How to optimize account structure in an era of automation

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Automation has dramatically changed Google Ads and the other big ad platforms in recent years.

In many ways, automation has made our lives easier. For example, I don’t miss the days of manually adjusting bids for each keyword in my account.

However, as machine learning has become an integral part of campaign management, it’s natural to feel a loss of control.

To ensure that you maximize the positive impacts of automation – while maintaining the necessary level of autonomy – marketers need to revisit their account structures.

The media plans we are trying to deliver for our brands/clients often contain multiple objectives or lines of business, making the account structure even more important.

What follows are some tips on how you can alter your account structure to strike the perfect balance. We’ll start with the most granular level of account organization and work our way up.

As has always been the case, ad group organization should marry keywords to the message/offer you plan to deliver.

Make sure the message and landing page are tightly correlated to the keywords in the ad group. Ad relevance and landing page experience are critical components of ad rank, which determine your position on the page and the price you pay for clicks.

With Expanded Text Ads, it made sense to break out granular ad groups so that you could incorporate high-volume keywords into the ads (and thus, improve your ad relevance); however, with responsive search ads becoming the default ad type in July, there may be an opportunity consolidate ad groups, as you can incorporate a wider array of messages within a single ad. If pursuing this model, I recommend organizing keywords based on the landing pages you plan to drive to.

While some advertisers may prefer to maintain their current approach to ad group segmentation, it is important to consider your team’s ability to develop strong, relevant RSAs at scale.

The best practice our teams use is at least 10 headlines and four description lines for each RSA. Compared to the ETA, that’s a lot more time you need to spend writing compelling copy.

Consolidating your ad groups & leaning on the automation behind RSAs can provide operational efficiencies for your team, especially if you are managing campaigns across multiple product lines or geographic markets.  

Campaign structure is where SEM becomes more of an art than a science.

There is no right such thing as the “perfect” campaign segmentation strategy; however, there are a couple of key facts about campaigns that should influence how you set up your account:

Think about your campaigns as tactics to support the broader goals of your media plan. You can specify a portion of your budget to allocate to the campaign, and you can optimize toward a specific goal with a campaign-level bidding strategy. Ensure that the keywords and ads within your campaigns are designed to achieve the same goal.

You will need to assess which segmentation strategies will help you meet your marketing goals. Keep in mind that you can use a combination of the segmentations.

When splitting out campaigns more granularly, you effectively provide your team with more control over the spend mix across the account. This is how you can provide some guardrails that would otherwise be unknown to bidding algorithms.

These can be business-related nuances in strategy (e.g., a focus on competitor keywords for the month) or optimizations to enhance the output of your campaigns based on your own analysis.

An easy place to start when considering more granular segmentation of campaigns is keyword match types. Using an example, we’ll show how a more granular campaign strategy can result in a more optimized spend mix and stronger overall performance.

Though the algorithm effectively achieved our tCPA goal, clearly there is an opportunity to optimize this spend mix toward exact match keywords, where we are driving the most cost-effective conversions.

By splitting the keywords into separate campaigns and structuring our campaign daily budgets in a way that we are prioritizing the exact match campaign, we can drive aggregate lifts in efficiency while still meeting our investment goals.

One last word of caution: be careful about getting too granular with your campaign delineations.

If you get too aggressive with the campaign restructures, you will see a negative impact on the ability of the campaigns to leverage machine learning. Portfolio bidding can help overcome this; however, my recommendation would be to ensure you have at least $25-$50 spend/day in each campaign.

If your campaigns are regularly spending less than that, you may have been too aggressive with the segmentation of campaigns.

Ready to alter your account to leverage platform automation more effectively? Here’s how to do it:

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