Spend that lands in hour-of-day buckets that historically convert below threshold. Pause or apply negative bid modifier.
At a glance
Spend in hour-of-day buckets where conversion rate is < 1%, typically the dead overnight hours when shoppers click but rarely buy. The dayparting-pruning workflow, identify low-CR hours and apply a negative bid modifier or pause the campaigns during those windows. Industry typical: 4-12% of total ad spend lands in low-CR hours. Recoverable with hour-of-day bid scheduling.
| The formula | SUM(cost) for hours where the 30-day rolling conversion rate is < 1%. The 1% threshold is a generous floor; many categories have 2-3% account-blended CR, so the dead-hour cohort is genuinely low-quality. |
| Reports API endpoint | POST /reporting/reports with reportTypeId=spCampaigns aggregated by hourOfDay. Hour-of-day reports require Amazon Advertising’s hourly granularity (available on Sponsored Products; partial on Sponsored Brands). |
| What “low-CR” means | A specific hour bucket where (clicks > 0) AND (orders / clicks < 1%). The hour-bucket is in PT (Pacific) regardless of merchant location, Amazon’s reporting backend timezone. |
| ACOS vs ROAS framing | A low-CR hour is mechanically going to be high-ACOS / low-ROAS for that window. The fix is bid-modifier or pause, not budget-cut. |
| Attribution model | Last-click within Amazon ecosystem, 14-day click window. The hour bucket is the click hour; the conversion may land days later but is attributed to the click hour. |
| Brand vs non-brand keyword scope | Branded clicks tend to convert at any hour (people searching the brand name buy quickly). The waste pattern is concentrated in non-branded, late-night browsers click but don’t buy. |
| Sponsored Products vs Brands vs Display vs DSP | SP exposes hour-of-day reliably. SB and SD have partial hour reporting. DSP uses different scheduling controls (day-parts in DSP service agreements). The card focuses on SP. |
| Currency | Account currency only. |
| Amazon-only attribution gap | Not specifically relevant, dayparting is about timing, not attribution path. |
| Time window | 30D rolling. Hour-of-day patterns are usually stable, so 30D smoothing avoids over-fitting on a single-week anomaly. |
| Alert trigger | >$0 spend in hours with <1% conv rate. Drives sentiment_key: zero_conversion_spend. The threshold is configurable (some accounts use 0.5% or 2% depending on baseline CR). |
| Roles | owner, marketing, finance |
Calculation
Calculated automatically from your Amazon Ads data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
A US home-goods seller, 30-day window covering 14 Mar 26 to 12 Apr 26. Account-blended CR is 4.8%. The card flags spend in 5 hour-buckets below the 1% CR threshold.| Hour (PT) | Clicks (30D) | Orders (30D) | CR | Spend | Status |
|---|---|---|---|---|---|
| 02:00-03:00 | 1,240 | 6 | 0.48% | $185 | Below threshold, prune |
| 03:00-04:00 | 980 | 4 | 0.41% | $146 | Below threshold, prune |
| 04:00-05:00 | 720 | 3 | 0.42% | $108 | Below threshold, prune |
| 05:00-06:00 | 650 | 4 | 0.62% | $94 | Below threshold, prune |
| 22:00-23:00 | 2,400 | 18 | 0.75% | $358 | Below threshold (but high volume, investigate) |
| Total dayparting waste | 5,990 | 35 | 0.58% | $891 | 3.3% of total spend |
| Comparison: peak hours (in-window) | |||||
|---|---|---|---|---|---|
| 20:00-21:00 | 4,200 | 220 | 5.24% | $640 | Healthy peak |
| 12:00-13:00 | 3,800 | 195 | 5.13% | $580 | Healthy peak |
| 08:00-09:00 | 3,400 | 158 | 4.65% | $510 | Healthy morning |
- The 520-650 (you lose some legitimate orders by reducing bids, so recovery is partial).
- The 22:00-23:00 hour is a special case. CR is 0.75% (below threshold) but click volume is 2,400, high enough that even at 0.75% CR, this hour contributes 18 orders. Pausing entirely loses real conversions. The bid-modifier (-25%) preserves some volume while reducing waste.
- The peak-hour comparison shows what “good” looks like. 20:00-21:00 PT (US prime evening shopping) converts at 5.24%. 10× the dead-hour rate. The fix isn’t to spend less, it’s to redistribute spend toward the high-CR hours.
