naras

Marketing intelligence, made legible.

See how your brand is understood — and what your marketing is actually doing.

naras is a marketing-intelligence platform. Resonance shows how your brand is seen, understood and recommended — by people, by search, and by AI. Impact shows which parts of your marketing are working, and how that’s changed over time. Both speak plainly, show their evidence, and are honest about what they don’t know.

Book a demo See how it works
United Kingdom Resonance AI names two rivals before you
A rotating globe showing the kind of actionable insight naras surfaces about a brand across markets worldwide.

Most marketing tools give you dashboards. naras gives you understanding.

Numbers without context invite false confidence. naras is built on a different principle: every score is directional, not absolute; every claim shows the evidence behind it; and every result is honest about its uncertainty. We’d rather be usefully truthful than falsely precise.

And because the hardest part of intelligence is reading it, every naras module comes with an AI assistant that turns analysis into a plain-language answer — so you leave with a decision, not a spreadsheet to decode.

The suite

One platform. A growing set of instruments.

Each module answers one question well, in the same house style, with the same assistant sensibility — instruments on the same bench, not competing tabs.

naras Resonance Available

How is my brand understood?

Brand visibility, perception and AI presence — from survey signal, live search, Google's AI answers and direct audits of large language models.

Explore Resonance
naras Impact In development

What is my marketing doing?

Marketing mix modelling, made friendly — which channels are working, where returns diminish, and how each channel's effectiveness has changed over time.

Explore Impact

Resonance tells you how you’re perceived. Impact tells you what’s working. Together they connect what the market thinks to what your spend earns.

Also on the roadmap

naras Synthetic Research On the roadmap

What would an audience say — before fieldwork?

naras Strategic Planning On the roadmap

Turn the evidence into a plan.

Both are directional aids grounded in your evidence — Synthetic Research narrows the field before fieldwork, never instead of it.

The same promise under every module.

Evidence you can see

Nothing is a black box. Open any score and you'll find the data, sources and reasoning underneath it.

Honest about uncertainty

Results are directional and come with their confidence. We show the range, not just the number.

An assistant that explains

Ask in plain English and get grounded answers, drawn only from your real data — never invented.

Designed to be read

Editorial, legible, uncluttered. Intelligence you actually want to open.

How it works

Bring your context. naras does the work. You read, ask, act.

  1. 01

    Bring your context

    A brand and category for Resonance; your media and sales history (a spreadsheet is fine) for Impact. It's a short setup conversation, not a project — most of the work is ours. Your data stays yours, held securely; we walk your team through exactly how it's handled.

  2. 02

    naras gathers and models

    Resonance collects live evidence and audits AI systems; Impact builds a rigorous model of what's driving your results. Both run on durable, repeatable pipelines — the search and AI read is quick; a commissioned survey takes weeks, not the months a tracker takes to stand up.

  3. 03

    Read, ask, act

    Explore clear reports, ask the assistant anything, and export decision-ready summaries for the people who need them.

naras Resonance · Brand visibility, perception & AI presence Available

See how your brand is perceived, found and recommended — across markets, search and AI.

Resonance reads the survey, search and AI evidence about your brand and turns it into seven clear, explainable signals — so you can see where you're losing visibility, where AI under-recommends you, and what to fix first. It's an audit you re-run when you need a read, not an always-on tracker.

  • See how you're perceived

    Salience, perception and distinctiveness, against the same fixed competitor set every time — so comparisons are honest.

  • See where AI recommends you

    More buyers now ask ChatGPT, Claude and Google's AI before they ask you. When AI names a rival first — or leaves you off the shortlist — you lose consideration before the conversation starts. Resonance shows you exactly where that's happening.

  • Know what to do next

    Every signal opens to show its evidence, what drove it, and a clear recommended action.

See it on a real brand

Meet Northwind — a mid-market challenger in a crowded category.

Here’s its workspace, followed end to end.

  1. 01

    The scorecard

    Seven directional signals at a glance. Northwind’s salience is mid-pack — but its AI Visibility is the weakest signal on the board.

  2. 02

    Open the signal

    AI Visibility expands: ChatGPT names two competitors before it names Northwind, and Google’s AI Overview leaves it out of the shortlist entirely.

