In an effective automated bid strategy, marketers need to choose the appropriate metrics relative to their goals and set effective target ROAS (return on ad spend) and target CPAs (cost per conversion). This post helps you optimize ad spend within paid search.
Embracing machine learning for automated bidding is becoming increasingly important. It’s not a question of whether you use it; its use is a best practice. But there are different metrics to watch and different bidding strategies to capitalize on depending on what goals you’re trying to achieve.
What’s the difference between ROAS and CPA?
ROAS, or return on ad spend, is the revenue you generate in relation to your advertising costs.
If your goal is to measure a profitable return on your marketing spend, ROAS is the most valuable metric to use. The catch: you’ve got to have the right data to use this metric. Ideal ROAS uses data tied to eCommerce or to selling a product (or a software or a service). That revenue data helps you get a clear view of the business impact your marketing choices generate. An increasingly high ROAS indicates that your campaign is performing well.
How to set target ROAS and target CPA as a bidding strategy
ROAS bidding aims to be above one, which means you’re generating positive revenue flow, and you should continue spending. If you’re below one, you should back off on spend and adjust the way you’re pacing and bidding. Your target ROAS helps you get more conversion value or revenue at the target return-on-ad-spend you set.
CPA bidding’s goal is to be below a specific dollar amount that you set. Machine learning helps you achieve that goal and sets bids to help drive as many conversions as possible at the target cost-per-acquisition you set.
When you set a target ROAS or CPA, this essentially tells your search platform, “Go find people, and utilize all the signals that you have to find me people who are more likely to convert.”
To illustrate how this works, imagine five people in a circle. The circle is where your paid search campaigns are targeting, and automated bidding will pick out three of those people who are statistically more likely to convert. The machine learning will show your ads to the three people according to your target ROAS or target CPA, and it will not show your ad to the other two people because it knows they’re less likely to convert or not in the market. When you set a target ROAS or target CPA, you can utilize the power of the search engine’s data to make sure your ads are shown to the right people at the right time.
Four steps to optimize ROAS and CPA
Step One: Determine where you want to go. You need to know your business objectives. But before you can set your business objectives, you need to know how you’ll determine your KPIs so that you can measure the real business impact of your efforts. Fortunately, Tim Wilson outlines a data-informed framework for creating measurement plans and objectives here. Once you’ve determined the metrics you need to be successful, you can set measurement goals.
Step Two: Determine where you are and how you need to adjust. It’s important to understand your campaigns’ historical performance in this step. If this is an already running campaign, compare your performance to your goal. If you’re performing lower than your CPA goal, that is, significantly more efficiently than your target goal, you have room to scale and grow. This type of performance is a signal that you might be able to spend more here and drive incremental results by increasing your target CPA to allow the search engine to find additional customers. Likewise, if you’re performing higher than your goal, you’re likely overspending. Understanding where you are relative to your goals helps you determine the appropriate path forward and whether you need to be more aggressive or relax your bidding strategy goals.
Day 7 set your CPA target to $150
Day 14 set your CPA target to $125
Day 21 set your CPA target to $100
Pacing your goals ensures that the machine learning model can adjust as you go. The same is true of the reverse situation: if you want to expand growth and go too high, the model won’t be able to account for a datapoint too far out of its comfort zone. We don’t want the machine learning to see our goals as outliers but realistic targets.
Step Four: Achieve and reevaluate. Once you achieve your goal, reevaluate. Media achievements are not linear but cyclical. After you’ve reached a goal, it’s time to set new goals based on what you’ve learned and continue through the process. This step is also an excellent place to drill down into the data to find places that can be more successful. For example, if one keyword isn’t meeting a goal, but your campaign is, that’s just fine; you probably shouldn’t throw more budget at the underperforming keyword in this instance. The micro and macro-elements of a campaign should all serve your larger goals (which you established in step one).
Whether you utilize this process for ROAS or CPA depends on what you’re trying to achieve. Are you trying to hit a revenue target with ROAS, or are you trying to succeed at driving volume with CPA? Answer each of these questions, follow these steps, and you’ll be well on your way to optimizing your automated bid strategy.