YouTube conversation research
Find the signal in thousands of YouTube comments.
Tell us the topic or the videos. SignalStory collects the public comments, shows you exactly what will be analysed, and turns it into a decision-ready report: themes, sentiment, the arguments people are having, and the quotes that prove it.
One payment of ₹999 covers collection, analysis and your finished report. Full refund if we can't deliver.
Design earns desire, service holds it back
How it works
One payment. Nothing else to buy.
Brief us
Tell us the brand or topic, competitors, market and what you want to learn.
Pay once
Secure payment by UPI or card. A study can only be charged once.
We collect
We gather public YouTube conversation on your topic. You can close the tab.
We analyse
Every finding is checked against real comments before it reaches your report.
You download
Get a finished PowerPoint report. Re-download any time from your dashboard.
Inside every report
Three views that turn noise into a decision.
Sentiment, honestly split
Positive, mixed and negative, overall and per product attribute.
Every insight, with its evidence
Each insight shows how strong the evidence is and the real comments behind it.
Actions, not just charts
What to protect, what to fix and what to keep watching.
What's in the report
Not a word cloud. An argument you can take to a meeting.
- Executive summary in plain language, with the takeaways to remember.
- Insights ranked by strategic priority, each with the real comments behind it and an evidence-strength label.
- Sentiment overall and by product attribute, so you see where the friction actually is.
- Decision-ready actions on what to protect, what to fix and what to monitor.
- Method & limits stated up front, so nobody over-reads it.
Good for
- Product and brand teams reading launch reactions
- Agencies scoping a category before a pitch
- Creators and publishers understanding their audience
- Researchers looking for hypotheses to test properly
Not for
- Measuring what "the public" or a national population thinks
- Forecasting elections, sales or any statistical outcome
Pricing
One study. One price. No subscription.
One payment covers collection, analysis and your report. No subscription, no add-ons. If we can't deliver, you're refunded in full.
PER STUDY
₹999one-time
- Thousands of public comments collected across dozens of videos
- Finished PowerPoint report, ready to present
- Report history kept in your account
- If analysis fails, we resume it. You don't pay again.
Questions
Before you start
When do I pay?
At the start. You describe your study, pay ₹999 once by UPI or card, and we then collect the comments, run the analysis and build your report. There is no free trial run because every study uses paid data collection and analysis.
Can I see what I'm buying first?
Yes. Open the sample report to see exactly what ₹999 produces, from the executive summary to evidence-backed insights, and download the sample PowerPoint.
Is this representative of the population?
No. It covers publicly available YouTube comments only. Commenters skew toward people who chose to speak up on a given video. Read the results as directional signal, not a survey.
What if the analysis fails after I've paid?
Your progress is saved in stages. We resume from the last completed stage without charging you again. If we can't deliver a report, we refund the payment.
Can I get the report again later?
Yes. Every report stays in your dashboard. Re-downloading never re-runs the analysis.
See what ₹999 produces before you spend it.
Halden Aurora: launch response
“Halden Aurora” is a fictional vehicle. Every comment and number here is invented to show the depth and layout of a paid report. No real customer's study is shown. This sample uses a small evidence set for readability; a live study analyses up to 600 evidence comments.
Desire is strong. Confidence is the gap.
Aurora is creating desire through distinctive design and legacy, but conversion confidence is being moderated by Halden ownership concerns and price expectations.
- Protect the design-led desirability.
- Convert heritage attention into contemporary product proof.
- Address service and ownership confidence visibly.
- Treat pricing and powertrain clarity as conversion levers.
How people feel
Product styling is strongly positive, while ownership/service sentiment is distinctly more cautious. Several comments are mixed rather than simply positive or negative.
What builds desire, what breaks it
What drives desire
- Distinctive exterior design and road presence
- Emotional pull of the Aurora legacy
- Premium/clean interior cues
- Perceived family usability
What breaks confidence
- Service and workshop confidence
- Quality/reliability anxiety
- Price threshold versus proven alternatives
- EV charging concern and desire for ICE choice
Which attributes people link to the brand
Share of brand mentions that also discuss each attribute, split by sentiment.
Design
6 OF 18 MENTIONS · 33.3%6 positive · 0 negative · 3 independent videos
Service & reliability
4 OF 18 MENTIONS · 22.2%0 positive · 4 negative · 2 independent videos
Price & value
3 OF 18 MENTIONS · 16.7%1 positive · 1 negative · 1 independent video
Five findings, each traced to real comments
Every insight names its evidence strength. Insights resting on fewer than three independent videos are labelled as developing or early rather than overstated.
Design creates desire beyond nostalgia
Developing evidenceConsumers respond to the Aurora as visually distinctive, with the legacy name amplifying rather than replacing current-product appeal.
Why it matters. This gives the launch a product-led hook rather than relying only on heritage. What to do. Lead communication with contemporary design while using heritage as an emotional amplifier.
“The new Aurora looks stunning, finally something different on the road”SYNTHETIC COMMENT · 4 VALIDATED COMMENTS ACROSS 2 VIDEOS
Ownership confidence is the clearest conversion tension
Developing evidencePositive reactions to the vehicle are repeatedly qualified by concerns about Halden service, workshop experience and quality confidence.
