How tickerAnalytiQ works
Built for new registered users who need a simple research workflow quickly. Use this as your onboarding page and as the script for your welcome video voice-over.
Video plan for onboarding
Suggested video length: 5 to 7 minutes. Keep pacing slow and practical. Show exactly where users click.
Add your YouTube onboarding video here
Tip: keep captions on for clarity
Voice-over script (ready to record)
Part 1. Welcome to tickerAnalytiQ. This guide is for first-time users and it takes about ten minutes.
Part 2. First, set up your account and choose one market. Then add 8 to 12 stocks you already know. This keeps your watchlist clean and easy to manage.
Part 3. Each morning, open your watchlist and review the model classifications. Always check confidence beside each classification. Higher confidence means stronger model agreement.
Part 4. Before making any serious decision elsewhere, open the ticker detail page. Review the five-day forecast table and model breakdown so you can see why the output exists.
Part 5. If anything is unclear, use AI Chat and ask what changed and why. Keep your routine simple, and review your watchlist weekly.
7-step operating guide for new users
Create your account and pick your market
Start with one market only (for example ASX). New users get confused when they try all markets at once. Keep setup simple in week one.
Build a watchlist with 8 to 12 stocks
Pick companies users already understand. Avoid random tickers just to fill the list. A focused watchlist is easier to trust and review.
Check model classifications each morning
Open the watchlist and review the daily model classification for each stock. Users should treat this as research support, not a direct instruction.
Read confidence before drawing conclusions
High confidence means stronger model agreement. Lower confidence means mixed model views. This helps users understand uncertainty before acting elsewhere.
Open ticker detail before any major research conclusion
Use the ticker detail page to review forecast tables, model split, and historical output quality. This is where research trust is built.
Ask AI Chat for plain-English explanation
If users are unsure, ask: ‘Why is this bullish this week?’ or ‘What changed from yesterday?’. The answer reduces confusion quickly.
Do a 10-minute weekly review
At week-end, compare model outputs vs outcomes and tune the watchlist. Remove low-interest tickers and focus on names users actually follow.