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With traditional data management and analysis methods becoming increasingly ineffective given the large volume of information to process, advertisers are looking more and more toward artificial intelligence (AI) and machine learning (ML) technologies for solutions. Being able to constantly learn and adapt, ML in particular can have multiple applications in the ad industry, ranging from data processing and analysis to cognitive intelligence and insights into an organization’s target demographic.

Properly implemented, ML technologies can provide accurate information about customers’ habits, needs and preferences, allowing advertisers to personalize and optimize their campaigns for better results and ultimately higher return on investment. And this is just the tip of the iceberg. As ML technologies continue to evolve, organizations will find new applications to further optimize operations and promote innovation. 

These entrepreneurs from Ad Age Collective are already familiar with the advantages of using machine learning in their day-to-day operations. We asked them to expand on the technology’s potential and the innovative ways in which it can further impact the ad industry.

Refine your intelligent brand experience.

Consumer intelligence remains one of the areas that can benefit the most from ML technologies, says Gary Walter, president and CEO of Infutor, an innovative provider of consumer identity management solutions. The advanced level of personalization machine learning provides will allow brands to target the right audience, while customers get to have a more meaningful experience with the company.

“The ad industry will take machine learning to the next level by layering in consumer intelligence into their campaigns,” Walter explains. “This will help them layer in deterministic data to further refine a segment, provide pinpoint accuracy personalization and do intelligent frequency capping across devices and channels to give consumers a better, more intelligent experience with a brand.”

Improve preliminary ad testing and optimization.

ML technologies can help avoid a lot of advertising faux pas by adapting and using machine vision to increase the accuracy of preliminary ad testing and optimization efforts. Brennan White, co-founder and CEO of marketing artificial intelligence software provider Cortex, can see multiple benefits to this scenario.

“Using machine vision, you can collect a lot more user data than ever before. And by coupling that with performance data, creative choices can be pretested, saving tons of time and money, and leading to superior performance,” White underlines.

Personalize your website.

Along the same lines, WPBeginner founder Syed Balkhi believes machine learning can be used successfully to make A/B testing more automatic, benefiting organizations’ advertising efforts, as well as other strategies to increase conversions. 

“Imagine your website automatically running constant variations to help increase conversions. Person A could prefer a specific layout, while person B could prefer another layout,” Balkhi explains. It is easy to see how this kind of dynamic would help any organization, including a WordPress tricks and tips resource like WPBeginner, increase personalization and continue tweaking its strategies to maximize conversions.

Gain enhanced impact through informative research.

As ML technologies continue to evolve, they can be used successfully to increase the impact of advertisements, says Shereta Williams, president of Videa LLC, a company that offers automated sales solutions and services to TV stations. 

“Traditional broadcasters, agencies and marketers are constantly looking to reach consumers more effectively. By using data and insights from AI and machine learning to inform their campaigns, marketers can create impactful ads through informative research and development,” Williams explains, adding that artificial intelligence solutions can also be used successfully to close the attribution loop and ensure a judicious budget distribution during ad campaign.

Achieve customized ads at scale.

Machine learning solutions can not only significantly improve ad personalization, but they can also do it at scale with minimal efforts on behalf of the company and little to no customer involvement, thinks Chris Brisson, CEO of Salesmsg, a two-way business texting service recognized for its scalability.

“In order to reach a broader customer base, companies like Facebook and Google need ways to make it even easier for non-technical-savvy customers to use their products,” Brisson explains his point of view. “With machine learning, you'll simply be able to choose an audience and the Googles of the world will create the individually personalized ads, find the audience and scale it without the customer lifting a finger.”