Why it matters. The barrier sits outside core product desirability and can therefore interrupt conversion late in consideration. What to do. Pair product excitement with visible ownership reassurance, warranty and service proof.
“Nostalgia is nice but I will buy only if Halden fixes service quality”SYNTHETIC COMMENT · 4 VALIDATED COMMENTS ACROSS 2 VIDEOS
Price is a threshold, not a background detail
Developing evidenceConsumers frame Aurora value conditionally: attractive pricing can unlock consideration, while a higher price immediately activates proven alternatives.
Why it matters. Price can determine whether design interest becomes a shortlist decision. What to do. Value communication should anchor the price against distinctive design, equipment and ownership reassurance.
“If they price this around 18 lakh it can be a killer deal”SYNTHETIC COMMENT · 3 VALIDATED COMMENTS ACROSS 1 VIDEO
Powertrain choice could broaden or narrow the audience
Developing evidenceInterest is not uniformly EV-led; some consumers explicitly ask for ICE/automatic options while others see EV suitability but retain highway-charging concerns.
Why it matters. A single-powertrain story risks leaving part of the consideration audience behind. What to do. Clarify the powertrain portfolio and frame each option around a distinct usage case.
“I want the diesel or petrol Aurora, not only EV”SYNTHETIC COMMENT · 3 VALIDATED COMMENTS ACROSS 1 VIDEO
Legacy opens the door, but present-day relevance must close the sale
Developing evidenceThe Aurora name triggers family memories and attention, yet consumers still evaluate the new vehicle on design, service, price and powertrain fundamentals.
Why it matters. Nostalgia is an acquisition asset but not sufficient proof of purchase value. What to do. Use heritage early in the story, then transition quickly to modern product and ownership proof.
“My dad had the old Aurora. This comeback hits differently”SYNTHETIC COMMENT · 3 VALIDATED COMMENTS ACROSS 1 VIDEO
What may matter next
Ownership reassurance may become part of launch communication
DevelopingConsumers spontaneously connect product interest with service/warranty confidence.
How to read this
Comments are collected from publicly visible YouTube conversation, filtered for spam and duplicates, and analysed with AI assistance. Python-measured counts and shares stay authoritative, and every cited comment is checked against the source data before an insight is accepted.
Every study you run, kept and ready to reopen.
Describe your study, pay ₹999 once, and get your report. Your history stays in your account.
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Your studies and reports are saved to your account.
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Review your study
Not paid yetSearch terms and collection depth are set by SignalStory. Results describe public YouTube conversation and are directional, not representative of a population.
What ₹999 includes
- Collection of public YouTube conversation on your topic
- AI analysis where every finding is checked against real comments
- A finished PowerPoint report, kept in your dashboard
- Automatic resume if anything stops, and a full refund if we can't deliver
We're building your report
- Payment receiveddone
- Collecting public YouTube commentsstage 1 of 3
- Analysing the evidencestage 2 of 3
- Building your reportstage 3 of 3
You can close this page. Your study keeps running and appears in your dashboard.
Your report is ready
Downloading or rebuilding never re-runs the analysis and never costs anything.
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Terms of Service
What SignalStory does
SignalStory analyses publicly available YouTube comments and produces a report. It is a research aid. It is not legal, financial or investment advice.
Directional, not representative
Reports describe the comments we collected. Commenters are self-selected and are not a random sample of any population. Do not present findings as representing the views of a country, market or demographic.
Your account
- You're responsible for keeping your login secure.
- Your studies and reports are private to your account.
Payment
Each study costs ₹999 [plus applicable taxes]. Payment is taken before collection begins and covers data collection, one analysis and the report for that study.
Acceptable use
Don't use SignalStory to harass, identify or target individual commenters, or to break YouTube's Terms of Service. We may suspend accounts that do.
Service limits
Reports are AI-assisted and may contain errors. We provide the service "as is" [liability clause to be drafted]. Governing law: [India / jurisdiction].
Last updated: [date]
Privacy Policy
What we collect
- Account: name, email, sign-in method.
- Studies: the topics and links you enter, and the public YouTube comments collected for them.
- Payments: handled by our payment partner. We keep the order status and amount, never card or UPI details.
How we use it
To run your studies, generate your reports, provide support and keep the service secure. Public comment text is sent to an AI provider (Anthropic) for analysis.
Retention and deletion
Reports are kept while your account is active. Collected comment data is deleted after [X days]. Email [privacy address] to delete your account and data.
Who can see your work
Only you, plus a small number of SignalStory staff for support and quality checks.
Contact & support
Reply within [1 business day]. Include your study name so we can find it fast.
- Support
- support@[yourdomain]
- Privacy
- privacy@[yourdomain]
- Business
- [Registered name, address, GSTIN]
- Hours
- [Mon–Fri, 10:00–18:00 IST]
Send us a message
Refunds
If we can't deliver a complete report for a paid study, we refund the ₹999 in full. Reports are not refundable once delivered, but write to us if something looks wrong and we'll re-check the analysis.