How Artificial Intelligence Is Transforming Digital Marketing
I’m sorry, Dave. I’m afraid I can’t do that.
One of the most sinister quotes in the history of cinema was uttered by HAL 9000, an intelligent, omniscient supercomputer controlling the doomed Discovery 1 spaceship in Stanley Kubrick’s 2001: A Space Odyssey.
A number of other sci-fi flicks also painted intelligent machines in a similar fashion – as antagonists trying to enslave mankind.
But, apart from being menacing and ominous, these robots powered by AI were also fascinating and capable of completing different sophisticated tasks and outthinking and outperforming humans.
Although artificial intelligence is still at its infancy, this technology holds tremendous power to revolutionize almost every industry out there.
And make no mistake, it is transforming digital marketing.
Detailed and Granular Analytics
Brands heavily rely on accurate customer information when it comes to the success of their digital marketing efforts.
Precise customer profiling, that is, precisely defined ideal customer profile and buyer personas allow brands to segment their email and content marketing efforts, as well as personalize their messaging.
Stats say that this approach leads to a 171% increase in marketing-generated revenue.
So, the trick is to gain an insight into consumers’ needs, spending habits, and purchasing motivations.
Collecting, analyzing, and interpreting massive amounts of data about their target audience’s interests, needs, preferences, and pain points is a task of gargantuan proportions.
First of all, all these bits of data come from different sources and channels – emails, social media posts, product reviews, etc.. This means that they’re unstructured and not organized in traditional row-column databases. And regular analytics can identify patterns and make sense only of structured data.
AI, paired with big data analytics, can overcome this obstacle.
As a matter of fact, although this technology is mainly identified with human-like robots, leveraging the power of data is one of the most important abilities of AI.
By tapping into such next-generation analytics, brands can deliver the right, highly personalized content, craft targeted email campaigns, and offer product recommendations.
Will AI replace humans by taking over their jobs?
That’s one of the most common concerns and reasons why the topic of the pros and cons of AI is brought up so often.
So far, content marketers don’t have to worry (at least not so much).
Superb, high-quality content is the backbone of every successful digital marketing strategy.
AI still can’t achieve the same level of uniqueness and creativity as human writers when it comes to generating content. Besides, despite being supported by machine learning and natural language processing, this advanced technology still lacks critical thinking, necessary for stealing content creators’ jobs.
However, the role of Artificial Intelligence in generating content is still valuable.
You may also want to read: How Integrating AI Into B2B Marketing Can Scale Your Business
A Couple Of Examples Of AI Writers
Different news companies and sports media outlets, such as ESPN, Reuters, and The Washington Post, have been leveraging robot writers to create reports and short stories for a couple of years.
Cyborg is an AI system used by Bloomberg News to help human reporters produce thousands of company earnings reports quarterly. This task is boring, repetitive, and low-value, and this sophisticated program can churn out these reports quickly. This frees up reporters to focus on more challenging well-researched stories. With the help of Cyborg, Bloomberg tries to stay ahead of its fiercest competitor, Reuters.
Similarly, Heliograph, a robot writer for the Washington Post, has been covering local high-school football games, the Rio Olympics, as well as gubernatorial and congressional races in the Washington area. Although simple and short, the stories that Heliograph whipped up managed to generate a fair amount of clicks.
The Future Of AI Content
The future of content lies in AI, and a recent example from Japan shows that intelligent machines will soon overcome the barriers of creativity and uniqueness, and take charge of more complex content. Namely, a Japanese robot writer almost won a literary award for authoring a short novel.
Still, as visual content is on the rise at the moment, it’s important to mention that it will be changed by AI too. For example, there are tools powered by this technology that allows content marketers to create and edit videos easily on their own. Lumen5 offers an exciting functionality – it can repurpose written content and turn it into videos in no time.
Customer Sentiments and Intent
Customer experience is about to overcome price and product as the key brand differentiator.
It’s clear that companies need to pay attention to what their customers think and talk about them.
But, the trouble is that it can be complicated to monitor what they’re telling other people on the internet and their connections on social media networks. That’s how a small crisis can snowball into a big PR issue.
Luckily, social listening tools can prevent this.
Natural language processing, a subset of AI implemented in these tools, has the ability to analyze conversations across the internet and social media channels, and pick up the overall sentiment.
This way, brands are able to take action and do something about the underlying issue.
Samsung leveraged social listening tools to identify and mitigate the problem with their customers’ dissatisfaction over the red-tint issue on their S8 model back in 2017.
Apart from monitoring their social media presence and eavesdropping on what their customers are talking about them, brands can use similar technology for identifying purchase intent. Again, natural language processing analyzes the way people talk about brands and products and interprets their sentiments.
With such valuable insights, companies can target interested customers and show them a particular product or service via an ad or other type or by offering them a discount.
You may also want to read: Sentiment Analysis Tools That Will Transform The Way You Work
This is one of the most commonly used AI features.
Every time we want to watch something on Netflix or purchase an item on Amazon, we’re taking advantage of advanced recommendation systems.
The streaming giants have taken personalization to the next level with their recommendation engines. They take into consideration a number of different parameters and filters to offer the most accurate suggestions to their users.
Examples of these parameters are:
- Interactions with the service
- Users with similar preferences and tastes
- The times of day when the content is watched
- The devices used for watching are among the factors
Amazon’s product recommendation engine works in a similar manner to the video recommendations. It helps its users to discover products that are of interest to them and that they wouldn’t be able to find on their own, or would have to spend a lot of time searching.
Although this proprietary algorithm is a secret, what we know is that with every user interaction, it gets smarter and better in recommending. Some of the signals Amazon uses to enrich its algorithm are
- The items customers bought in the past,
- The products that customers reviewed or liked, or
- Products that customers who viewed the same products purchased.
To be able to handle millions of customers and products in real-time, Amazon leverages a neural network. In other words, the retail behemoth created DSSTNE to train neural networks and create personalized recommendations at scale.
Artificial intelligence will, no doubt, continue to revolutionize digital marketing and help brands understand how to best attract and serve their customers.
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Aran Davies is based in Swansea, Wales. He attended the University of Gloucester, earning a BS with honours in computer science in 2003. He is the blockchain expert, developer and head of content at DevTeam.Space. You can connect with Aran on LinkedIn by clicking here
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