Kozan Digital Agency

    Free Tool — Based on Real Benchmarks

    Free Ad Timing Optimizer

    When should you run your ads? Stop wasting budget on dead hours. Get exact days, times and budget split to maximise ROAS — for your platform, industry and goal.

    No signup3 ad platformsHour-by-hour heatmapBudget split guide

    Ad Timing Optimizer

    Select your platform, industry and campaign goal to get a full timing recommendation.

    Device:

    What is the Ad Timing Optimizer?

    The Ad Timing Optimizer is a free dayparting tool that tells you when to run paid ads on Google Ads, Meta, and LinkedIn for maximum ROAS. It builds a day-and-hour heatmap based on real industry benchmarks, weighted by your platform, vertical, audience type, and campaign goal. The output is a concrete schedule — high-performance windows, dead hours to avoid, and a suggested budget split across the week — so you stop wasting spend on impressions that don't convert.

    Who it's for

    Paid-media managers running campaigns on Google or Meta, agencies optimising client accounts, ecommerce brands trying to lower CPC, and B2B advertisers on LinkedIn who need to align bidding with buyer behaviour. If your campaigns are running 24/7 on default settings, this is the fastest way to cut wasted budget.

    How to use it

    Pick your ad platform, industry, primary goal (sales, leads, awareness, app installs, etc.), and target audience or device. The tool returns a heatmap, top-performing time slots ranked by efficiency, an avoid list, and a budget-distribution recommendation by daypart. Use it as a starting point for ad scheduling and bid adjustments inside your ad platform. Run it monthly or when your campaign goal changes. Kozan's team also builds full Google Ads and Meta programmes if you'd rather have us manage the spend.

    Why dayparting improves ROAS

    Most ad accounts run on default 24/7 schedules because setting bid adjustments by day and hour feels manual and arbitrary without data to support the decisions. The Ad Timing Optimizer removes the arbitrary by grounding the schedule in benchmarks that reflect when buyers in your vertical actually convert. DTC ecommerce sees purchase intent spike in the evening when consumers browse leisure purchases on mobile. B2B software advertisers get better CPL rates early in the working week during morning hours, before prospect calendars fill and attention drops. Local healthcare ads peak around appointment-seeking moments: early morning before work and lunchtime during breaks. LinkedIn B2B campaigns see their highest-quality engagement on Tuesday through Thursday, during business hours when decision-makers are actively reading industry content. Applying a data-informed schedule before you accumulate your own conversion volume shortens the learning phase and protects daily budget during low-intent hours — two to three weeks of structured dayparting almost always produces a lower effective CPA than running flat budgets indefinitely and waiting for the algorithm to figure it out.

    Ad Timing Optimizer FAQ

    Common questions about dayparting, data sources, and how to apply the schedule in your ad account.

    Yes — no signup, no payment, no usage limits. The tool runs entirely in your browser and you can save or copy any output.

    The model is weighted by published industry benchmarks for Google Ads, Meta, and LinkedIn — broken down by vertical, audience type, device, and campaign goal. It's a sensible starting point, not a substitute for your own account data once you have meaningful conversion volume.

    Use it as a hypothesis to test, not gospel. Apply the high-performance windows for one to two weeks, measure your own ROAS or CPA, then refine. Industry benchmarks are averages — your specific audience may behave differently.

    Yes for budget planning and overall account pacing, but Performance Max doesn't let you set ad schedules at the campaign level. Use the optimiser to inform when you increase or decrease daily budget across the week.

    Monthly, or any time you change campaign goal, audience, or product category. Buyer behaviour shifts seasonally — a schedule that worked for Q4 retail may not work for Q1 B2B services.

    The tool returns recommendations in the audience's local time zone. If you're advertising to multiple regions, run the tool once per region and stagger your campaigns accordingly inside your ad platform.

    For account-wide testing, yes — Google Ads needs data across all hours to optimise. But once you have 4–6 weeks of conversion data, dayparting based on what actually performs almost always lifts ROAS and cuts wasted spend.