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Marketing intelligence, made legible.

See how strong your brand is, and what your marketing is doing to it.

naras reads how strong your brand is, and whether you’re found and recommended by people, by search and by AI. Then it connects that to what your media earns: return on spend, cost of acquisition, growth. One picture, honest about what it doesn’t know.

Greater than the sum of its parts.

naras replaces brand tracking, creative pre-testing and marketing mix modelling, then combines them with a campaign advisor that turns the evidence into better briefs. Every part explained by an assistant that helps you, your team and your agency understand, and act.

Brand strength, availability & AI presence

Salience, distinctiveness, perception and reputation, plus whether people, search and AI recommend you. Every signal shown with its confidence.

Resonance turns the survey, search and AI evidence about your brand into ten clear signals: where you're losing ground, and what to fix first. Each signal opens into its evidence and ends in a recommended action, with the assistant on hand. It's an audit you re-run when you need a read, not an always-on tracker.

Fig. 1aBehind Distinctiveness · the trait landscape
See it in the demo
narasAIthe desk · one assistant, every lensAsk it to remix your media plan, walk you through running a test, or explain what a diagnostic means. Every answer grounded in your workspace's numbers and sources, never invented.Fig. 1 · Illustrative: five lenses on one workspace.

A tracker reads the brand. A mix model reads the spend. The naras workspace joins them, what the market thinks to what your spend earns, and prices confidence into every move it recommends.

The best result isn’t always the best bet.

Two strategies. A promises the higher return, on a range so wide it dips below break-even. B promises a little less, on evidence you can bank. Most tools hand you the midpoints and call it a plan.

naras shows the range behind every number, and builds that confidence into scenario planning. We don’t chase the best-looking result: we back the results we’re confident in, and scale tentatively into the ones we’re not.

Fig. 2Return on spend · two strategies · range, not midpoint
Two strategies, each shown as its full range with the mean marked. A's average is higher; B's worst case still clears break-even. The range, not the midpoint, makes the decision.

One connected picture

Brand and spend, on one bench.

The people-vs-machines read: what your customers think, set against what search and AI say. Every signal with its trend and confidence, the weakest flagged, and the ranked moves to make. One workspace, one read.
Fig. 3The Overview · signals, impact, moves
Every signal on the board with its range and confidence, the weakest flagged; media impact blended beneath; the ranked moves alongside, with confidence priced into every one.

How you run it

Read. Plan. Act. Measure. React.

Strategy is not a report, it’s a loop. naras runs the whole cycle on one bench, and every turn of it is priced with confidence.

Fig. 4The lifecycle · one continuous loop
ONEWORKSPACEREADPLANACTMEASUREREACT
  1. 01

    Read

    Ten signals with confidence read the brand against its competitor set, and the weakest is flagged first.

  2. 02

    Plan

    The advisor turns the evidence into a working brief, and scenarios play the plan forward with the range shown.

  3. 03

    Act

    You make the move: budgets shift, creative runs. It proposes; you decide, and an overrule is a recorded decision.

  4. 04

    Measure

    Impact models what the spend earned, channel by channel, as ranges against break-even.

  5. 05

    React

    New waves and results land, plans re-score, and the next move ranks itself. The loop turns again.

The read, opened

Every signal is a row on one board: its trend, its rank, its confidence. Open one and the read unfolds in place: Brand Salience at 86, high confidence, #5 of 29 in the set.

Fig. 5The board · one row opened
One row per signal; open it and the read unfolds in place: the score, the rank in the set, and the confidence behind it.

The move, on tap

Ask the desk and get the move: shift about £20k a quarter from Meta (returning under 1×) into Google Search, for an estimated 2–4% uplift given as a range, never a promise.

Fig. 6The desk · ask, and the move composes
Ask, and the grounded move composes: the shift, its cost, the estimated uplift as a range, and the records it rests on.

The figures on this page are drawings of the product, and the worked numbers are illustrative. Your workspace runs the loop on your own evidence: a survey commissioned for your brand, plus live search and AI audits.

The stack, consolidated

Four tools. One workspace.

naras replaces the point tools around brand and media effectiveness, and joins what they never could: what the market thinks to what your spend earns.

  • Replaces

    Brand tracking

    An always-on tracker and a quarterly deck.

    naras Resonance

    Ten signals with confidence, each opening into its evidence and ending in a recommended action. An audit you re-run when you need a read.

