Technology is evolving and the world of online marketing is evolving with it. Artificial intelligence (AI) as well as machine learning (ML) now make a wide variety of marketing tasks easy, even those which would have been impossible just a few years ago.
Brands and marketers are now leveraging AI digital marketing to save time and resources through automated digital marketing services and new channels.
Here are 8 examples of how artificial intelligence is currently being used in digital marketing:
1. Search Engines
AI performs quality control in the search industry. Just by separating high-quality content from the low-quality spam, it protects search engines from manipulation. Google, for example, uses a machine-learning AI system called “RankBrain” to help sort through its search results.
Sundar Pichai, Google’s CEO, mentioned during Google’s I/O developer conference keynote that AI is now interwoven into everything Google does – especially with products such as Google Lens – Google’s engine for seeing, understanding, and augmenting the real world, a tool which is becoming available on all of it’s platforms.
All in all, artificial intelligence is taking the SEO industry to the next level.
Businesses are integrating chatbots into their inbound marketing strategies. They believe it will lead to improvements in efficiency and customer satisfaction as relevant information is handed to the customer at the time they need it the most.
Here are some examples of the best AI chatbots:
Starbucks: A chatbot can now take your order on Starbucks app – You can talk to it or text it. It will tell you the time your order will be ready and the total cost.
Pizza Hut: Pizza Hut uses Facebook Messenger’s chatbot to help you order your pizza. It can tell you all about their ongoing deals too.
Future possibilities for chatbots include proposing strategy and tactics for overcoming business problems and allocating resources to deal with customer cases based on the classification and sentiment analysis of the conversations they are having.
3. Content Creation
Thanks to AI and ML, marketers can now meet the demand for content and redefine the way content creation and delivery occurs. Content curation tools provide efficient and accurate content choices thanks to machine learning-powered predictive recommendation engines.
With the goal to move a prospect through the awareness stages, this can help marketers create relevant content for their audience at each stage of the marketing funnel.
4. Predictive Intelligence
Predictive intelligence help companies understand an individual customer and personalise content such that it appeals to their needs and interests.
One example of the usage of predictive analytics is in lead scoring — a points system used to determine where a prospect is in the buyer journey. This allows marketers to fast-track the sales process by ascertaining which customers are ideal to convert, depending on their past behaviours and history.
5. Dynamic Pricing
AI and ML models have had a large impact on dynamic pricing methods.
Widespread in both the air travel and hotel industry, and famously well executed at Amazon, companies are now utilising this pricing to respond to changes in demand and to drive significant increases in revenue.
6. Marketing Automation
If the marketing message is not relevant to the audience, customers will tune out as their expectations are not met.With a combination of AI and marketing automation marketers can now predict the right messages for the right people.
Marketers can then enhance their campaigns and programs by drawing on everything they know about their consumers to tailor experiences with speed and precision, even on a massive scale.
7. Ad Targeting
There are many ways that marketers can use AI, but so far, targeting and audience segmenting are among the most common uses for the emerging technology.
Programmatic advertising uses artificial intelligence technology in their algorithms to analyse a visitor’s behaviour allowing for real time campaign optimisations towards an audience more likely to convert.
Responsive search is also an advertising tool that has now been streamlined by the Google Marketing Platform. This program asks advertisers to submit anywhere between three and fifteen different creative ad layouts and as many meta-descriptions to Google’s ad database. Google then uses its gathered data to determine which ad, from a collection, is right for each particular instance autonomously through the use of AI.
8. Personalised Product and Image Recommendations
With the help of ML, personalisation and image recommendations are now made thanks to data – this can offer suggestions for something that might interest a user.
Such ML technology can be seen with Netflix’ algorithm update. This update applies to the thumbnails we see before clicking on a show or movie. Depending on our search and watch habits, Netflix’s algorithm decides which thumbnail photo to display in order to get users’ attention and get them to click on that show.
Through these examples and real-life applications, we can see how much of an ally AI and ML can prove to be in marketing. Not only do they save us precious time, but they also prove to be exceedingly efficient and accurate.
AI individualised and caters to the customer through steps that are virtually impossible for real-life marketers to do so manually. This, in turn enables businesses to grow, adapt and thrive.