beyond data
    Marketing Spend Optimisation

    Due North

    “It's incredible… we're looking at up to 30% reduction in wasted click spend for our customers.”

    Ben Hirons, Founder & CEO, Melbourne

    Find the 20-30% of your paid media budget funding search terms and creatives that will never convert.

    Outcomes

    What changes once this is in

    Up to 30% reduction in wasted click spend

    Validated at Due North, a Melbourne performance-marketing agency running the system across client Google Ads accounts. The wasted spend comes mainly from irrelevant search terms and negative-keyword gaps the platform never flags.

    ROAS decay caught in days, not months

    Campaigns drifting down in return on ad spend are flagged inside the first week of decay. The intervention happens before the quarter's budget is burnt, not after the board meeting.

    Your marketing manager stops firefighting

    Instead of scanning six dashboards every morning, they open one queue. The system tells them what changed, why it matters, and what to do. Analyst-grade analysis without an analyst.

    Agency conversations move from invoices to outcomes

    For agencies, monthly client reviews shift from defending fees to showing saved spend and recovered margin. Client churn drops. Retainer conversations get easier.

    Marketing Spend Optimisation is an AI layer over your Google Ads, Meta, and LinkedIn accounts that watches every campaign daily, flags the queries, keywords, and creatives burning budget, and routes the specific intervention to your marketing manager before the monthly report lands. It is built for growing brands and the agencies that run them, not for enterprise ad-ops teams.

    The Problem

    What usually breaks

    You are paying for clicks that will never convert. Every week. The average paid-search account wastes 20-30% of its budget on search terms the buyer never intended, negative-keyword gaps nobody has audited, and ad groups quietly drifting on ROAS. Nobody inside the business sees it until the month-end report, by which point the money is gone.

    The data to catch this already exists. It is sitting in Google Ads, Meta Ads Manager, GA4, and your Shopify or HubSpot back-end. What's missing is the thing that reads all of it together, daily, and tells your marketing manager what to do next. Agency reports describe the past. Platform recommendations optimise for platform revenue. Neither closes the loop back to profit.

    That is the gap this solution fills. One system, reading everything, acting weekly.

    In Your Business

    How this lands inside your operation

    Your marketing manager already opens Google Ads every morning. They are competent. They are not a data scientist, and they should not need to be. This solution runs quietly in the background across your ad platforms, CRM, and commerce stack. Each morning it surfaces a short list: the search terms to negate, the ad groups with ROAS decay, the creatives showing fatigue, and the CPA drifts worth a closer look. One brief per morning, in Slack or email, with the recommended action next to each item.

    For agency owners managing $50k to $500k a month of client spend, the same system runs per client account. It turns the end-of-month conversation from invoice defence into outcome reporting.

    This is for you if…

    • Growing eCommerce and DTC brands running $50k-$500k a month of paid media with an in-house marketing manager and no data team
    • Digital marketing agencies managing multiple client accounts who want to turn reporting into outcomes
    • Multi-site retailers and franchise networks running paid media at head office for branches that never see the data
    • Tourism, hospitality, and education groups with seasonal paid-media budgets they cannot afford to waste
    • Marketing directors tired of monthly retros where the money is already spent

    This probably isn't the right fit if…

    • Brands spending under $20k a month on paid media. The system earns out at scale.
    • Organisations looking for a pure reporting tool. This is built to drive weekly action, not weekly slides.
    • Teams with a mature in-house data science function already running custom media-mix models.
    Signals to actions

    What we monitor and act on

    Below is the live list of signals the system watches across a paid-media account, and the action it recommends when each one fires. Every recommendation lands with your marketing manager, not the algorithm. No auto-apply.

    SignalWhat the system seesRecommended action
    Wasted click spend by querySearch terms driving clicks but zero conversions over a statistically meaningful windowAdd as negative keywords at campaign or account level. Dollar saving quantified.
    CPA driftCost per acquisition trending up against the 30-day baseline for an ad groupInvestigate bid strategy, audience overlap, or creative fatigue. Bid adjustment suggested.
    Negative-keyword gapsHigh-impression queries that are clearly off-intent but not yet blockedBulk-add negatives, grouped by theme, with impression and cost context.
    ROAS decay by ad groupReturn on ad spend falling week over week against the rolling baselinePause, rework creative, or reallocate budget to the ad group outperforming.
    Creative fatigueCTR and conversion rate decaying on a specific ad while impressions holdRotate creative. Brief the designer with the exact ad, the decay window, and the audience.
    Audience saturationFrequency rising on Meta while incremental conversions flattenRefresh audience or shift budget to prospecting.
    Landing-page mismatchHigh click-through but weak conversion on a specific URL pairingFlag to the CRO team. Suggest A/B test or redirect.
    Budget pacing anomaliesSpend running hot or cold against plan by channel or campaignRebalance daily caps. Alert if monthly burn will overshoot before month-end.
    How It Works

    The engagement, step by step

    1. 1

      We connect to your Google Ads, Meta, LinkedIn, GA4, and commerce or CRM data through the platform APIs.

    2. 2

      The system builds a baseline of what "good" looks like per campaign, ad group, and audience in your account.

    3. 3

      Daily, it scores every search term, keyword, and creative against that baseline for waste, drift, and fatigue.

    4. 4

      Anomalies are surfaced to your marketing manager as a prioritised action queue, not a dashboard.

    5. 5

      Each recommendation carries the expected dollar impact and the exact change to make in-platform.

    6. 6

      Accepted and rejected actions feed back into the model, so next week's recommendations get sharper.

    7. 7

      Monthly, the system produces a plain-English outcome report for the board or the client.

    Capabilities

    The capabilities behind this

    AI Development

    AI components for trusted decision systems, with traceable evidence, evaluated outputs and explicit human approval boundaries.

    Learn more

    Advanced Analytics & ML

    Forecasting, simulation and optimisation for consequential decisions, with visible uncertainty and quantified trade-offs.

    Learn more

    Insight-to-Action Systems

    Connect evidence, scenarios and quantified trade-offs to human approval, approved action and outcome learning.

    Learn more
    Proof

    What this looks like in the field

    Ben Hirons, Founder & CEO of Due North

    Due North

    Digital Marketing

    “It's incredible… we're looking at up to 30% reduction in wasted click spend for our customers.”
    • AI monitoring of Google Ad campaigns and keywords, surfacing insights directly to ad managers
    • Automatic identification of up to 30% of wasted ad spend on irrelevant search terms
    • Early detection of ads trending down in profitability — intervention before the loss lands
    Read the full study
    Common Questions

    Frequently asked

    Let's talk about Marketing Spend Optimisation.

    30-minute call, no slides, no obligation. We'll tell you plainly whether this is the right fit for what you're trying to do.

    Read the Due North story

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