How should we improve the NHS?
Give specific details of what could be done and how? Give examples of what is not working with proposed solutions. How could we leverage technology whilst also ensuring privacy?
Vote on statements. Discover where you agree with people you thought you didn't. See what the data actually reveals — not percentages, but clusters of real opinion.
You start with a statement, cast your vote, and discover how your view fits into the wider picture — not as a raw percentage, but as part of a real opinion cluster.
A discussion statement
"The UK should bring forward its net zero target from 2050 to 2040 to maintain climate leadership."
Statement 3 of 8
Based on 1,247 votes
How it works in 3 steps
Each discussion presents clear, balanced statements on a real issue — written to be fair to all sides. No leading questions, no loaded language.
One tap. No essays, no point-scoring. Just your genuine position. You can add reasoning or evidence, but it's optional. Vote on 5 statements to unlock your cluster.
Once enough people have voted, machine learning groups participants by their actual voting patterns. You'll see which group you're in, what your group agrees on, and where surprising common ground exists.
Try it yourself — takes 2 minutes
Vote on our live demo discussion, then see what the consensus analysis reveals about how opinion clusters.
We show you the shape of opinion, not just the count — which groups emerge, what they share across divides, and where genuine fault lines lie.
Opinion clusters
Consensus Analysis — UK Net Zero Discussion
1,247 participants612 people
412 people
223
ML clustering by voting pattern
"Investment in renewable energy creates more jobs than it destroys."
"Energy security and climate action can and should be pursued together."
"The cost of the transition should fall primarily on high-income households."
Why this matters
Traditional polls reveal how many people agree with something — but not who, or why, or what else they share. Clustered opinion data reveals the genuine structure beneath the numbers: which groups agree, which diverge, and where opposing groups find unexpected common ground.
Ideas with broad agreement across all groups — the genuine common ground that polls often miss.
Ideas that unite people who otherwise disagree — the foundation for productive conversation across divides.
Real fault lines — the places where groups genuinely differ. Understanding these is the start of honest public debate.
Why this matters now
Social media rewards outrage over nuance. Opinion polls flatten complexity into percentages. Comment sections amplify the loudest voices. And governments run "consultations" that nobody reads. We built Society Speaks because the infrastructure for genuine public deliberation is broken.
A poll tells you 62% of people agree with something. It doesn't tell you which 62%, how strongly they feel, whether they have anything else in common, or whether that 62% is actually six different groups who agree for completely different reasons.
Comment sections are dominated by the most motivated, most extreme, and most available voices. They create the illusion of discourse while actively suppressing it. The quiet majority rarely speaks — and when it does, it's drowned out.
Government and corporate consultations generate thousands of unstructured submissions. They are expensive to analyse, easy to game with organised campaigns, and almost never result in a usable picture of where genuine public agreement lies.
Our methodology
Society Speaks uses a machine learning technique called opinion clustering (based on principal component analysis of voting patterns) to group participants not by who they are, but by how they actually vote on statements. This reveals the genuine structure of public opinion.
Once participants vote on enough statements, the algorithm identifies natural clusters — groups of people who vote similarly. It then classifies each statement as:
This approach is resistant to organised manipulation — coordinated campaigns show up as a distinct cluster rather than distorting the overall picture. It also surfaces the quiet majority: participants who never comment but whose votes carry equal weight.
Built on Pol.is — and beyond
Pol.is pioneered this approach and used it for Taiwan's vTaiwan participatory democracy process — one of the most successful examples of digital deliberation in history. We are inspired by that work and the open-source research behind it.
Society Speaks builds on the core clustering insight and takes it further for structured, institutional use:
Native statement curation
Statements are reviewed, balanced, and AI-assisted — ensuring quality and fairness rather than surfacing the most popular submitted statements
Programmes — structured multi-discussion campaigns
Group many discussions into phases, themes, and cohorts — enabling full consultation campaigns, not just one-off conversations
Evidence-linked reasoning
Participants can attach evidence and reasoning to their votes — moving beyond a binary to a richer record of why people think what they think
Publisher and partner integration
Embed discussions directly in news articles, policy documents, and websites — meeting participants where they already are
How we compare
| Feature | Society Speaks | Pol.is | YouGov / Polling | Citizens' Assemblies | Standard Consultation |
|---|---|---|---|---|---|
| Opinion clustering (ML) | ✓ | ✓ | ✗ | ✗ | ✗ |
| Structured programmes / phases | ✓ | ✗ | ✗ | ✓ | ~ |
| Embeddable in websites | ✓ | ✓ | ✗ | ✗ | ✗ |
| Evidence-linked reasoning | ✓ | ✗ | ✗ | ✓ | ✗ |
| Open to public participation | ✓ | ✓ | Panel only | Selected only | ~ |
| Free to use | ✓ | ✓ | ✗ | ✗ | ✗ |
| Curated, balanced statements | ✓ | ✗ | ~ | ✓ | ✗ |
| Full data export (CSV/JSON) | ✓ | ✓ | Paid only | ~ | ✗ |
| Scalable — from 10 to 100,000 participants | ✓ | ✓ | Expensive at scale | 100–200 people | Unwieldy at scale |
~ = partial or limited capability
Real discussions on real issues — join in and see where opinion clusters.
