Travel Problem Radar: travel-industry problems, each turned into a product idea
Above: the public demo after replaying the July 2026 sample. Every card has a source link and a one-line product
opportunity.
Travel Problem Radar searches the web for problems in travel: traveler complaints, new visa rules and taxes,
booking-site outages, strikes. It sorts what it finds into four categories, flags anything not seen before, and tags
each item with a product idea a PM could build.
Product owner: Bhawna Mangla · Built with AI (Claude) · Status: live; Pro paid through Razorpay since
28 Oct 2026, at ₹1 a month or ₹1 a year for now. First built July 2026
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| Home page | https://radar.pehchanthetraveller.com/ (also served by GitHub Pages). Latest findings, plans, and sign-up / sign-in |
| Try the demo | https://bhawnamanglapm.github.io/travel-problem-radar-case-study/demo/ (replays a saved sample; no AI calls) |
| Sample digest | https://bhawnamanglapm.github.io/travel-problem-radar-case-study/demo/#report |
| Live page | https://radar.pehchanthetraveller.com/live/. Pro members only since 2026-10-23 (BOARD_PAYWALL); others see a sign-in or Request Pro panel, and the demo above is open to all. It sweeps 1 to 5 times a day: as often as the Pro member who chose the most emails a day (T32). The first production sweep (Oct 2026) saved items from only 1 of 4 categories; the cause, an output token limit, is fixed, and on 25 Oct 2026 a production sweep saved all four (18 items). |
| Get it by email | https://radar.pehchanthetraveller.com/pricing/. Free: a daily summary (counts and headlines). Pro: the live board and 1 to 5 emails a day (the member chooses, default 2), for the categories and areas they choose. Pro costs ₹1 a month or ₹1 a year, paid through Razorpay since 28 Oct 2026 (plan.json's paid, monthly and yearly): tick Pro when you sign up, or use Upgrade to Pro on the manage page your emails link to. One price whatever you choose (T33). |
| PM case study | pm/CASE_STUDY.md: the product written up across eight product-management stages, from discovery to testing. Stage 5 was written as a plan before payments went live on 28 Oct 2026; it now records the launch and what's still open |
| More | Technical reference · PRD · Decision log · Subscriptions: how it fits together · Changelog |
Problem
The original case study put it this way: "The best product ideas in travel start as someone's bad day: a refund that never
came, a visa fee that quietly quadrupled, a booking that vanished after payment. But those signals live everywhere:
news wires, government notices, outage trackers, review sites, protest calendars. No PM has time to read all of it,
every day, across the world."
The user is a product manager looking for problems worth solving, starting with the owner. The goal is a standing
feed that finds problems, sorts them and suggests the "so what" before the morning starts, rather than a one-off
research report.
OWNER INPUT NEEDED: did anyone other than you use the radar (a PM team, a manager)? If not, say so. This repo
records no user research.
Why AI, and why not just rules
The repo does not record whether keyword alerts or RSS feeds were tried first. This is how the design splits the work
between the model and plain code:
| Job | Who does it | Why |
|---|
| Finding problems across news, government notices, outage trackers and travel sites, worldwide | Claude with its web-search tool, one call per category | There is no fixed list of sources or keywords. A model can search, read and judge relevance across countries and formats. |
| Writing a summary, judging severity, proposing a product opportunity | Claude, in a fixed JSON shape | This is the judgement part: turning a news item into a product angle. |
| Merging, de-duplicating, flagging "New", keeping history, limiting runs | Plain code | These must be predictable and testable. All of them are covered by offline tests. |
| Cleaning the model's output | Plain code | A link must start with http(s):// or it is dropped; severity outside Low/Medium/High becomes Medium; an unreadable reply fails that category. |
Key decisions and tradeoffs
Full log with dates: docs/decisions.md.
This is the beginning of the README. Read the rest at the original. Read the full README ↗
