{{announcement.body}}
{{announcement.title}}

How AI Will Power Intelligent Advertising

DZone 's Guide to

How AI Will Power Intelligent Advertising

In this article, see how a breakdown of how AI will power intelligent advertising and the issues it will resolve.

· AI Zone ·
Free Resource

Advertising relies on gathering and processing user behavior to create personalized ads. More relevant and personalized ads create a great user experience for a business’s audience and also a better return on ad spend. 

However, there are concerns in the advertising sphere about how businesses collect data and whether user’s data privacy rights are being protected. 

Here are the major points of interest that AI will play a role in to transform advertising:

  • Businesses need data and to process that data well to get insights
  • Audiences must get personalized ads to drive up conversion rates and returns on advertising spend
  • These goals should not negatively affect users’ privacy rights

So, there’s an ongoing conflict and many businesses are concerned about how they’ll be able to target the right audience better when they also have restrictions on what data they can gather. 

This conflict, however, can be managed with the help of AI. Brands like Oracle are already taking steps to ensure that they have the tools and platforms to create helpful ads but without extracting users’ personal information.

This is important since the implementation of the GDPR act and the upcoming cookie depreciation is going to change how business’s advertising. 

Here’s a breakdown of how AI will power intelligent advertising and help resolve these issues. 

Contextual Advertising

A major tool that businesses use to gather data and create relevant ads is the use of cookies on websites. But Google will soon be blocking third-party cookies and preventing businesses from collecting data without explicit consent. For the advertising industry, this is a shakeup that needs a solution fast. 

To that end, Oracle, for example, has bought Grapeshot’s Contextual Intelligence platform. The platform uses machine learning algorithms to scan and categorize text, video, and image content to understand what they are about. 

Advertisers can use this platform to avoid having their ads seen on undesirable sites. But it’s also a game-changer if and when the cookie depreciation takes place. 

Businesses will be able to target users by interest based on the content of the page rather than targeting the user’s data and information. It’s a shift that will keep businesses getting positive ad results while staying on the right side of data privacy laws. 

Adtech and Martech Convergence

Another problem faced by businesses is the need for multiple tools and platforms to manage their advertising and marketing campaigns. 

While both marketing and advertising strategies work towards the same goal-getting new customers - their methodologies are different. 

Adtech relies on paid advertising and third-party tools like cookies. AI supports advertising by creating automatic bids and by optimizing ads for keywords.

Martech works with first-party data and is concerned with building relationships. It includes email marketing, CRM, and AI-powered chatbots. An interesting way that AI supports marketing is through conversational marketing with the help of chatbots. Some 60% of people consumers use chatbots to find answers and it’s the preferred platform for Millennials. Another 50% of people say they’d purchase something from a website’s chatbot that uses a conversational approach.

Adtech and Martech platforms have operated separately so far, making it necessary for businesses to adopt several vendors for different activities. According to one study by Sizmek, they found that reducing the number of technology vendors is important. Some 28% of marketers believe that reducing the number of Martech and ad tech vendors is critical while 36% believe that it’s urgent.

AI is making it possible to combine these two technology stacks, Martech and Adtech, into ‘Madtech’. This is a platform where marketing and advertising activities can be driven from a single platform.

In this type of tool, machine learning algorithms can be trained to analyze users’ behaviors online, develop patterns, and then trigger the right communication method or optimize ads based on the audience’s behavior.

For example, Vizury has come up with an IntelliBid and IntelliRec solution for its engagement platform. The IntelliBid algorithm optimizes ad bidding while IntelliRec supports advanced segmentation and communication customization. 

In this way, both advertisement and marketing goals will be supported as businesses seek to reduce the number of vendors they use. 

Conclusion

For businesses, data is the source of growth and conversions. They rely on AI to collect and process data, and to also come up with the best ways to leverage it in advertising, communication, and other activities. 

However, how businesses can use such data is likely to change and become more limited in the future as privacy concerns arise. 

AI can improve the efficiency with which marketing and advertising activities are carried out by unifying various platforms. It can also protect users’ privacy by relying on content to drive advertisement placements. With the help of Natural Language Processing and machine learning tools, businesses can face virtually any major changes in the future. 

Topics:
Contextual Advertising, advertising, ai in advertising, artifical intelligence

Opinions expressed by DZone contributors are their own.

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}