Amazon · Dayparting
Schedule Amazon bids by the hour.
Most accounts run the same bid 24 hours a day. ADFIXER reads your hour-of-day and day-of-week conversion data, then schedules bids and budgets so spend rises during peak windows and drops during slow hours.
Conversion heatmap
Last 90 days · ROAS by hour × weekday · UTC−5
−43%
slow-hour spend
+19%
ROAS lift, 30d
The problem with flat bids
3 AM clicks cost the same as 7 PM clicks.
Amazon does not discount your bids overnight. If you bid the same number across all 168 hours of the week, you pay peak-window prices for off-hour traffic.
01 · Flat-bid accounts
38%
of ad spend lands outside your top conversion windows.
02 · ADFIXER cohort, n=1,200
2.4×
gap between best-hour and worst-hour ROAS for typical SKUs.
03 · Overnight click cost
11pm–5am
average account spends $4 of every $10 in this window.
How it works
Four steps to a time-aware schedule.
The setup runs in four steps. Any window can be overridden manually at any point.
Profile your week
ADFIXER analyzes 30 to 90 days of hourly conversion data per ASIN, by day of week, hour, and marketplace.
Find your windows
The model identifies high-ROAS windows, slow overnight hours, and the shoulder periods between them.
Schedule bids
Bid multipliers and budget caps apply per slot. Typical settings push 1.4× at peaks and 0.6× overnight.
Adapt every week
Patterns shift with seasonality and lifecycle. The schedule re-fits weekly so it stays current.
Scheduler
The 24-hour bid curve, side by side.
Switch presets to see how ADFIXER shapes a 24-hour bid curve. In the app, you fine-tune each slot and ASIN individually.
Sample ASIN · last 30d
Peak +50% · Dead −60%
PEAK
12 hours
multiplier 1.2×–1.9×
DEAD
5 hours
multiplier 0.2×–0.6×
SHOULDER
7 hours
close to baseline
Features
Controls down to the hour.
Most dayparting tools advertise hourly resolution. ADFIXER makes it usable day to day.
Hourly granularity
Schedule bids and budgets at the hour level. 168 slots per week, per ASIN.
Timezone-aware
Peaks follow the buyer's local clock. EU, US, JP, and AU handled per marketplace.
Per-ASIN profiles
Each product has its own buying rhythm. The schedule fits to each ASIN's signal.
Auto-fitting weekly
Patterns drift over time. The model re-reads recent data every week to keep pace.
Event boost mode
Apply a temporary surge curve over the base schedule for Prime Day, BFCM, or a launch.
Manual overrides
Lock any hour at a fixed multiplier. The model respects every override on each re-fit.
The impact
Same budget, allocated to better hours.
Dayparted accounts spend less during slow hours and bid up during peaks, lower TACoS without raising total spend.
Flat bid vs Dayparted
90-day median · 240 accounts · indexed to flat = 100
Patterns we see
Different products, different rhythms.
A handful of patterns show up repeatedly across thousands of fitted schedules. Yours is likely one of them.
Two daily peaks at 9–11 AM and 7–10 PM
Strongest conversion at 9–11 AM and 7–10 PM. Minimal between 1–4 AM. Friday night and Sunday evening over-perform the weekly average.
Weekday window, 9 to 5
Buyers research from work desks. Weekends convert at 30–40% of the weekday rate. Monday mornings are the weekly peak.
Q4 ramps from October 15
Conversion windows widen as deadlines approach. The final 72 hours before each holiday outperforms any other window in the year.
Month-end paycheck spike
Days 28–3 of the month over-perform by 22%. Dayparting accounts schedule budget pulses against this cycle.
Stop paying peak prices at 3 AM.
Let ADFIXER fit a schedule to your real conversion data. Free for 14 days, no card required.