People know what marketing is, and probably have an idea about what AI is as well, but the two together? Not so much.
AI marketing definition
Artificial intelligence marketing is a method of using automation, specifically machine learning, to extract data, anticipate user needs, and improve customer experience.
AI marketing for digital marketers
Over the years, companies have learned to implement big data and advanced analytics to their methodology, thus allowing them to define what a target audience is and how to appeal to them. This pertains specifically to digital marketing given the extensive amount of online reader, user, and customer information brought in from monthly subscribers to casual site visitors.
Using big data and machine learning as AI marketing tools helps digital marketers boost the success and performance of their marketing campaigns, which can lead to a higher return on investment (ROI).
Before digging in to how marketers can use big data and machine learning for ROI and bettering marketing strategies, it’s important to be clear on what each term means.
Big data and machine learning in AI marketing
Big data refers to large amounts of structured and unstructured data that is too complex to be handled by standard data-processing software. Machine learning (ML) focuses on developing programs that access and use data on their own, leading machines to learn for themselves and improve from learned experiences.
When it comes to using big data for marketing purposes, the concept is pretty straightforward. Big data allows marketers to extract, aggregate, and segment large datasets via automation, not manually. After gathering and sorting the data, it can be analyzed to ensure that the best content and messages are not only reaching, but also positively impacting the appropriate audience.
As far as machine learning goes, ML algorithms help marketers with identifying trends, patterns, insights, commonalities, and abnormalities in data. Where big data helps with the extracting and sorting of data, machine learning helps with understanding issues, coming up with solutions, and predicting future outcomes in the near and far future.
Artificial intelligence, unlike some think, is not a threat; rather, AI is used as a benefit and supplement to business strategies, especially those of digital marketing. Other than automating tasks like data extraction, sorting, and analysis normally completed by human data analysts, AI is becoming increasingly more intelligent while working at an unprecedented speed.
Artificial intelligence has grown to the point that it is capable of benefiting multiple facets of digital marketing platforms, such as customer service and user experience (UX).
In fact, 61% of marketers say AI is the most important aspect of their data strategy. With a number like that, the advantages AI brings to a marketing strategy are highly valued and important as AI becomes more widely used in marketing.
Predictive analysis, audience targeting and segmentation, and chatbots are three examples show ways that AI marketing can benefit digital marketing strategies.
1. Predictive analytics
The core of AI marketing is using big data and machine learning to gather data so that it can be analyzed against a number of factors. As stated above, some of these factors might include demographic information, while others focus more specifically on website analytics.
Predictive analytics often include metrics like: page views, time spent on page, bounce rate, and click-through rate on calls-to-action (CTAs) among others. These metrics can be tracked by AI so that you, the marketer, can make informed decisions about which areas you should be dedicating more concentrated focus on in regard to your marketing strategy.
Extracting data from the above metrics can help you make informed predictions about future engagement. Rather than using data to retroactively analyze why something happened, you can now predict how to prevent the same thing from happening twice.
This not only amplifies future audience engagement by driving more people to your content, but AI allows you to enhance user experience on your site, encouraging new users to sign up and current users to continue regular engagement.
2. Audience targeting and segmentation
A facet of creating a personalized digital marketing experience for customers is knowing how to target the right audience for your content. By using customer data, machine learning algorithms can be trained to identify important, recurring patterns, such as demographic information about users based on specific pieces of content produced.
For instance, if your ML algorithm notices that 18 to 30-year-olds are drawn to your social media articles, but the 40 to 60-year-olds are drawn to articles about small business ownership or how to manage remote employees, you may want to focus content dissemination to each audience on different platforms: social media, email, via banner ads, and so on.
Additionally, the algorithm will be able to gather information about the time of day and days of the week that your content is accessed the most via social media platforms. Since this information cannot be tracked well by a human data analyst, AI machine learning algorithms can garner this information and help you learn the best time to post on Facebook or other social platforms for the highest levels of user engagement.
Using AI-powered chatbots for marketing can bring a wealth of benefits to your digital marketing strategy. Chatbots are chat robots that can converse with a human user through text or voice commands. The most obvious use of chatbots for marketing is customer-centered interactions. As a digital marketing platform, it’s crucial to have multiple ways for customers to contact your company during on- and off-hours.
For instance, if you have customers who live on a different continent than you, you’ll want to be accessible to answer their questions – especially something time-sensitive that could be the determination between a sale, a sign-up, or them moving on to a different company with a faster response time.
AI chatbots assist not only with customer inquiries, but also with gathering user data in a way different than machine learning algorithms do. A chatbot can garner data by sending a post-conversation survey to a customer. A survey like this might ask for a user’s demographic information as well as their purpose for visiting your site.
Most digital marketing websites not only have a dedicated Learn Hub or equivalent knowledge platform, but also have a product or software they’re pushing to sell. Chatbots can easily ask for – and often receive – user data much more quickly than other methods that rely on big data to access, sort, and filter user information.
Read our comprehensive guide on chatbots to help you decide if integrating chatbot software into your company’s website is your next move for marketing automation success.
What’s next for AI marketing?
As marketers grow more comfortable with the idea of adding AI into their marketing strategies, site visitors new and old will feel the benefits of artificial intelligence integration. There’s nothing to fear about big data, machine learning, or chatbot automation – all of these benefits and more will enhance the effectiveness of marketing campaigns and customer accessibility to come.
Rebecca Reynoso is the Senior Editor and Guest Post Program Manager at G2. She also works as a freelance editor and writer for a few small- and medium-sized tech companies. Outside of work, Rebecca enjoys watching hockey, cooking, and spending time with her family and cat. (she/her/hers)