The Use of A.I in the World of Advertising
What is artificial intelligence (AI)
The term “artificial intelligence” is an umbrella term that covers a range of machines that learn, with the help of human or entirely on their own. In this way, AI technologies perform certain cognitive tasks as well or better than humans.
AI-powered machines can read and understand text, see and identify images, physically move around obstacles, hear sounds and understand them, and sense their external environment.
For instance, Gmail and Google Docs now use AI to read what you're typing, then understand it enough to recommend what to type next with the power of Predictive Analytics.
Facebook uses AI to detect who is in your photos, then recommends who to tag.
Self-driving cars use AI to detect obstacles and drive (hopefully) in a safe and effective way.
Siri on your iPhone uses AI to understand your voice commands and create responses that make sense.
Smart home technology, like Ring cameras and Nest thermostats, use AI to sense changes in their observable environments, then take action based on what they sense.
Some AI technologies you might hear about are: machine learning, computer vision, natural language generation, natural language processing, deep learning, and neural networks. There are dozens of others, too.
AI technologies are transforming industries from finance to healthcare to retail. In those industries, AI tools are dramatically transforming how work is done, providing unprecedented revenue opportunities, and significantly cutting costs. That's because AI technologies have a couple advantages over traditional software.
How AI is different from traditional software
First, unlike traditional software, AI has the ability to usefully process huge datasets at scale.
Traditional software certainly has access to large amounts of data (think: all the contacts in your CRM system). The software offers clarity to a marketer, because you now can see all your data in one place and perform tasks more easily. But it doesn't offer any context about the data. Traditional software won't tell you what to do with the data or what it means.
Artificial intelligence technologies, however, are "smart." They analyse the data at scale, then make predictions about what that data means. An AI-powered CRM system, for instance, would contain all the same data as a traditional one. Except, the AI-powered system could also potentially recommend which leads are most likely to close, who you should talk to next, and how to score leads based on their behaviours on your site.
Second, some AI-powered systems have the ability to learn to get better, either with human help or on their own. Traditional software does exactly what it is programmed to do. Any useful results you get with the software are possible because programmers built the system to produce those results. If you want the system to get better at what it does, you'll need to rely on a software update, where developers manually make the system better.
Some AI-powered systems, however, can improve their performance over time in response to the data they analyse. Sometimes, this happens because humans manually train AI systems on more and more data, so the system has better information from which to make predictions. Other times, the system can actually learn on its own.
Let's take our traditional vs. AI-powered CRM system again.
A traditional CRM system might be programmed to flag any leads that take high-priority actions on your site, like downloading an E-book or request a consultation. The system might then assign a lead score to the contact based on those actions. Presumably, their score will go up because they've taken some qualified actions on your site, based on rules that you manually created.
An AI-powered CRM system, on the other hand, could possibly take the lead scoring rules you created, then analyse how well it works over time, based on comparing each lead's score to whether or not that lead converts into a customer. Without your involvement, the AI-powered CRM might then automatically adjust lead scores or create new ones based on what it sees working from the data. Maybe downloading an E-book isn't as strong of a lead score signal as you thought, and leads who download one aren't any more likely to convert. An AI-powered CRM might identify that and improve its lead scoring capabilities accordingly.
Why AI is taking over the advertising industry
This is why AI is starting to gain traction in marketing and advertising.
Thanks to the digital marketing revolution, we have tons of data at our disposal from CRM systems, Marketing automation software, ad platforms, etc.
But we lack the time, energy, or cognitive capacity to process all of this data effectively, even though it probably holds insights that can dramatically improve ourcampaigns. Our marketing and advertising performance suffers as a result, costing huge amounts of time and money for brands.
As a result, entrepreneurs and forward-thinking marketing leaders are turning to AI for its ability to increase revenue, reduce costs, and build massive competitive advantage.
And when it comes to AI for advertising, there are already plenty of use cases and tools that anyone can understand, pilot, and scale.
How AI applies to Advertising
Advertising platforms give us lots of data to work with, including measurable impressions, click-through rates, bid levels, demographics, and more.
Humans certainly have the ability to produce good advertising, measure that advertising, and improve ads based on what they learn.
But, digital advertising across search, content, and social media channels, gives us an almost unlimited ability to generate data on what works and what doesn't.
That's what makes advertising at scale tricky (read: impossible) for humans. And it's what makes AI a natural fit for advertising.
With the right data, AI-powered ad tools can detect patterns at scale in your advertising data, then predict what changes to campaigns will improve performance against a specific KPI. This can all happen in seconds, rather than the hours, days, or weeks it might take a human to analyse, test, and iterate across campaigns.
Advertising costs a ton of money, especially if you're selling a product or service that doesn't produce an immediate return.
AI for advertising has the ability to increase your return on ad spend (revenue) and reduce the amount of money you spend on staff time and ineffective ad budget.
But, AI can actually go one step further.
In one high profile example we covered, an AI-powered advertising system actually helped a brand discover and convert new customers they didn't even know existed.
Case Study
Entrepreneur Naomi Simson, a host on Shark Tank Australia, owns a company called RedBalloon, which sells gifts and experiences online (think: an experience-focused Groupon).
She was spending $45,000 per month on ad agencies alone to run digital advertising for the brand. She was paying over $50 to acquire a single customer at the time. She lamented at the unsustainability of it in the long run.
Desperation drove her to investigate every possibility. She found an AI tool for advertising called Albert. The tool uses sophisticated AI to analyse ad campaigns, then manage targeting, testing, and budgets.
The tool was able to do things humans couldn't. In one day alone, it tested 6,500 variations of a Google text ad and learned from the experiment.
Over time, the tool was so effective at learning from data to improve performance that it skyrocketed RedBalloon's return on ad spend. The company was averaging a whopping 1,100% return on ad spend using the tool when we spoke with them. They had also cut marketing costs by 25% thanks to improved efficiency, all while improving results.
The tool also identified hungry potential customers that Simson didn't even know she had. The system identified from its experiments and the data generated by them that Australian expats were highly motivated to buy.
Normally, this wouldn't make sense. RedBalloon sells experiences in Australia, not the other countries where these Australians lived.
But, it turns out, the expats were highly motivated to buy gifts and experiences whenever they returned home, either for themselves or for their family and friends.
Also, the system identified people traveling to Australia from other countries as prime customers.
“I found markets in the US and UK of people traveling to Australia that I didn’t even know I had,” Simson mentioned.
She was so impressed, she started a company to add to her portfolio that acts as an exclusive distributor of the technology in Australia.
The story sums up the promise of AI for advertising in a nutshell:
Increase revenue by analysing and acting on data at scale.
Reduce costs by acting on that data faster and automatically.
Build a massive competitive advantage with both superior insights and superior speed.