- Dayparting waste rises during Prime Day. Bargain hunters click everywhere at all hours; expect 02:00-06:00 spend to inflate 50-100% during sale weeks. Don’t react in-window; review the next month after the promo cools.
- B2B-adjacent products show different patterns. Office furniture, professional supplies, and similar B2B-leaning categories peak at 09:00-17:00 PT and have low-CR overnight; consumer goods peak at 20:00-22:00 PT. Configure thresholds per category; the default 1% CR floor may be too high for niche or seasonal products.
- Total dayparting waste 5-15% of spend = healthy. Recoverable with bid modifiers.
- Total < 3%: probably already optimised, or low-volume account where every hour matters.
- Total > 15%: structural over-bidding in dead hours; auto-campaigns are spending where they shouldn’t.
- Pattern shifting suddenly (waste rising sharply): seasonality (e.g. tax-prep traffic at unusual hours) or competitor entered the auction during low-volume periods.
- Same hours flagged month after month: candidate for permanent dayparting schedule.
Sibling cards merchants should reference together
| Card | Why pair it with Dayparting Waste |
|---|---|
| Spend by Hour | The full hour-by-hour spend breakdown. |
| Conversion Rate by Hour | The CR side of the same data. |
| ROAS by Hour | The efficiency lens. Low-CR hours are also low-ROAS hours. |
| Day-of-Week Spend Mix | The day-of-week analogue of this card. |
| Bid-Modifier Coverage | Tracks whether the dayparting fixes have been applied. |
| Wasted Spend | Keyword-level waste; this card is hour-level waste. |
| Zero-Conversion Spend | Campaign-level waste. The three (keyword, campaign, hour) are independent slicings. |
| CPC by Hour | If low-CR hours also have high CPC, the waste is double. |
Reconciling against the vendor’s own dashboard
Where to look in Amazon Ads Console: Amazon Ads Console > Reports > Sponsored Products > Performance Over Time, choose hour-of-day granularity. The total in low-CR hour buckets should match this card to within ~1%. Amazon Ads Console > Campaign Manager > [Campaign] > Bidding shows day-part bid adjustments where set. Amazon’s native dayparting controls are limited compared to Google Ads, they’re per-campaign and have only 24 hour-buckets per day-of-week. Amazon Ads Console > Recommendations, sometimes flags “hours with low conversion” but inconsistently. Why our number may legitimately differ from Amazon Ads Console:| Reason | Direction of divergence | Why it happens |
|---|---|---|
| Timezone. All Amazon Advertising reports use PT (Pacific). Vortex IQ aligns to PT for Amazon Ads. | None when both PT-aligned. | Amazon’s reporting backend is in Seattle. Critical for dayparting: a US-East merchant must remember 02:00-05:00 PT = 05:00-08:00 ET (early morning ET, dead-hour PT). |
| Hour-bucket granularity. Amazon’s hourly reports have ~99% completeness on Sponsored Products; rare hours may be missing in low-volume sub-accounts. | This card may show slightly less spend in those hours. | Hourly granularity is best-effort on Amazon. |
| Report-generation latency (1-3 hours). | Today’s hour-buckets are provisional for ~24h. | Amazon batches report builds. |
| Threshold definition. This card uses CR < 1% as the cutoff; the Console doesn’t have an equivalent canned filter. | Manual recreation in Console requires custom filters. | Intentional design. |
| API rate limits. Hour-of-day reports are heavier than daily reports; large accounts may have slower refresh. | Stale by up to 1 refresh cycle (~4h). | Reports are paginated and rate-limited. |
| Card | Expected relationship | What causes legitimate divergence |
|---|---|---|
amazon_sp.amzn_sp_total_sales | Marketplace orders correlate with PT-hour conversion patterns. The peak hours in this card should match the peak hours in SP Total Sales by Hour. | None expected. |
google_ads.gads_dayparting_waste | Cross-platform analogue. Patterns may differ. Google Ads sees full-web traffic; Amazon Ads sees marketplace shoppers (often more concentrated in evening hours). | Different audiences, different patterns. |
shopify.total_revenue | DTC site has its own dayparting pattern. The merchant’s Shopify peak hours may be 1-2 hours earlier than Amazon’s (DTC shoppers often browse before bed; Amazon shoppers commit during peak evening). | Independent traffic sources. |