In 2018, Lexus released what it called artificial intelligence’s first advertisement.
According to Variety, Lexus used IBM Watson to analyze 15 years of “car and luxury brand campaigns winning Cannes Lions creativity awards as well as a range of other external data.”Watson was able to identify the elements that would resonate with viewers from the dataset.
Artificial intelligence takes over the advertising world. Although there are commercially available platforms that use AI to create ads without human involvement, artificial intelligence is not just creating ads.No, AI transforms at every level what is possible in the advertising world, from ad creation to targeting audiences to ad purchasing.
What is artificial intelligence (AI)
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
AI-powered computers are capable of reading and understanding text, seeing and recognizing images, going around obstacles physically, hearing and understanding sounds, and sensing their external environment.
Gmail and Google Docs, for example, are now using AI to read what you’re typing, and then understand enough to decide what to type next with Smart Compose. Facebook uses AI to detect the person in your photos and then recommends the person to tag.
Machine learning, computer vision, natural language generation, natural language processing, deep learning, and neural networks are some of the AI technologies you might hear about. There are also dozens of others.
AI technologies transform industries from finance to retail healthcare.AI tools in these industries are dramatically transforming the way work is done, providing unprecedented opportunities for revenue, and significantly reducing costs. That’s because there are some advantages of AI technologies over traditional software.
How AI is different from traditional software
First, AI has the ability, unlike traditional software, to usefully process huge data sets on a scale.
Certainly, traditional software has access to large amounts of data (think: all contacts in your CRM system). The software provides a marketer with clarity, as you can now see all your data in one place and more easily perform tasks. But it does not provide any data background. Traditional software will not tell you or what it means to do with the data. It’s “dumb.”
However, artificial intelligence technologies are “smart.” They analyze the data on a scale and then predict what it means. For example, an AI-powered CRM system would contain the same data as a conventional system. Other than that, the AI-powered system might also potentially recommend which leads are most likely to close, who to talk to next, and how to score leads based on their behaviors on your site.
Let’s take our traditional vs. AI-powered CRM system again.
A traditional CRM system, such as downloading an ebook or requesting a consultation, could be programmed to flag any leads that take high-priority actions on your site. Based on these actions, the system could then assign a lead score to the contact. Presumably, their score will go up because they’ve taken some skilled actions on your site, based on rules you’ve created manually.
On the other hand, an AI-powered CRM system might take the lead scoring rules that you created and then analyze how well it works overtime, based on comparing the score of each lead to whether or not that lead converts into a customer. The AI-powered CRM could then adjust lead scores automatically or create new ones based on what it sees working from the data without your involvement. Perhaps downloading an ebook isn’t as powerful as you thought about a lead score signal, and leads who downloads one is no longer likely to convert. This could be identified by an AI-powered CRM and its lead scoring capabilities improved accordingly.
Why AI is taking over the advertising industry
This is why in marketing and advertising, AI is beginning to gain traction.
We have tons of data available from CRM systems, marketing automation tools, ad networks, etc. due to the digital marketing revolution.
Yet we lack the time, resources, or cognitive ability to effectively analyze all of this data, even though it may have information that can dramatically improve our campaigns. As a result, our marketing and advertising performance is suffering, costing brands enormous amounts of time and money.
As a result, entrepreneurs and forward-thinking marketing executives turn to AI for their ability to boost sales, cut costs, and build massive competitive advantage. And as far as advertising AI is concerned, there are already plenty of use cases and tools that anyone can understand, pilot, and scale.
How AI applies to advertise
Advertising tools, including observable views, click-through rates, bid levels, demographics, and more, give us tons of data to work with. There is no question that humans have the ability to produce good advertising, evaluate advertising, and enhance ads based on what they know. But digital advertising across search, content, and channels of social media gives us an almost unlimited ability to generate data about what works and what doesn’t.
That’s what makes ads difficult for humans on a scale (read: impossible). And that’s what makes AI an advertisement natural fit.
AI-powered ad systems can identify trends on a scale in your advertisement data with the right data, then predict the campaign improvements can improve performance against a particular KPI. All this can happen in seconds, rather than the hours, days, or weeks that a person can take to evaluate, check, and iterate through campaigns.
Advertising costs a ton of money, particularly if you sell a product or service that does not yield an immediate return.
AI for ads has the ability to increase your ad spending (revenue) return and reduce the amount of money you spend on employee time and inefficient ad budget.
