Advanced bid optimization techniques refine Amazon PPC campaigns. The guide covers placement modifiers, dynamic date ranges, hourly adjustments, impression targeting, ACoS goals, and inventory-based bidding strategies for improved campaign performance.
Here is another Bid Ops cheat sheet, covering some additional โlayersโ of refinement that can be added onto a standard approach. ๐
Placement Modifiers: Great in theory, but there are some glaring issues with heavily incorporating them: Data at the Target level for SP doesnโt exist (outside Marketing Stream), control per Placement is done at the Campaign level, yet the performance itself comes from the Target level, Amazon will only honor the Modifiers based on their opinion of โlikelihood to convertโ, from week to week, the performance of any given Placement for any given Campaign will fluctuate significantly. I am not fully opposed to incorporating Placement Modifiers, but there are some huge issues that need to be factored in.
Dynamic Date Ranges: This is one of my favorites. If a Target doesnโt not have at least the ASINs avg CVR in clicks for a given date range, then the date range being used is too short, and vise-versa for using too long a date range. Nonetheless, I still would not use a shorter date range than a few days. Use AMC to ultra fine-tune thisโฆ
Hourly Bid Adjustments: Making hourly Bid adjustments is more efficient than a traditional โdaypartingโ system, where you โgo darkโ for specific blocks of the day. Just keep in mind that most Targets in the account will not have enough data for any given single hour over even a 30 day period to make any kind of intelligent adjustments with, some aggregation will be required.
Boosting Low Impression Targets: I have only seldom times found this to be helpful. Usually, starting bids on new Targets at roughly the avg CPC will at least serve some Impressions. If it doesnโt, this is usually a problem with the algo, not the bid. What can end up happening is that over time, 0 Impression Targets repeatedly get bid boosts, and then suddenly, the algo starts serving Impressions through those Targets. Not a fun place to be inโฆ
Dynamic ACoS Goals: More complex brands will naturally going to have performance goals per product line, customer journey stage, etc. A bid ops system that can work fluidly with this is highly advantageous.
Inventory Levels: This is definitely a higher-level strategy. The idea here is that if an ASIN is approaching OOS, then gradually reducing a normal bid amount may be helpful. This is opposed to: making no changes at all, raising price, pausing ads entirely. I have always found that pulling this lever to decrease sales velocity while lowering TACoS to be the most efficient.
I would love to hear what other things yโall are incorporating that I missed.
Check out my other Bid Ops cheat sheet here: https://lnkd.in/gjR2_sAc
I also dive deeper into some other Bid Ops gold here: https://lnkd.in/gQG8Uyt4