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Amazon PPC
Day parting on Amazon PPC (rule-based bid/budget adjustments by time of day or week) is oversold as a magic hack by low-effort blog and Reddit content, but the video argues it can produce real results — tripling sales on one product and nearly halving ACOS on another — when executed properly via either a free manual Google Sheets analysis or a paid automated tool, and only after other PPC fundamentals are already in place.
Day parting is defined as making rule-based bid or budget adjustments based on the time of day or week when ads perform best.
The video explicitly pushes back on hype: day parting should not be the #1 priority in Amazon PPC optimization, and other fundamentals should come first.
Two methods are demonstrated: a free manual method using Amazon's hourly export plus a Google Sheets pivot table, and an automated method using paid software (AdLabs).
The manual method builds an hour-by-hour table of impressions, clicks, orders, sales, spend, then derives ACOS, CTR, CVR, and CPC, color-coded with conditional formatting to visually reveal strong vs. weak hours.
Amazon's own native day-parting tool (Budget Rules) is called an 'embarrassing excuse for a day parting tool' because it only allows budget increases in a set window, with no bid adjustments and no decreases.
A cruder alternative — manually turning campaigns on/off by time of day — is explicitly discouraged because it limits Amazon's ability to collect and use campaign data.
A real case is described where manual day parting (as a 'hail mary' last resort) tripled sales on a struggling product.
A second real case, run via the AdLabs software, is described as cutting ACOS nearly in half while sales grew exponentially.
Oliver (a Sophie Society colleague) prefers granular hour-of-day adjustments over whole-day or day-of-week adjustments, because changing bids for an entire day alters placement settings for the full day and can hurt organic rank.
AdLabs' raw suggested bid adjustments (e.g., 270%) are treated as too extreme; Oliver manually moderates them, typically applying +15% to +60% increases or larger cuts for clearly bad, low-data hours.
The day-parting schedule is only re-optimized every 3-4 weeks to allow enough data to accumulate, and bids are deliberately not changed the same week as the schedule to isolate cause and effect.
A counterexample brand is shown where day parting has not worked and sales decreased after it started; the plan is an aggressive 80% bid decrease in non-converting hours, and full abandonment if that fails.
The video's closing framing: day parting 'is not a silver bullet' — it doesn't always work, but when it does it can be the difference between a profitable and unprofitable brand.
Day parting — Rule-based adjustments to Amazon PPC bids or budgets based on the time of day or week when ads perform best, as defined in the video. Apply: Analyze hourly campaign performance to find strong and weak hours, then set bid/budget rules that push spend up in strong hours and down in weak hours.
Manual pivot-table day-parting analysis (Sophie Society/"Zoki" method) — A free, no-software technique that uses Amazon's own hourly campaign export and a Google Sheets pivot table to visualize hour-by-hour ad performance, credited inside Sophie Society to "Zoki.". Apply: Export Amazon hourly campaign data, load it into Google Sheets, and build a pivot table filtered by portfolio with hour-of-day as rows and impressions/clicks/orders/sales/spend as values.
Amazon hourly Sponsored Ads report export — Amazon's native reporting feature (Measurement and Reporting > Sponsored Ads Reports) that produces hourly campaign-level data but is capped at 14 days per report. Apply: Run two separate 14-day exports (report type Campaign, time unit Hourly) and combine them in Google Sheets to assemble roughly a month of hourly data.
Derived PPC metric formulas (ACOS, CTR, CVR, CPC) — Spreadsheet formulas that convert raw pivot-table totals into standard PPC ratios: ACOS = Spend/Sales, CTR = Clicks/Impressions, CVR = Orders/Clicks, CPC = Spend/Clicks. Apply: Add these formulas next to the hourly pivot table, formatted as percentages (or 2-decimal currency for CPC), to compare each hour's efficiency.
Conditional formatting color-scale technique — A Google Sheets red-white-green color scale applied per metric column to visually flag good vs. bad hours, reversed in direction for 'lower is better' metrics (ACOS, CPC) versus 'higher is better' metrics (CTR, CVR). Apply: Apply Format > Conditional formatting > Color scale per column (min=green/max=red for ACOS/CPC; min=red/max=green for CTR/CVR), then collapse rows to read all 24 hours as a pattern.
Amazon native Budget Rules tool — Amazon's built-in day-parting feature (Campaign Manager > Budget rules), described as very basic since it only allows budget increases within a chosen start/end time window, with no bid adjustments and no decreases. Apply: Use it only for simple budget boosts during already-known strong hours, since it cannot decrease budgets/bids or handle nuanced hour-by-hour bid changes.
Manual campaign on/off toggling — A crude, explicitly not-recommended day-parting alternative of manually turning campaigns on and off at set times based on performance data. Apply: Discouraged in the video because it limits Amazon's ability to collect and use campaign data; presented only as a fallback, not best practice.
