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Technology and Artificial intelligence have provided tangible market results across industries, and it has been rapidly reshaping the way we conduct business. When it comes to digital marketing, it has already started revolutionizing how businesses interact with their consumers online. Marketers have access to advanced technology and consumer insights enabling them to target highly relevant users, with customizable messages, automation of tasks offering significant business advantages, improved ROI generation, and new market exposure. Digital advertisers, however, have some expectations about the application of artificial intelligence in marketing, but it’s not always that these anticipations come true. Here’s a brief rundown of what advertisers expect of AI as they integrate it into digital marketing and what the ground reality is.

#1: Expectation: AI in digital marketing enhances customer journey and generates higher ROI

Businesses in diverse industries have been leveraging AI in their digital marketing campaigns, right from optimizing their advertising efforts by targeting the most relevant audience, with the most relevant personalized messaging to increasing the engagement rate and marketing automation. Various digital marketing platforms and technologies powered by AI allow organizations to simplify and increase productivity for their marketing activities. Thus, corporate executives plan to boost the ROI in their business operations by harnessing artificial intelligence. An example of AI in digital marketing is advertising on platforms like Google and Facebook that leverage AI to help advertisers reach their potential target audience based on the behavior of their users on the platform, or different bid strategies like target CPA, target ROAS, maximize conversions powered by AI to control the delivery of ads to users that are more likely to convert and meet the advertisers’ targets and boosts ROI.

Reality: The output from AI is only as good as the input given to the AI tool

Businesses are creating an AI-driven marketing automation approach and leveraging existing tools powered by AI to generate better ROI. However, just the implementation of AI tools is insufficient to support advertisers and marketers. Algorithms are the foundation on which AI applications and tools work but the AI can only generate results depending on the inputs given to it. Therefore you need a fitting algorithm backed with consumer insights to produce the best results. If we look at the AI tools on advertising platforms like Google and Facebook, the algorithm works on the inputs from the advertiser in terms of the target audience and messaging, learns based on user interactions, and produces similar results. This means the advertiser has to run campaigns targeting relevant audience groups for long enough to give the algorithm signals about the users that actually matter and not just focus on the cost of the acquisition. For example, the advertiser runs campaigns and generates leads at a lower cost but the qualification ratio of the leads is very low, the algorithm will churn out more and more leads that are not qualified, which in turn drives up the cost and negatively impacts the ROI.

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