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DayParting Decoded - The Good, Bad & PPC Ninja

Updated: May 4

Thoughts on Amazon PPC Dayparting and our Amazon PPC Agency will use it

Day parting has been a hotly debated topic in the advertising industry for some time now. It’s one of the top questions we get asked about at PPC Ninja. Are we using day parting? And how should we be using this hotly debated feature? First, let’s talk about what day parting is.

What is Day Parting?

Day parting is the practice of scheduling and optimizing ads to run during specific times of the day or days of the week. Advertisers and sellers want this feature due to known patterns of poor performance. These patterns can be certain days of the week or certain times during the day, like early morning or very late in the evening.

What makes optimizing day parting challenging is how the attribution works. A customer can add your product to their cart during a "poor-performing" time slot in the day but can wait for several days before checking out. If our ads are not serving, we can miss out on this sale entirely. The problem is we have no idea what day or time this conversion happened, so optimizing our dayparting schedule can be challenging. Let's explore the three paths PPC Ninja has identified for this feature.

1. Lowering Bids During the Worst Hours of the Day

The problem with lowering bids is that each bid is tied to THREE placements. Lowering bids often, but not always, has the effect of losing the Top of Search placement in favor of Rest of Search or Product Pages. These placements may offer more impressions and more clicks, but at lower CVRs.

So there is a possibility you may end up with worse performance than before. You can't control placements with bid adjustments.

Making real-time bid adjustments is tricky because of attribution. You will need 2 additional pieces of information to be absolutely sure about your choice to drop bids: the average Time-to-purchase for THAT hour of the day and your historical ACoS at THAT hour of the day in order to base changes on statistically relevant data.

We can also risk losing performance on some of our keywords by drastically reducing our bids, and restoring them to previous setpoints does not guarantee the return of performance.

2. Lowering Budgets During the Worst Hours of the Day

With day parting, we can automate lowering our budgets, but lowering budgets often does not stop the algorithm from going over the budget by 100% (unless you have specifically set the max allowance to 25%). But even then there is a monthly max spend allowance for adjustments that can still spend over the 25% threshold on any given day. Another challenge with this option is you can never control budget pacing. Even with lower budgets, they could still be consumed before your best hours because of higher pacing. Limiting our budgets will reduce some wasted ad spend, but as long as Amazon views our budgets as suggestions, it will never be perfect.

3. Pausing Campaigns During the Worst Hours of the Day

When it comes to implementing dayparting in your advertising strategy, one approach stands out as the safest and most cautious choice—pausing campaigns during specific hours of the day. Ideally, we would want to leave our best campaigns running at all times and use rules to restrict our testing or poor-performing campaigns to only operate during the best times of the day, giving them an opportunity to increase their efficiencies and join the best performers.

The primary benefit of pausing campaigns during certain dayparts is that it puts a definitive halt to any unnecessary spending. Imagine this scenario: early in the morning, after budgets reset, many advertisers experience a surge in competition, leading to higher CPCs, and cheaper CPCs in the afternoon/evening as the competition budgets are consumed. By pausing your campaigns during these competitive hours, we can potentially avoid overpaying for ads or placements. We can use rules to control the automation of which campaigns will get paused, like operating above a predetermined ACoS value.

Downloading Hourly Data and Building A Heat Map

Now that we understand how day parting works, it's time to download your hourly data. In the Advertising Console, go to Measurement and Reporting.

Select Sponsored Products for the Report Category.

Report Type is Campaign and the most important part of this is selecting Hourly. Amazon will only allow us to download 14 days of data at a time, but up to 1 month is available.

Now that we have our data it's time to build a heat map. Use this link to access our heat map template. Be sure to make your own copy by going File > Make a copy.

Once that is done, follow our SOP on the instructions tab, and the output will look like this and easily allow us to analyze our data.

On the bottom of the sheet, we will have 4 different tabs. We will be able to see what time of day our ad sales are happening, when we are spending the most, when our ACoS is the highest/lowest, and when we have the best conversion rate. When we stitch all of this data together we can then paint a better picture of what time we should be pausing our ads.

Day parting & PPC Ninja

We are happy to announce that PPC Ninja is currently beta testing our newest feature, you guessed it, day parting. After diving deep into the pros and cons available for this feature, we believe option 3 will deliver the most utility without potentially impacting the performance of any campaigns while giving us higher control over when we wish our ads to be delivered. If you’re interested in testing our day parting, sign up for PPC Ninja now and be among the first to harness the power of our cutting-edge day parting feature!

PPC Ninja is a powerful software helping agencies and brand owners increase their advertising efficiency with cutting edge techniques such as the Bid Sufficiency model, Zero Sales Algorithm, Placements X-Ray and more. Sign up for a 14-day free trial here.

If this post sparked your interest, leave us a comment or a question!

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