  3. 03

    The evidence

    Every claim links to the stored response that produced it — nothing is asserted without a record behind it.

  4. 04

    The action, on tap

    Each signal ends with the one move most likely to shift it — and you can ask the workspace about anything you see.

These visuals are illustrative, built from the design system; demo workspaces use synthetic survey data, clearly marked. Your workspace uses your own evidence — a survey commissioned for your brand, plus live search and AI audits.

Resonance · the method

Evidence first. Signals second.

naras Resonance reads four kinds of evidence about your brand, then turns them into signals you can act on. Nothing is invented — every score traces back to a record you can open.

Four evidence pillars

  • Survey Commissioned · real respondents Brand-health and perception data from a survey commissioned for your brand (synthetic in the demo).
  • Search Gathered live What organic results, Knowledge Graph and Google Trends say about you (via SerpApi).
  • AI Overview Gathered live How Google’s AI summary treats you in category searches.
  • AI audits Gathered live What OpenAI’s and Anthropic’s models say when asked to recommend in your category.

Seven signals

  1. Brand Salience how present you are in mind
  2. Perception Alignment whether people see you as you intend
  3. Competitive Distinctiveness how differentiated you are
  4. AI Visibility whether ChatGPT and Claude recommend you when asked directly
  5. Search AI Visibility whether Google’s AI Overview includes you in search
  6. Demand Signal the category’s pull toward you
  7. Reputation Signal risk and negative perception, handled carefully

Where the survey data comes from

Your survey is commissioned with real respondents through Cint, one of the largest respondent marketplaces and our survey-execution partner — with questions customised to your brand, category and the decisions you’re making. In the demo, the survey layer is synthetic (illustrative, not real respondents) and always marked as such.

Works with your existing tracker

Already run a brand tracker? We can take it over and onboard your history, keeping your audience definitions, segmentation and market coverage so your trend lines stay consistent — often on the same respondent marketplace your current provider uses. Starting fresh? We help you design a survey that captures what’s worth tracking. Not a second tool to run alongside — a smarter, faster, more actionable replacement.

These are directional diagnostics, not statistical guarantees — built to tell you which way to move, with the evidence shown so you can judge for yourself.

What “directional, not statistical” means

A signal’s confidence reflects how much evidence sits behind it — the sample and audience coverage of the survey, the recency of the search and AI evidence, and how consistent the sources are. Survey signals carry the sample and representativeness of the commissioned fieldwork; thin cells are flagged, not smoothed over.

What we don’t do is dress a diagnostic up as a significance test or a precise measurement. The job is to tell you which way to move and what to look at first, with the evidence open so you — or your insight team — can judge how far to trust it. Usefully honest beats falsely precise.

naras Impact · Marketing mix modelling, made friendly In development

See which parts of your marketing are working — and how that's changed over time.

Upload your media and sales data. Impact builds a rigorous model of what drove your results — channel by channel — and, uniquely, shows how each channel's effectiveness has risen and fallen over time. An AI assistant explains it in plain language, so the output is a decision, not a regression table.

You spend across a dozen channels and rarely know which earned their keep. Marketing mix modelling is meant to answer this, but it’s slow and expensive, opaque — a wall of statistics — and quietly misleading: a model fit over three years reports a single average per channel, hiding the rise, peak and fall within that window. Facebook today is not the Facebook of three years ago — and your model shouldn’t pretend it is.

01

Effectiveness that moves with time

Most models give one number per channel for the whole period. Impact shows each channel working harder or less hard over time — when it peaked, when it started to decay, when a strategy change paid off. Stop optimising against a stale average; see the trajectory.

02

Anchored to real-world lift, not just model fit

A model can fit your history and still be wrong about cause. So channel ROIs are calibrated against real-world lift and incrementality tests, and checked out-of-sample on held-out periods — anchoring the answer to measured reality. A proprietary databank of priors (by market, industry and channel) gives you a credible starting point fast, even on thin data; your own data then sharpens it, and you can watch the prior give way to the posterior.

03

A model you can talk to

An AI assistant turns the statistics into plain language: which channel improved most, why a result is uncertain, what happens if you move budget, and a summary you can send to your CMO.