Use cases for AI in advertising
Although you may not always see it, AI is crucial to the infrastructure that underlies advertising products on many platforms.
Digital advertising exchanges and websites all use artificial intelligence to monitor the real-time buying and selling of ads. It involves programmatic platforms, networks of third parties, and channel advertisements such as Twitter, Instagram, and Snapchat.
Such markets, utilities, and networks will not be able to announce how their AI will function anytime soon. But that’s the point: Artificial intelligence decides even behind the scenes how your ad spend is used, who sees your advertising, and how successful your overall campaigns are.
This means that if you run paid advertising, you need to understand the terminology of artificial intelligence (this resource is a great starting point) and ask the right questions about how the AI used by ad platforms can affect your spending.
A very basic example of this is:
Advertising on Facebook, explicitly ad frequency and a score of significance. These two numbers are key pieces of data that Facebook’s algorithms use to dictate how much you pay and how your ads are displayed, without human involvement.
You may think it’s good to show your ad more often. But that’s not it.
Traditional advertising research has shown that, within a brand purchasing period, optimum ad duration is at least three exposures. Traditional advertising schools say that as many times as possible you have to “bury” the audience with the same ad.
This is because user feedback is taken into account by Facebook’s algorithms. If you display your ad too often, and users rated it poorly, your score of relevance could fall.”In most situations,” says Social Media Examiner, “the higher the duration, the lower the score of relevance.” A high score of relevance means that your ad is more likely to be shown to a target audience than the other ads you compete with. That means better results and lower costs.
Performance and spend optimization
Quality optimization is one of the most significant advertising technologies for AI. Commercially available solutions use machine learning algorithms to evaluate how the ads perform across different platforms and then provide feedback on how performance can be improved.
These platforms may, in some cases, use artificial intelligence to smartly automate actions that you know you should take based on best practices, saving you significant time. In other cases, performance issues may be highlighted that you didn’t even know you had.
We know of at least one commercially available tool in the most advanced cases that automatically manages ad performance and spends optimization, making decisions on how best to reach your advertising KPIs on its own. In another case, there is at least one platform that automatically allocates ad dollars across all channels and audiences, so people can focus on strategic tasks of higher value rather than manual guesswork on what works and what doesn’t.
There are AI-powered systems that will generate advertisements for you in whole or in part, depending on what works best for your goals. Some of the social media ad networks already have this feature, which uses many smart algorithms to recommend ads that you should run based on the links that you are promoting.But there are also third-party applications that actually use smart algorithms to write ad copies for you. These systems leverage the processing of natural language (NLP) and the generation of natural language (NLG), two AI-powered technologies, to write ad copies that perform well or better than human-written copies — in a fraction of the time and on a scale.
Your targeting ad is as important as, if not more important than, copying and creating your ad.You have a seriously robust set of consumer data to target audiences thanks to platforms like Facebook, LinkedIn, Amazon, and Google. But it’s not always easy to do this manually. Here, AI can help. We know of at least one artificial intelligence system that looks at your past audiences and ad performance, tests it against your KPIs and incorporates real-time performance data, then identifies new audiences that are likely to purchase from you.
Vendors that offer AI tools for advertising
Most vendors offer partly or exclusively advertising-focused AI-powered solutions.
Adobe Advertising Cloud is billed on a demand-side platform unifying digital and TV campaign advertising data. As part of the platform, according to the company’s website, Adobe Sensei, the company’s artificial intelligence product, offers “predictions on how to get the highest conversions at the lowest cost.”
As mentioned, Albert is another key player in the AI-powered advertising space. The company’s artificial intelligence platform analyzes data across your ad accounts and customer databases then use sophisticated machine learning to target, run, and optimize your ad campaign
GumGum’s artificial intelligence-powered computer vision technology learns from web-wide images and videos, then lets you place ads precisely where users will see them.
Formerly The Weather Company (acquired by IBM in 2015), IBM Watson Advertising uses IBM Watson’s AI capabilities and (presumably) acquisition data to improve brand advertising performance.
Pathmatics uses artificial intelligence to provide an advertising with transparency and perspective. The tool shows you exactly how your ads work across networks and provide you with competitive data on the output of ads from your rivals.
Phrasee uses AI to tackle the production of ads. One of the main features of the device is that it automatically writes better email subject lines than humans — but that same AI-powered function has now been modified to automatically write Facebook ads and push notifications.
The AI platform of WordStream analyzes your advertising campaigns across Facebook and Google Ads and then helps you change campaigns quickly.