Give specific details of what could be done and how? Give examples of what is not working with proposed solutions. How could we leverage technology whilst also ensuring privacy?
Iran's Foreign Minister Abbas Araghchi said Tuesday his country would keep fighting as long as necessary, casting doubt on US President Donald Trump's insistence that the conflict would be over "soon."
Min Aung Hlaing has been replaced by a close ally as military commander. He will now face a three-way vote for president by a parliament mostly loyal to the army
Programmes
A Programme groups multiple discussions into one structured campaign — with shared themes, phases, participant cohorts, and full data export. Used by organisations and governments for everything from stakeholder consultations to national strategy dialogues.
Programme · Example
Regional consultation on housing supply, planning reform, and affordability
8
Discussions
2,419
Participants
4
Cohorts
What this generates
Same platform. Same rigour. Works differently for each audience.
Citizens, activists, students, curious people
Take a position on issues that matter to you. See where you stand relative to others — not just as a percentage, but as part of a cluster of people who think like you. Discover where you have more in common with other groups than expected.
Brands, media, podcasters, newsletter writers
Your audience has opinions. Society Speaks lets you surface them properly — not with a poll or a comment section, but with structured debate and real analysis. Find out what your audience actually agrees on, and what genuinely divides them.
NGOs, councils, research bodies, companies
Run structured public or stakeholder consultations with full control over who participates and what gets asked. Create a Programme to group discussions by theme, organise them into phases, and export the full dataset for your own analysis.
Departments, strategy offices, democratic institutions
Run deliberative polling at national or regional scale. Map what the population agrees on, where genuine divisions lie, and what bridges opposing views. Get structured evidence to inform policy — not just percentages, but clustered insight.
In use: National Strategy Project
The National Strategy Project is using Society Speaks to run national dialogue on the UK's long-term future — mapping where citizens agree, disagree, and where common ground exists across divides.
Visit the National Strategy ProjectGet set up
Profiles take a few minutes to create and are free. Choose the type that fits how you want to use the platform.
Best for: citizens, researchers, journalists, activists
What your profile includes
Best for: NGOs, councils, think tanks, media, podcasts
What your profile includes
Common questions
Yes — participating in discussions, creating discussions, and creating individual and organisation profiles are all free. Programmes are also free for most use cases. For large-scale institutional deployments with dedicated support, white-labelling, or advanced integrations, get in touch.
The clustering algorithm needs enough data to identify meaningful groups. In practice, you'll start to see clear patterns from around 30–40 active participants (people who have voted on at least 5 statements). The analysis becomes significantly more reliable with 100+ participants, and very robust at 500+. Each participant needs to vote on at least 5 statements to be included in their cluster.
Individual votes are private — no one can see how you specifically voted on any statement. What is visible is the aggregate result: the percentage breakdown of agree/disagree/unsure across all participants, and the cluster groupings. The consensus analysis shows which cluster you belong to, but does not reveal your individual votes to other participants or the discussion host.
A discussion is a single conversation on one topic. A Programme is a structured campaign that groups many discussions together — for example, a national consultation on housing policy might have separate discussions on planning, affordability, social housing, and landlord regulation. Programmes support phases (e.g. Listening → Deliberation → Recommendations), themes, and participant cohorts, with a single export of all data.
Yes. Discussion creators and Programme managers can export all vote data as CSV or JSON — including per-statement results, participant clusters, and cohort breakdowns. This lets you do your own analysis, feed results into reports, or archive everything outside the platform.
Survey tools give you aggregate responses — percentages and averages. Society Speaks reveals the structure of opinion: how views cluster, which ideas bridge opposing groups, and where genuine fault lines lie. It's also open to public participation by default, and participants can add their own statements and reasoning — making it a genuine deliberative tool rather than a data collection exercise.
Still have questions? Email us or read the docs.
See it in action, read the docs, or set up an embed.
Traditional polling gives you percentages. Comment sections amplify the loudest voices. Society Speaks shows you how views actually cluster — and where genuine common ground lies. Inspired by Pol.is, built for deliberative democracy at any scale.