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    December 24, 20254 min readBy Chris Avery

    Why Q4 PPC Performance Is a Terrible Baseline for January Decisions

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    The January Trap

    Every January, the same pattern emerges.

    Brands look at their Q4 numbers and plan their Q1 strategy based on what "worked." They set ROAS targets from December. They scale campaigns that performed during peak. They make budget decisions based on seasonal data.

    Then reality hits.

    Efficiency drops. Volume disappears. Campaigns that seemed optimised suddenly struggle. And the question becomes: what changed?

    Nothing changed. Q4 was never reality. It was a seasonal distortion. And using it as a baseline guarantees disappointment.


    Why Q4 Lies to You

    Demand Inflation

    In Q4, demand exceeds supply. More buyers are actively searching with purchase intent. Conversion rates rise not because your ads improved, but because the market shifted.

    This inflates every metric:

    • Click-through rates — More intent means more clicks on the same ads
    • Conversion rates — More buyers means more purchases from the same traffic
    • ROAS — Higher conversion rates and AOVs inflate efficiency

    None of this reflects your advertising skill. It reflects seasonal demand. In January, demand normalises. The inflation disappears. Your "great" performance reverts to baseline.

    Auction Softening (Then Hardening)

    The auction dynamics in Q4 are complex:

    • Early November: Some advertisers pull back, waiting for Black Friday
    • Black Friday week: Everyone piles in, CPCs spike
    • December: Sustained high competition, but also sustained high demand
    • January: Demand drops faster than competition, efficiency collapses

    If you averaged your Q4 CPCs and used them to model January, you'd be wrong. January auctions behave differently—often worse efficiency at lower absolute spend.

    Brand Bias

    During Q4, brand search volume spikes dramatically. Customers who've already been influenced by your non-brand activity search for your brand directly.

    Your brand campaigns intercept these searches and claim the conversions. The result:

    • Brand ROAS looks exceptional
    • Non-brand appears less efficient (but created the demand)
    • Your channel mix analysis is distorted

    In January, brand volume drops. Non-brand has to work harder. But if you cut non-brand based on Q4 data, you'll starve acquisition.

    PMAX Misreads

    Performance Max thrives on signal density. More conversions = better predictions = better performance.

    Q4 provides abundant signals. PMAX campaigns that struggled in Q3 suddenly look competent. The algorithm appears to have "learned."

    It hasn't. It's benefiting from easier conditions.

    In January, signals thin out. PMAX performance degrades. Campaigns that seemed optimised reveal themselves as dependent on seasonal volume. The algorithm doesn't get worse—it just loses its crutch.

    False Confidence

    All of these factors combine into one dangerous outcome: false confidence.

    Brands believe their advertising is working well. Agencies point to Q4 numbers as proof of competence. Budget decisions get made based on inflated metrics.

    Then January arrives, and everyone scrambles to explain why performance "suddenly" declined.

    It didn't suddenly decline. It returned to reality. The decline was baked in the moment Q4 became the baseline.


    What January Actually Tells You

    January is closer to reality than Q4. It's not pretty, but it's honest.

    Conversion rates normalise. The buyers who remained after Q4 are your actual audience—not seasonal gift-givers.

    ROAS reveals truth. Without demand inflation, your efficiency reflects genuine advertising performance.

    Weak campaigns surface. Campaigns hidden by aggregate Q4 performance become visibly problematic.

    PMAX shows its real face. Without abundant signals, you see what the algorithm actually delivers.

    January isn't a failure. It's a diagnostic. The brands that treat it that way make better decisions.


    How to Use Q4 Data Correctly

    Q4 data isn't useless. It just needs interpretation.

    Compare to last Q4, not to Q3

    Year-over-year Q4 comparison tells you something useful. Q4-to-Q3 comparison is meaningless noise.

    Look at relative performance, not absolute

    Which campaigns outperformed their seasonal peers? Which products gained share during peak? Relative performance carries forward; absolute numbers don't.

    Discount ROAS by 30-50%

    As a rough heuristic: whatever ROAS you achieved in Q4, assume January will be 30-50% lower. Plan accordingly.

    Audit before scaling

    If Q4 made you confident about scaling spend, stop. Get an audit first. Understand what actually drove performance before committing January budget.


    The Baseline Question

    When planning January, ask:

    "If I remove seasonal demand inflation, brand bias, PMAX signal density, and competitive shifts—what performance is actually repeatable?"

    That's your baseline. Not the dashboard numbers. Not the Q4 reports. The underlying, normalised, sustainable performance level.

    If you don't know what that is, you're guessing.

    And guessing in January is how brands destroy Q1.


    Want a clear-eyed view of your account's real performance? Our Google Ads Audit strips away seasonal distortion and shows you what's actually working. Or read our Spend Philosophy to understand how we think about advertising investment.

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