  • Replaces

    AI visibility monitoring

    A point tool watching one assistant.

    naras Resonance · AI signals

    Weekly audits of the assistants buyers actually ask, across three vendors and per market, read into the same board as the survey.

  • Replaces

    Creative pre-testing

    Panels, fieldwork and weeks of lead time.

    naras Synthetic Research

    Concepts and messages read as ranges across three AI models on a simulated population, validation-gated, in minutes not weeks.

  • Replaces

    Econometric modelling

    A consultancy engagement and a static report.

    naras Impact

    Channel returns with credible ranges, calibrated against lift tests and held-out periods, explained in plain language.

One method under all four: evidence first, ranges always, and confidence priced into every move it recommends.

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; a spreadsheet of media and sales history for Impact. A short setup conversation, not a project. Most of the work is ours, and your data stays yours.

    Already measuring? Tracker history and audience definitions carry over, and past lift tests sharpen the model's starting point.

  2. 02

    naras gathers and models

    Resonance collects live evidence and audits the AI systems buyers ask; Impact models what's driving your results. 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.

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

  • SurveyCommissioned · real respondentsBrand-health and perception data from a survey commissioned for your brand (synthetic in the demo).New waves field in weeks, whenever you need a fresh read, not on a vendor's calendar.
  • SearchGathered liveWhat organic results, Knowledge Graph and Google Trends say about you.
  • AI OverviewGathered liveHow Google’s AI summary treats you in category searches.
  • AI auditsGathered liveWhat OpenAI’s, Anthropic’s and Google’s models say when asked to recommend in your category, refreshed weekly.

Ten signals

  1. 01Brand Salience
  2. 02Perception Alignment
  3. 03Competitive Distinctiveness
  4. 04AI Visibility
  5. 05AI Advocacy
  6. 06Model Agreement
  7. 07Search AI Visibility
  8. 08CEP Coverage
  9. 09Demand Signal
  10. 10Reputation Signal

Built to tell you which way to move and how hard to lean on it: the range, not just the number, priced into every recommendation.

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

Every result comes with its range and its confidence: we show the spread, 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, on any device, and built to WCAG AA accessibility. Intelligence you actually want to open.

Common questions

The things buyers ask us first.

How rigorous is this, and how far should I trust the numbers?

We never collapse a result to one number and hide its margin. Every signal carries its confidence: the sample, recency and consistency of the evidence behind it. Impact's Bayesian model goes further and gives you the estimate, the range, and how much of that range your data actually supports. A wider range means a more cautious move, and that's priced into every recommendation and into scenario planning. Thin evidence is flagged, never smoothed over.

Is “AI visibility” actually a proven driver of growth?

We treat it as an emerging signal, not a settled KPI, and we say so. We show where AI represents you: whether ChatGPT, Claude and Google’s AI mention, rank and recommend you when buyers ask, because more of them now start there. We don’t claim a fixed link to sales, and LLM answers shift with each model update, so it’s an early-warning indicator to watch, not a number to game. It sits alongside salience and distinctiveness, which have decades of evidence behind them.

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.)

What is a simulated panel? Is Synthetic Research real research?

It’s a hypothesis tool, and we’re precise about that. Respondents are synthesized from your workspace’s real survey data, never invented personas, and every question runs across three AI model families so no single vendor’s biases become the answer. Results come back as ranges, and a published validation against held-out human survey data decides what each cut may claim; anything unchecked is withheld and named. Use it to narrow the field in minutes, then validate the winner with real research. It never replaces fieldwork, and it never produces a brand-health number.

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, and kept separate from your other clients?

Your data stays yours, encrypted in transit and at rest, including the sales data Impact ingests. Every brand gets its own isolated workspace, unreachable from another’s by construction: the application only resolves data for the workspace you’re in, and the database enforces the boundary again with row-level security, so even a coding mistake can’t return another client’s data. We’re glad to take your security or procurement team through the architecture before anything moves.

Can my agency run naras across a client roster?

Yes. It’s a first-class shape, not an afterthought: every client brand gets its own workspace, kept cleanly separate, with its own evidence, signals and assistant. Exports are client-ready, so your team can drop them straight into a plan, a QBR or a pitch. Co-branded and white-label outputs are available on request. Talk to us about agency access.

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.

Get in touch

See it on your brand.

A short, tailored walkthrough of naras on your brand and your spend. No slides, just the actual instrument.

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