AdLabs day-parting calculator — A paid third-party PPC software, named as the presenter's/Sophie Society's favorite, with a dedicated day-parting tool that auto-calculates suggested bid adjustments by hour and day of week from imported hourly campaign data. Apply: In AdLabs, open Optimize > Day parting, copy the calculator's Google Sheet template, paste in the same 2x14-day hourly Amazon export, review the 'days of the week,' 'hour of day,' and 'bid change rules' tabs, then manually moderate and apply adjustments and save a new schedule against chosen campaigns.
Adtomic — A named competing Amazon PPC software with day-parting capability, mentioned as an alternative to AdLabs. Apply: Named only as an option to consider; not demonstrated in the video.
Perpetua — A named competing Amazon PPC software with day-parting capability, mentioned as an alternative to AdLabs. Apply: Named only as an option to consider; not demonstrated in the video.
Manual severity color-coding overlay (Oliver's method) — Oliver's personal layer on top of AdLabs' raw suggested adjustments, using bright/light red and bright/light green shading per hour to mark the intended severity of a decrease or increase before typing in a moderated percentage. Apply: Review AdLabs' suggested % alongside ACOS and click/order volume for each hour, color-code it by judgment, then manually enter a tempered adjustment (typically +15% to +60%, or larger cuts for clearly bad, low-volume hours) instead of applying AdLabs' raw suggestion directly.
Optimization cadence rule — A stated rule to re-optimize the day-parting schedule only once every 3-4 weeks, allowing enough data to accumulate. Apply: Wait 3-4 weeks between day-parting schedule changes before re-running the analysis and adjusting again.
Variable-isolation rule (bids vs. schedule) — A rule against changing regular PPC bids in the same week that the day-parting schedule itself is changed, to avoid overoptimization and keep cause and effect attributable. Apply: When updating the day-parting schedule for a campaign, hold other bid optimization steady that week, and vice versa.
Fundamentals-first principle — The video's framing that day parting is not the top-priority PPC lever and should only be layered on after other core PPC fundamentals are already handled. Apply: Confirm base campaign structure, keyword/bid fundamentals, and overall account health are solid before investing time in hour-by-hour day-parting analysis.
The presenter frames day parting less as a universal win and more as a diagnostic overlay: the same technique tripled sales on one account, nearly halved ACOS on another, and actively hurt a third, and the video keeps all three outcomes in view rather than only showcasing successes.
Whole-day bid or budget changes are claimed to have a hidden second-order effect — altering placement settings for the full day in a way that can suppress organic rank via lower CTR — which is why hour-level granularity is preferred over day-level toggles.
Software-suggested bid adjustments (like AdLabs' 270%) are treated as directional signals rather than literal instructions; the human moderation step (checking click/order volume before trusting an ACOS swing) is presented as more decisive than the tool's raw math.
The video builds in an explicit causal-isolation discipline — never changing the day-parting schedule and bids in the same week — specifically to avoid misattributing a win or loss to the wrong lever.
For the failing brand, the stated next step is not to abandon day parting outright but to escalate it first (an 80% cut in dead hours) before giving up, treating failure itself as something to be tested rather than assumed.
One audience comment offers a competing causal explanation for the video's own flagship example: that the strong morning ACOS/CTR/CVR numbers may reflect campaigns still having budget left earlier in the day rather than a skincare-specific morning usage pattern — a direct challenge to the video's stated hypothesis.
«I'm about to show you how we tripled the sales of one of our Amazon products overnight and on one of our other Amazon products cut the a cost in half while growing sales exponentially using the mythical day parting.»
— 00:00
«The reality is day parting should not be the number one thing on your list when it comes to Amazon PPC optimization.»
— 00:57
«This block right here performs really well from every perspective from 4:00 a.m. to 12:00 noon.»
— 09:03
«Here's where I have to go back to Amazon ad console and show you the embarrassing excuse for a day parting tool that Amazon has given us.»
— 10:04
«Day parting was kind of like a hail mary, like last resort option for us, and it worked really well.»
— 11:24
«Sometimes if you go too extreme with it, it can actually be counterproductive and actually hurt your performance.»
— 12:10
«If you increase or decrease an entire day, your placement settings are going to change for the full day and I think it's going to start affecting your organic ranks.»
— 14:53
«I actually I'll do usually I'll start off with between 15% increase and like a 60% increase.»
— 17:07
«And when I do change my day day passing schedule, I won't optimize the bids for that week.»
— 19:40
«My next step for this day parting is I'm actually going to turn it off almost completely for the hours that we're not converting.»
— 20:32
«Remember, this is not a silver bullet. It doesn't always work, but sometimes when it does work, it can work really well and it could be the thing that makes the difference between profitable and unprofitable for certain brands.»
— 21:04
«if you want to learn another hack that allows you to increase profitability by exploiting a loophole in the data Amazon made available to sellers without realizing it, click here to watch my video on how to exploit that loophole and increase your profits right now.»
— 21:51
Reception
Viewers found the dayparting/PPC video informative and appreciated Chris's content, though several reported technical issues with the reporting tool and some newer sellers struggled to apply the advice.
The video positions itself as a corrective to hype-driven day-parting content by walking through two concrete methods with named tools and two contrasting real-account outcomes (a win and an ongoing failure), while repeatedly framing the technique as a secondary lever rather than a primary fix.
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