Israeli Chatbot Analytics
Verified94/100Analyze and optimize Hebrew chatbot performance with conversation flow analytics, Hebrew sentiment analysis, drop-off detection, user satisfaction scoring, A/B testing for response variants, and reporting dashboards.
Trust score 94/100 (Verified) · 57+ installs · 3 GitHub contributors · MIT license
Teams deploy Hebrew chatbots without proper analytics, making it impossible to know if the bot actually helps users or where conversations break down. The challenge is amplified by Hebrew-specific issues like sentiment analysis accuracy and RTL visualization.
npx skills-il add skills-il/developer-tools@v1.2.0-israeli-chatbot-analytics --skill israeli-chatbot-analytics -a claude-codeInstall on Claude.ai, Claude Desktop, ChatGPT, Manus, or other platforms
- 1. Click "Download ZIP" to download the skill files.
- 2. Open Claude Desktop and go to Customize > Skills.
- 3. Click "+" and select "Upload a skill", then upload the ZIP file.
- 4. Start a new conversation. The skill will activate automatically when relevant.
When to Apply
- When analyzing why users abandon chatbot conversations
- When measuring Hebrew chatbot sentiment accuracy
- When A/B testing different Hebrew response phrasings
- When building performance dashboards for a chatbot team
- When setting up alerts for chatbot performance degradation
Try These Prompts
Analyze the chatbot conversation logs and identify drop-off points where users abandon the conversation. Break down by: question type, conversation stage, time of day, and device. Present findings in a table with drop-off percentage per point and improvement recommendations.
Set up a real-time sentiment tracking system for Hebrew chatbot conversations. The system should detect sentiment shifts during the conversation, handle Israeli slang and sarcasm, and flag conversations where sentiment drops below a defined threshold.
Create a weekly chatbot performance report template that includes: conversation count, resolution rate, average response time, average sentiment, top 10 unanswered questions, and week-over-week comparison. The report should support Hebrew with RTL-compatible charts.
Set up an automatic alert system that detects anomalies in chatbot performance: sharp increase in abandonment, drop in average sentiment, unusual response times, or rise in unanswered questions. Define thresholds for each metric and alert channels (Slack, email).
Frequently Asked Questions
Changelog
Dialogflow CX language code he-il (iw deprecated). WhatsApp Business per-message pricing (July 2025 cutover): 4-category model, free 24h service window, 72h click-to-WhatsApp ad window. Section 30A compliance with 1,000 NIS statutory damages + 226K NIS criminal fine. DictaLM 2.0-Instruct (7B Mistral, ~200B tokens) + AlephBERT alongside DictaBERT. Rasa CALM is dialogue-driven Pro path. Statsig acquired by OpenAI 1.1B USD 2025. GA4 AI Assistant channel for ChatGPT/Gemini/Claude referral traffic.
May 20, 2026
Added Privacy and Consent guidance (Amendment 13), retention metrics (D1/D7 return rate), and an MCP-servers note; updated the Rasa reference to the legacy OSS docs.
May 14, 2026
Added Reference Links section pointing to official sources for fact verification.
Apr 15, 2026
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