Most guides to managing dayparting across a portfolio treat all Amazon campaign types the same way: pull your hourly conversion data, identify the dead hours, suppress them, and watch your ACoS improve. The advice is not wrong for Sponsored Products. For Sponsored Brands, it can quietly cost you brand visibility and attributed revenue that never shows up in the hours you suppressed.
The core problem is that Sponsored Products and Sponsored Brands are different ad types operating under different auction dynamics with different relationships to time. Applying one suppression schedule to both treats them as interchangeable, and they are not. Understanding the distinction is what separates a dayparting setup that genuinely improves efficiency from one that improves SP metrics while eroding SB performance in ways that take weeks to notice.
Why SP and SB behave differently by hour
Sponsored Products show up when someone searches for something specific. The buyer has intent. They typed a keyword, Amazon ran an auction, and your ad appeared in a results grid or on a product detail page. The relationship between the hour someone searched and the hour they converted is relatively direct. When someone searches for a kitchen scale at 9pm and buys one, that conversion registers within minutes. The hourly data you pull reflects actual buyer behavior with a short lag.
Sponsored Brands work differently. They appear at the top of search results, often before a buyer has made up their mind about exactly what they want. An SB ad for a kitchen brand might surface to someone searching broadly for "meal prep containers." That impression plants something. Maybe the buyer converts in the same session. Maybe they come back two days later having thought it over. SB-attributed sales frequently carry a 1-to-3 day attribution lag, and some SB placements are designed explicitly for awareness rather than immediate conversion. The hour when the impression fired and the hour when the purchase happens are not always the same hour, or even the same day.
Sponsored Display adds another layer. Display placements reach buyers off Amazon, on third-party sites and apps, which means the impression timing follows content browsing patterns rather than purchase intent patterns. The conversion lag here can extend even further. For accounts running SB Video, the separation is even more pronounced: video impressions build brand recall that simply does not appear in same-session ACoS figures.
The mistake: identical schedules for different ad types
When teams apply the same suppression grid to SP and SB, the data they used to build that schedule was almost certainly pulled from SP campaigns. SP data is clean and direct: an hour with low spend and zero conversions over 30 days is genuinely a dead hour for Sponsored Products. Suppressing it is correct.
SB data looks similar on the surface but means something different. An hour with clicks and no same-session conversions for an SB campaign is not necessarily dead. It may be the consideration window during which buyers see the brand, browse the store, and come back to purchase during a different session. Pausing SB during those hours removes brand impressions at the exact moment buyers are in consideration mode. The attributed revenue from those impressions does not vanish immediately. It erodes over weeks as the brand's presence in the upper funnel thins out.
Parkway Home, a home goods brand, ran into exactly this when their team applied a unified suppression schedule to all campaign types at once. The SP efficiency gains they expected arrived. SB performance dropped 14% week over week. When they investigated, the suppressed hours corresponded with late-evening browsing sessions where buyers were considering purchases but not yet converting in the same sitting. After splitting the schedules, SB performance recovered and SP efficiency held.
Building separate schedules for each campaign type
The practical approach is to create two distinct dayparting rules in Off Hours: one scoped to your SP campaigns, one scoped to your SB campaigns. They can share some logic, but the suppression aggressiveness should differ meaningfully.
Sponsored Products: run aggressive suppression
For SP, the standard approach works well. Pull 30 days of hourly performance data broken down by hour of day. Look for hours with zero conversions across the full period. If an hour has delivered spend and clicks but no attributed orders over a month, suppressing it is a low-risk improvement. You are not giving up anything the data suggests was working.
A useful threshold: any hour where your conversion rate falls below 20% of your account average, sustained over 30 days, is a candidate for suppression. Run the schedule for 14 days before drawing conclusions. SP data is direct enough that two weeks is a meaningful sample for hourly scheduling decisions.
Sponsored Brands: run a softer schedule
For SB, the criteria for suppression should be stricter. Do not suppress an hour just because it does not convert same-session. Instead, look for hours with no impressions AND no clicks over 30 days. An hour where SB genuinely generates zero activity is a reasonable suppression candidate. An hour that generates impressions and clicks but not conversions may be doing work you cannot see in the immediate data.
A good frame: ask whether suppressing this hour removes brand visibility during times when buyers are on Amazon. If the answer is yes, leave it running. The ACoS for that hour may look unfavorable in isolation. Viewed across the full attribution window, it may be contributing meaningfully to purchases that register in other hours.
Sponsored Brands Video: run the softest schedule
SB Video warrants the most conservative approach of the three. Video impressions operate at the brand awareness layer. A shopper who watches a fifteen-second video about a cookware brand at 10pm on a Wednesday is in a different mental state than someone actively searching for a specific SKU. The conversion signal from that view may not materialize for days. Suppressing SB Video hours based on same-session performance data is almost always a mistake. The only hours worth suppressing are those with truly zero delivery, which typically indicates a budget issue rather than a scheduling opportunity.
The comparison in practice
| Campaign type | Conversion timing | Suppression approach | Data window |
|---|---|---|---|
| Sponsored Products | Same session, short lag | Aggressive. Pause hours with zero conversions over 30 days. | 30 days hourly |
| Sponsored Brands | 1 to 3 day lag common | Soft. Pause only hours with zero impressions AND zero clicks. | 30 days hourly |
| Sponsored Brands Video | Multi-day, recall-based | Minimal. Only suppress hours with zero delivery. | 30 days hourly |
| Sponsored Display | Extended, off-Amazon lag | Soft to minimal. Consider browsing patterns, not purchase patterns. | 45 days hourly |
How to build this in Off Hours
In Off Hours, creating separate dayparting rules for different campaign types is the expected workflow. When you build a new rule, you select which campaigns it applies to. Build one rule for your SP campaigns with the suppression grid that reflects your hourly conversion data. Build a second rule for your SB campaigns with a more conservative grid. The two rules operate independently, run on their own 15-minute evaluation cycle, and can be adjusted separately as your data evolves.
If you are also using performance rules to react to prior-day metrics, keep in mind that those rules evaluate once daily and apply to the account level. The interaction between performance rules and dayparting rules is additive: a campaign can be paused by a performance rule during a window where dayparting would have it running, or it can be running during hours where dayparting would suppress it if a performance rule overrides. Build the schedules first, then layer performance rules on top with awareness of how they interact.
For teams evaluating ad scheduling software for the first time, this campaign-type separation is worth asking about explicitly. Tools that apply one schedule to all campaigns are not built for the nuance that mature Amazon accounts actually need. The ability to scope rules to specific campaign types is not a nice-to-have feature. It is the feature.
Off Hours lets you build separate dayparting schedules for each campaign type, so Sponsored Brands and Sponsored Products each run on their own logic. Start a free 14-day trial.