query': f'{app_name} app reviews 2026'},
timeout=10).json()
# Reddit for community sentiment
r = requests.post('https://api.scavio.dev/api/v1/search', headers=H,
json={'platform': 'reddit', 'query': f'{app_name} app'}, timeout=10).json()
google_snippets = [o.get('snippet', '') for o in g.get('organic', [])[:5]]
reddit_titles = [o.get('title', '') for o in r.get('organic', [])[:5]]
# Simple sentiment signal: check for negative keywords
neg_keywords = ['bug', 'crash', 'slow', 'broken', 'worst', 'terrible', 'unusable']
all_text = ' '.join(google_snippets + reddit_titles).lower()
neg_count = sum(1 for kw in neg_keywords if kw in all_text)
return {
'app': app_name,
'negative_signals': neg_count,
'sentiment': 'negative' if neg_count >= 3 else 'mixed' if neg_count >= 1 else 'positive',
'google_snippets': google_snippets[:3],
'reddit_titles': reddit_titles[:3],
}
apps = ['Notion', 'Obsidian', 'Todoist']
for app in apps:
signals = app_review_signals(app)
print(f'{app}: {signals["sentiment"]} ({signals["negative_signals"]} neg signals)')JavaScript Example
const H = { 'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json' };
async function appReviewSignals(appName) {
const [g, r] = await Promise.all([
fetch('https://api.scavio.dev/api/v1/search', { method: 'POST', headers: H,
body: JSON.stringify({ platform: 'google', query: `${appName} app reviews 2026` }) }).then(r => r.json()),
fetch('https://api.scavio.dev/api/v1/search', { method: 'POST', headers: H,
body: JSON.stringify({ platform: 'reddit', query: `${appName} app` }) }).then(r => r.json()),
]);
const snippets = (g.organic || []).slice(0, 5).map(o => o.snippet || '');
const titles = (r.organic || []).slice(0, 5).map(o => o.title || '');
const negKw = ['bug', 'crash', 'slow', 'broken', 'worst', 'terrible'];
const allText = [...snippets, ...titles].join(' ').toLowerCase();
const negCount = negKw.filter(kw => allText.includes(kw)).length;
return {
app: appName,
sentiment: negCount >= 3 ? 'negative' : negCount >= 1 ? 'mixed' : 'positive',
negativeSignals: negCount,
googleSnippets: snippets.slice(0, 3), redditTitles: titles.slice(0, 3),
};
}
const signals = await appReviewSignals('Notion');
console.log(`${signals.app}: ${signals.sentiment} (${signals.negativeSignals} neg signals)`);Platforms Used
Web search with knowledge graph, PAA, and AI overviews
Community, posts & threaded comments from any subreddit