The Current State of AI in Digital Advertising

At Dyverse, we always work hard to stay current on all of Google's advertising offerings. We continually look for how Google's new campaign types, AI machine learning, and automation technology can help our client partners succeed.

It's not an easy task to keep up with advancements in the digital advertising space. We take pride in taking time to truly understand the pros and cons before utilizing a new trendy feature that is being talked about a lot because there are often misconceptions. We have always found it is best to analyze based on the unique dynamics of the multifamily industry.

Advertising Automation

One of the fastest-growing advancements we are seeing is using Google's AI and automation features. Whether it is related to audience targeting or automated bidding, it is exciting to think of the potential benefits that AI can provide. For example, based on your conversion data and other signals, such as first-party lists, Google touts that it can utilize its automated bidding strategies, such as Max Conversions, to get you more conversions at a lower cost-per-conversion.

We believe AI machine learning, and automation are the future of digital advertising. We have adopted several campaign types and tactics that Google has rolled out. Some of these campaign types require utilizing Google’s automated features. This includes responsive ads, which use a combination of possible text and design assets to serve the best option most likely to convert. Google's relatively new Performance Max campaign type will automatically use the Maximize Conversions automated bid strategy to "help you get the most conversions for your budget."

Concerns with Automated Recommendations

There are other automated recommendations that we have been hesitant to fully embrace until there is data to back up the claims that there would be a performance boost. This includes utilizing the Smart Bidding strategies such as Maximize Conversions with paid search campaigns. Google recommends pairing this Smart Bidding strategy with broad match keywords to see improved performance. Still, when testing, we have seen a drop in key performance indicators such as Search Impression Share and click volume.

Below is a screenshot of an automated recommendation from Google Ads, which could potentially cause a lot of wasted spend if implemented without close measurement.

The performance challenges with automated bidding strategies, which rely on conversion data, can be partially attributed to the requirements of the machine learning technology. For optimal functioning, this technology needs a substantial number of conversions. However, in the context of a single-location multifamily apartment community campaign, the actual number of significant conversions, like form submissions, tends to be relatively low. This discrepancy often hinders the effectiveness of automated bidding strategies. This is not an issue for some other industries where campaigns can generate hundreds to thousands of true conversions per month.

Dyverse's Careful Approach to Incorporating AI and Automation

For now, we are utilizing and maximizing the opportunities that AI provides through the areas we believe are beneficial for multifamily, such as Performance Max campaigns and responsive ad creative. We are also utilizing our client partners' first-party audience lists to provide Google's AI with more signals to hopefully improve bidding and audience targeting.

We will continue primarily utilizing manual bid strategies for paid search to control the KPIs that logically provide the best chance for our client's campaigns to succeed.

As Google's AI technology evolves, we will remain open-minded to new opportunities to improve performance. With Dyverse, you can be confident that we will also test performance before taking on any automated suggestions to make sure we utilize the best strategies that will result in improvements to return-on-ad-spend for our clients and their unique situations.