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App Review Alert Workflow

Automated workflow that monitors competitor app reviews via Google and Reddit search and alerts on sentiment shifts within 24 hours.

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Overview

Monitor competitor app reviews daily by searching Google for indexed app store reviews and Reddit for community discussions. Alert on negative sentiment spikes, major bugs, and feature complaints before your competitors react.

Trigger

Daily cron at 09:00 UTC

Schedule

Daily at 09:00 UTC

Workflow Steps

1

Define competitor apps

Maintain a list of competitor app names with their app store identifiers. Group by category for targeted monitoring.

2

Google review search

For each competitor app, search Google for '[app name] app reviews 2026'. Google indexes app store reviews and surfaces them in organic results.

3

Reddit community search

Search Reddit for each competitor app name. Community discussions often surface issues before they appear in formal reviews.

4

Sentiment scoring

Count negative keywords (bug, crash, slow, broken, worst) in result snippets and titles. Score each app's daily sentiment as positive, mixed, or negative.

5

Alert on changes

Compare today's sentiment score against the 7-day average. If sentiment drops or negative signal count doubles, fire an alert to Slack or email.

Python Implementation

Python
import requests, os, json
from datetime import date

H = {'x-api-key': os.environ['SCAVIO_API_KEY']}
NEG_KW = ['bug', 'crash', 'slow', 'broken', 'worst', 'terrible', 'unusable', 'down', 'error', 'freeze']

def monitor_app(app_name):
    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()
    r = requests.post('https://api.scavio.dev/api/v1/search', headers=H,
        json={'platform': 'reddit', 'query': f'{app_name} app'}, timeout=10).json()
    google_text = ' '.join(o.get('snippet', '') for o in g.get('organic', [])[:5]).lower()
    reddit_text = ' '.join(o.get('title', '') for o in r.get('organic', [])[:5]).lower()
    all_text = google_text + ' ' + reddit_text
    neg_count = sum(1 for kw in NEG_KW if kw in all_text)
    return {
        'app': app_name, 'date': str(date.today()),
        'negative_signals': neg_count,
        'sentiment': 'negative' if neg_count >= 4 else 'mixed' if neg_count >= 2 else 'positive',
        'google_snippets': [o.get('snippet', '')[:100] for o in g.get('organic', [])[:3]],
        'reddit_titles': [o.get('title', '')[:80] for o in r.get('organic', [])[:3]],
    }

apps = ['Notion', 'Obsidian', 'Todoist', 'ClickUp', 'Monday']
for app in apps:
    result = monitor_app(app)
    indicator = '!!!' if result['sentiment'] == 'negative' else '...' if result['sentiment'] == 'mixed' else '   '
    print(f"[{result['sentiment'].upper():>8}] {indicator} {app}: {result['negative_signals']} neg signals")

JavaScript Implementation

JavaScript
const H = {"x-api-key": process.env.SCAVIO_API_KEY, "Content-Type": "application/json"};
const NEG_KW = ["bug", "crash", "slow", "broken", "worst", "terrible", "unusable", "down", "error", "freeze"];

async function monitorApp(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 googleText = (g.organic || []).slice(0, 5).map(o => o.snippet || "").join(" ").toLowerCase();
  const redditText = (r.organic || []).slice(0, 5).map(o => o.title || "").join(" ").toLowerCase();
  const allText = googleText + " " + redditText;
  const negCount = NEG_KW.filter(kw => allText.includes(kw)).length;
  return {
    app: appName, negativeSignals: negCount,
    sentiment: negCount >= 4 ? "negative" : negCount >= 2 ? "mixed" : "positive",
    googleSnippets: (g.organic || []).slice(0, 3).map(o => (o.snippet || "").slice(0, 100)),
    redditTitles: (r.organic || []).slice(0, 3).map(o => (o.title || "").slice(0, 80)),
  };
}

(async () => {
  const apps = ["Notion", "Obsidian", "Todoist", "ClickUp", "Monday"];
  for (const app of apps) {
    const r = await monitorApp(app);
    const ind = r.sentiment === "negative" ? "!!!" : r.sentiment === "mixed" ? "..." : "   ";
    console.log(`[${r.sentiment.toUpperCase().padStart(8)}] ${ind} ${app}: ${r.negativeSignals} neg signals`);
  }
})();

Platforms Used

Google

Web search with knowledge graph, PAA, and AI overviews

Reddit

Community, posts & threaded comments from any subreddit

Frequently Asked Questions

Monitor competitor app reviews daily by searching Google for indexed app store reviews and Reddit for community discussions. Alert on negative sentiment spikes, major bugs, and feature complaints before your competitors react.

This workflow uses a daily cron at 09:00 utc. Daily at 09:00 UTC.

This workflow uses the following Scavio platforms: google, reddit. Each platform is called via the same unified API endpoint.

Yes. Scavio's free tier includes 50 credits on signup with no credit card required. That is enough to test and validate this workflow before scaling it.

App Review Alert Workflow

Automated workflow that monitors competitor app reviews via Google and Reddit search and alerts on sentiment shifts within 24 hours.

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