How artificial intelligence is improving the digital advertising experience for consumers

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We’ve tested them all: the ad that runs six times during our favorite TV show, or the online ad that follows us everywhere. We’re looking for something once, and suddenly ads for it are popping up all over our social media feeds.

With the growth of digital audiences, largely driven by the growth in Channels like CTV / OTT And the audio broadcastAdvertisers are streaming buckets of money in communicating their brand messages to these captive audiences.

While targeting Technology has evolved so much to provide more fit and better personalization, it’s not without flaws. Saturation is still an issue. And automation can sometimes further improve it for a specific, possibly unintended direction.

The need for a human touch in advertising

Part of the reason why ads are sometimes inaccurate is because technology doesn’t understand the nuances of human behavior. In fact, AI It should, by design, be free from bias and influence. But when it comes to advertising, there is a lot of counterintuitive information to take into account, particularly regarding human behaviour.

For this reason, although AI techniques have a significant impact on improving the advertising experience, it still takes a human touch to interpret and inform the model. Here’s how marketers can take advantage of AI to deliver a better consumer experience.

Identify and respond to trends at scale

Certainly, analysts can look at ad performance data to see what resonates and use that insight to improve campaigns. But doing so with the necessary speed and scope is impossible. Effective performance measurement requires real-time, multi-platform analysis – how ads are performing across multiple channels examined together – and real-time optimization to be effective. By using artificial intelligence for analysis and optimization, marketers can get rid of repetitive, annoying or misplaced ads.

Take advantage of multi-touch referral

Digital marketing is traditionally based on first or last touch referral, which means that the “credit” for a purchase, web visit or download is due to the first or last impression a consumer has. But in reality, the waterfall effect is likely what drove the action — multiple points of contact in a given position, interconnected together in a chain — and that experience is very different across each consumer’s journey. AI can analyze this dynamic journey, learn specific touchpoints and cascade through multiple channels that lead to effectiveness and deliver that experience just right to influence buyer behavior.

Volume management across platforms

Artificial intelligence based advertising platforms are optimized for performance. But for a device, high performance means getting the most ads in front of the largest and most valuable audience. This can have a definite negative impact on a fire hose, not to mention hitting the budget in no time at all. It’s like turning on a sink faucet to full blast without adjusting the flow or temperature. This is why it’s important to adjust variables to manage ad serving size, including setting frequency limits that span multiple platforms, so consumers aren’t initially bombarded and then ghosted.

Publish smarter contextual targeting

In addition to making ads relevant to the viewer based on known interests or intent, AI can also make them relevant based on the context in which they appear. For example, if an advertiser sets up a weather stimulus to sell his latest winter coat, he may not want that ad to run during a discussion about climate change. But what if a weather clip was about a change in climate this week — lower temperatures, for example? AI can tell the difference and deliver the ad appropriately.

Include attention metrics

Marketers have long used uptime to measure an advertisement’s effectiveness – the more time a viewer lets it play, the more interested they are in it. But this only tells part of the story. How many times have you gotten up and walked away from the TV or left the device off for a snack while viewing an ad? With AI, we can improve attention metrics, which usually means getting our message across in the context of higher-quality, more compelling content — the content audience is less likely to shy away from that. AI helps brands do this in real time, but again, it takes human vision to know what catches the eye and will get people’s attention.

AI also needs a human touch

Of course, artificial intelligence is certainly not without risks. In fact, without proper input and adjustment, you can start to make poor decisions. For example, if we see that the performance of a particular ad creative starts to decline, the AI ​​may want to opt out of that purchase and shift the spending elsewhere, especially if the CPM goes up as the audience shrinks. But the campaign could have reached the bottom of the conversion funnel to the most engaged and high value customers. The cost may be higher, but so is the return on ad spend because it is a more valuable audience. Human guidance is key to preventing AI from improperly optimizing.

In a world where privacy is a constant concern, it is important for ICT vendors to understand how to reach people in a meaningful way that can be addressed without disturbing or interrupting their experience. Using AI, powered by human intuition, to improve targeting and delivery provides a more structured experience that adds value to the consumer.

T.J. Sullivan is Executive Vice President of Sales at Digital Remedy.

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