Google AI Takes the Wheel in Auto-Selecting Photos for Local Services Ads

Google is updating its LSA platform in an advanced way, which has been long overdue. It’s actually going to change the game as far as visual management is concerned. By implementing an automated selection feature, AI becomes the one to decide which photos will be displayed in LSA ads. That changes the previous model of where advertisers are in full control over ad visuals.

Central to this shift is Google’s relentless pursuit of making its user experience better. In other words, the company tries to serve images to its users that are most likely to attract users by leaving photo selection to AI. It is now up to the algorithm to correctly interpret any advertiser’s photo library in order to find the image that meets the expectations of a specific, sophisticated series of criteria.

Although this undoubtedly does remain an innovation that holds out the promise of much better ad performance, it also injects some uncertainty for the marketer. Specifically, photo selection will undoubtedly impact ad ranking, but by how much is truly anybody’s guess. While Google says including high-quality images could have a positive impact on visibility, how that comes to correlate with photo-type choice and the ultimate ad position is yet to be established.

Advertisers must now adjust their visual content strategy to accommodate this new dynamic. Maintaining a varied collection of quality, original images that showcase the business and services best is recommended to increase the likelihood of desirable photo selection. Not only does Google advocate for authenticity, but it also discourages the use of stock photos or images belonging to others.

Photo management has also evolved. The advertiser’s image catalog is now viewable and editable in the Profile and Budget section in their LSA dashboard. Yet, not every advertisement will present with a photo, and the photo displayed can be dynamic because it is dependent on other elements, to include the end-user’s query, and other unspecified factors, among others.

This variety in photo appearance is a problem for advertisers who want to keep the image of the brand consistent. The possible upsides of photo selection powered by AI are obvious, but the loss of control over visual representation is worrisome. Advertisers might find it difficult to adjust the creativity of advertisements based on pendings of individual marketing campaigns or promotional offers if the visuals are up to the discretion of the algorithm.

Advertisers should be ready to scrutinize their LSA performance metrics more than ever before to minimize the risk of this change. The monitoring of key indicators, such as click-through rate, conversion rate, and generation of leads, will inform the business of the adequacy of the strategy for photo selection. In case of poor performance, there might be a need to reassess the image library or explore alternative advertising channels.

As the LSA scene continues to evolve, so must the advertiser. It means being agile while maintaining a very focused user experience. While the introduction of AI-driven photo selection presents a significant milestone on its own, it also drives home the importance of how holistic an approach to LSA management must be.

Effects on Advertisers: A Closer Look

This shift in photo management for LSAs to AI-based photo selection means there needs to be a whole new rethink in terms of advertising strategy. Of course, what Google is trying to do here is first and foremost to increase user experience; however, the stakes for an advertiser are very different.

Probably the biggest concern would be decreased brand control. Traditionally, advertisers have depended on visual consistency as part of brand expression. This allows a dilution of brand messaging since, in this case, AI will define which image best depicts a company. In such cases, it would mean increasing the photo libraries to include more image types that reflect different brand stories. In addition, strong brand guidelines can help make sure that whatever image the algorithm opts for presents the image of the company the brand owners would want portrayed.

The performance implications of this change are yet to be fully realized. Google does mention that including a photo can be useful to the ad rank, but how that links to ad performance with specific image attributes remains to be seen. For advertisers, it means keeping a close eye on photo choice within campaign metrics to see if any trends are appearing. A/B testing multiple image sets also gives insight into the variety of visuals that resonate with the target audience.

The stakes thus become even higher for those advertisers operating within highly competitive industries. The stakes of differentiation in these industries are huge, and by sight, there is a major fact within this context. Although AI can identify attention-grabbing images, it may not quite capture competitive landscapes. For these types of industries, investment in professional photography or videography may be a requirement in order to have uniquely amazing visuals.

Another consideration is the possibility of bias within the AI algorithm. For instance, if the algorithm is learned using non representative data, it would unconsciously pick images representative of stereotyping or the exclusion of groups of people. Advertisers have to stay wary of the types of images that are being picked by the AI for bias and provide feedback to Google when they find some.

But this is the way human creativity plays a role in LSA advertising: it changes in application over time. While AI is able to work out processing and analyzing images, it cannot really realize the effect brought about by pictures. One advertisement that can merge a data-driven-based insight with creative storytelling will likely hold a competitive advantage. It could involve the creation of ideas for visual concepts from AI, with a human in the loop to do so.

This basically implies that what Google has introduced to Local Services Ads is an AI-driven photo selection. The long-term impacts of this move remain to be seen, and it puts advertisers in a position where they will have to alter strategies accordingly. Proper management of your image library, monitoring ad performance, and using human creativity can help businesses fully realize this potentially fast-evolving platform.

Sources:

• https://www.searchenginejournal.com/googles-ai-now-chooses-your-local-ad-photos/523911/
• https://seo.ctr.hk/blog/google-s-ai-now-chooses-your-local-ad-photos-via-sejournal-mattgsouthern-765.html
• https://canalgrowthmarketing.com.br/blog/tendencias/googles-ai-now-chooses-your-local-ad-photos/
• https://twitter.com/sejournal/status/1821279548761108644

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