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    Signal

    One dashboard where organic search and Meta spend stop arguing — rankings, ROAS and budget pacing wired to the same source of truth, refreshed every hour.

    Year
    2026
    Disciplines
    SEO, Meta Ads, Analytics
    Platform
    Web
    Brief
    Sample client

    Use Signal now

    Signal on desktop: Growth engine for a DTC brand

    01Context

    Verre was flying blind across four tools: Ads Manager for spend, Search Console for rankings, GA for sessions, a spreadsheet to reconcile the lies. We built Signal — a growth cockpit fed by the Meta Marketing API and Search Console API, normalised through a BigQuery + dbt pipeline, served by a Next.js app on Vercel.

    02Strategy

    Hourly ETL pulls ad-set spend, CPM and conversions from Meta; a nightly job snapshots keyword positions. dbt models blend them into one attribution table, so ROAS is computed the same way everywhere — no more channel-flattering math.

    • Meta Marketing API + Search Console ingestion
    • BigQuery warehouse, dbt models, tested SQL
    • Budget pacing with automatic ad-set pause rules
    • Server components, edge-cached KPI reads

    03Design

    Signal, desktop layout
    Desktop, 1280 wide. Captured from the running build.
    Signal, phone layout
    Phone, 430 wide. Same build, same data.

    04Engineering

    Hourly workers pull Meta Marketing API and Search Console into BigQuery; dbt models normalise attribution, and a Next.js app on Vercel reads pre-aggregated marts so every number is one query deep.

    • Meta + GSC ingestion with token rotation
    • dbt-tested models — ROAS defined once, everywhere
    • Pacing rules auto-pause underperforming ad sets
    • Looker Studio marts for the founders' weekly

    Also considered. GA4 + spreadsheets — rejected: sampled data and channel-flattering attribution.

    05Details

    The mechanism underneath, as a working model. Press the buttons.

    lab / data / blended attribution

    Meta spend and organic search normalised in one dbt model, so ROAS is defined once and pacing rules act on it.

    BigQuery · dbtOpen in the Lab

    Loading the model

    Figures inside a model are simulated to show how the mechanism behaves. They are not production measurements.

    06What shipped

    9 modules are in the build below. Each one works.

    • 01Campaign toggles and CRUD
    • 02Pacing against time of day
    • 03A rule builder that actually fires
    • 04Attribution breakdown
    • 05Organic keyword sparklines
    • 06Alerts
    • 07Audiences and lookalikes
    • 08Creatives with A/B tests
    • 09UTM builder and report builder

    07Technology

    • Next.js
    • Meta Marketing API
    • Search Console API
    • BigQuery
    • dbt
    • Node.js
    • Vercel

    This is the kind of work we do under SEO & Meta Ads.

    Now use it.

    This is Signal, the whole application. Continue as the sample user, change things, reload. Your data stays in this browser and resets from Settings, then Data.

    yakooha.com/demo/signal
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    Signal: Growth engine for a DTC brand

    A full application, not a recording. Sign in as the sample user; your data stays in this browser.

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