  • Time-varying effectiveness
  • Channel contribution
  • Return on spend, with honesty
  • Lift-test calibration
  • Holdout validation
  • Diminishing-returns curves
  • Budget optimiser
  • What-if scenarios
  • Prior-powered fast start
  • The AI assistant

Every figure is directional and shown with its uncertainty — the estimate, the range around it, and how confident the model is. Usefully honest beats falsely precise.

And what it won’t do. No user-level tracking, so no “attribution”; no guaranteed or exact ROI; no real-time prediction of your sales. Time-varying effectiveness is modelled carefully so it reflects genuine change — not price, promotion, seasonality or competitor moves leaking in — and the budget optimiser stays within the spend levels your data actually supports. Where the data can’t carry a question, we say so.

The method, for those who want it

Impact is a Bayesian marketing-mix model built on PyMC-Marketing. It models adstock (carryover) and saturation (diminishing returns) per channel, and estimates effectiveness as time-varying coefficients — regularised so the trajectory reflects real movement rather than noise. Priors are elicited from a databank of prior fits (by market, industry and channel, each weighted by how many models informed it); ROIs are then calibrated to lift / incrementality tests and validated out-of-sample. The complexity is real — we keep it under the surface, and let you open it when you want to.

Join the waitlist Impact is in development.

Who it’s for

For brand leaders, marketers, strategists, insight teams and the agencies who serve them — anyone who has to defend a budget, direct a strategy, or explain a result and wants evidence rather than anecdote.

For agencies

Built to run across your whole client roster.

Resonance and Impact give your team a view of the brand most clients don’t have — how AI describes and recommends it, and what their spend is really earning — whether you’re defending a recommendation, proving the work, or winning the pitch.

A workspace per client

Run every brand you serve from one place — each with its own evidence, signals and assistant, kept cleanly separate. Switch context without losing it.

Client-ready outputs

Export decision-ready summaries and signals your team can drop straight into a plan, a QBR or a pitch — legible enough to forward without a translation layer.

Your brand on it

On request

Co-branded and white-label outputs so the work carries your studio’s name, not just ours.

Talk to us about agency access

Common questions

The things buyers ask us first.

Is this statistically significant, or just directional?

Directional — and deliberately so. Every signal shows the evidence and confidence behind it: the sample and coverage of the survey, the recency of the search and AI evidence, and how consistent the sources are. It’s built to tell you which way to move and what to look at first, not to pose as a precise measurement. Thin evidence is flagged, never smoothed over.

Where does the survey data come from — and will it clash with my existing tracker?

Surveys are commissioned with real respondents through Cint, a major respondent marketplace, with questions customised to your brand and category. If you already run a tracker we can take it over and onboard your history — keeping your audience definitions, segmentation and markets so your trends stay consistent. It replaces the tracker rather than running beside it, so there’s no “paying twice” and no conflicting numbers. (The demo uses synthetic data, clearly marked.)

Which markets and languages can you cover?

Search and AI audits run in your markets and languages; survey fieldwork runs wherever Cint has reach, which is most of the world. The demo workspace is built on the UK. We’ll confirm exact coverage for your market set before you commit.

How long does it take, and how much of my team’s time?

Setup is a short conversation, not a project — most of the work is ours. The search-and-AI read is quick; a commissioned survey takes weeks (versus the months a tracker takes to stand up). For Impact, a spreadsheet of media and sales history is enough to begin.

How is our data handled?

Your data stays yours and is held securely — including the sales data Impact ingests. We’ll walk your team, and your security or procurement people, through exactly how it’s stored and used before anything moves.

What does it cost?

Pricing depends on scope — which modules, how many markets, and how often you run. Tell us what you need and we’ll be straight about the cost; no surprises.

Do you have clients and case studies?

We’re early, and working with our first cohort of brands. Rather than borrow logos or invent numbers, the worked example uses a fictional brand on clearly-marked synthetic data — so what you see is the real instrument, honestly labelled. Ask us what we can show you.

Something we haven’t answered? hello@naras.ai — or ask in the form below.

Two questions. One platform. Real answers.

See how naras reads your brand and your spend — in a short, tailored walkthrough.

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Get in touch

See naras on your brand and your spend.

Tell us a little about you and we’ll set up a short, tailored walkthrough. No slides — the actual instrument.

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