Amazon PPC Bid Optimization: How Long Should You Wait Before Adjusting Bids Again?

Your ACOS is stuck at 35%. You optimize your bids, wait a week, and see a slight improvement to 33%. Now you’re wondering: Do I optimize again? Should I use the last 30 days of data or just the last 7 days?

This is a common question among Amazon sellers, especially those aiming for specific ACOS targets. It’s frustrating to feel like you’re not making enough progress, even after putting in the work.

In this article, we’ll break down how long you should wait after optimizing your Amazon PPC bids and which date range you should use. We’ll also cover how to know if your optimizations are actually working. Let’s dive in.

After Amazon PPC Optimization: How Long to Wait Before You Optimize Again

A user, Craig, asked us this question: “I have an ACOS of 35% and use a 30-day window for the first optimization, targeting 30%. After one week, my ACOS is down to 33% with no irregular spikes. Do I run the bid optimizer again with a target ACOS of 30%? And would I use another 30-day look-back window, or just the last 7 days?”

Here’s how we’d respond.

Directionally Moving Towards Your Goals

First, figure out if your optimizations are working. A quick way to tell is to see if you’re moving in the right direction.

• Example: If your goal was to reduce ACOS and you see spend spiking the next day, something’s probably wrong.
• Example: If your goal was to lower spend and lower ACOS, and you see spend decreasing, you’re likely on the right track.

What’s accurate immediately after a round of optimizations is your spend trend. Sales and ACOS take longer to reflect true performance due to sales attribution delays.

Account-Specific Attribution Delays

The sales attribution delay is when there is a delay in reporting sales that have occurred as a direct result of clicks on your ads.

Here’s what’s happening: Because of the sales attribution delay, ACOS will always look a little high for the last couple of days.

• Example: If you sell a $10 product with same-day purchases, yesterday’s ACOS might be just 32-33% when you usually have a 30% ACOS.
• Example: If you sell a $200 product with a longer consideration window, yesterday’s ACOS might be 40-45% when you usually have a 30% ACOS.

If you’re looking at a 7-day timeframe, nearly 30% of that data is averaging slightly higher ACOS due to the attribution delay. Keep this in mind before optimizing again.

Micro vs. Macro Adjustments

A tight max increase/decrease setting means you’ll need more frequent optimizations to continually move spend or ACOS down. If you’re trying to significantly move ACOS or spend, you’ll want to open up those max decrease settings.

• Example: You can do a 25% or even 50% max decrease to accelerate pulling back spend on high ACOS keywords.

If you’re seeing that your ACOS stayed flat or even increased in the last 7 days, consider a micro adjustment.

• Micro Adjustment: Analyze just the last 7 days and look for anomalies. Maybe one campaign has a spend spike and ACOS spike. Drill into that campaign (or even just one or two keywords) to clean it up.

How to Choose the Right Time Frame

The time frame you select impacts how your optimizations work. If Craig ran an optimization looking at the last 30 days and is now looking at it again, we don’t know what those bids should be based on the data coming in.

If you’re using 30 days of data, that’s pretty high data confidence. Sometimes, though, you need to incrementally move towards your goal.

• Example: Even if you needed to pull bids back 60%, you may have only pulled them back 10%. One thing you can do is go in, turn off the limits, so you can get an idea of how far some of those bids are actually needing to be pulled down.

If you start using a shorter time frame, you’re ignoring valuable historical data from the last 30 days. And if you’re doing revenue per click bidding like we do in AdLabs, you want to give more data to the algorithm for it to work well.

Is Data From Before Your Optimization Still Relevant?

It can feel like data from before your optimization is irrelevant, since you’re using a different bid now.

Here’s the thing: Variables aren’t that different.

It’s still the same keyword, the same product. That keyword and product will have a specific conversion rate in their relationship that’s relevant whether it was at a $1 bid or a $0.50 bid. It’s all traffic, all conversion rate.

You want to include all of it.

Having a longer time frame, while still using the last 7 days’ data, is a good mix. You’re getting data since the optimization, but also thousands of clicks from before that are still relevant and accurate.

• Example: If your default date range is 30 days, you can do something in between, like a 14-day timeframe, to be more biased toward what happened since the last optimization. That way, half of your data is since the last optimization, but the other half is still those relevant clicks.

The Dangers of Only Optimizing Based on Data Since Your Last Optimization

Generally, optimizing based only on days since the last optimization is a bad idea. Unless, of course, it’s been 30 days since your last optimization.

Most sellers optimize once a week or every other week. On the date range selection episode, we talk about shorter versus longer timeframes. The “right” date range really depends on your goal and the considerations for each timeframe.

Be Careful with Placements

One thing to keep in mind is that, if you’re using a shorter timeframe to make those micro adjustments, you typically want to avoid optimizing placements. Usually, it gives more sporadic, wild results.

Instead, use a longer timeframe, like 30 to 60 days, to optimize placements, especially if things are consistent.

So, if you’re going in and making those micro adjustments, isolate the keyword that’s the problem, pull it down, and don’t really mess with the placements. Just address the core issue there.

Waiting for X Number of Clicks

One tool had a logic built into it that, after making a bid change, it would wait until it got X number of clicks before optimizing again. The problem with this is, if that bid change wasn’t enough, you’re just wasting money the whole time you’re waiting for the keywords “to get enough clicks”.

What if the ACOS is still high? You can lose a ton of money just waiting for that click confidence to come in when you already have the click confidence.

• Example: You definitely have enough clicks to know what the bid should be from the last 30 days of data. This is why we use that revenue per click.

Another problem with waiting for a certain number of clicks is if that bid change was too much of a correction. Now it has zero clicks, and you’re going to be waiting until X number of clicks, which isn’t going to happen again.

So, you’ll have to wait basically 30 days until it hits another condition (like no clicks in 30 days) to start increasing it again.

Final Thoughts

You can optimize based off of the last 30 days. One week later, you can jump in and optimize again using the last 14 to 30 days. Just be mindful of your max increase/decrease limits.

If you’re going to use a really short timeframe (like just the last 7 days), treat that as a micro adjustment. You’re not doing placements in those cases. You’re just drilling into a few problematic keywords or campaigns and doing a small cleanup.

Optimize Based on Your Goals

Hopefully, this was helpful. Remember to consider attribution delays, data confidence, and micro versus macro adjustments when deciding when to optimize your bids again. By understanding these concepts, you can make informed decisions and drive better results for your Amazon PPC campaigns.

Want to make bid management easier? AdLabs gives you the speed of bid automation towards campaign group goals while allowing you to remain in control. See why users say it’s the right balance of efficiency + strategy + control—and it’s a big reason their brands scale smarter on Amazon.

This article is based on Episode 112 of That Amazon Ads Podcast. Subscribe for weekly Amazon PPC strategies.