Artificial intelligence is the next big thing in digital marketing. AI technologies are designed to make machines more intelligent. These technologies can process an immense amount of information and make sense of it in a human-like way. Artificial intelligence algorithms understand the context of information and predict future outcomes based on historical data, thus making marketing organizations more efficient.
AI covers a large range of capabilities: Natural Language Processing, augmented reality, predictive analytics, and other forms of interactive technology.
They all share common features:
- Continuously learning from user interactions and adjusting accordingly
- Finding trends and patterns in large data sets to generate predictions
- Making autonomous decisions and mimic human behavior
This article covers how digital marketing organizations leverage AI-powered technologies to drive costs down and performance up.
Artificial intelligence directly affects the marketing world and decision-makers
The potential applications of artificial intelligence in digital marketing are still being explored. To help marketers classify use cases, we refer to the 5Ps framework developed by Paul Roetzer, creator of the Marketing Artificial Intelligence Institute.
Planning: Building more accurate profiling
An essential part of digital marketing activities is market segmentation and audience profiling. Dividing customers into groups with common characteristics helps marketers better tailor their core message and improve customer experience.
Traditionally, marketers focus on basic segmentation criteria such as demographics or geographic location. However, AI and machine learning algorithms are now able to analyze more complex information. They can find patterns that are not visible to the human eye looking into purchase behavior, social media activity, and other large pools of data.
This allows businesses to build a more accurate picture of their customer base. With behavioral and psychographic segmentation, marketers can achieve a level of customization never reached before.
Production: Curating content
AI-powered technologies now have the ability to “read” and understand human language. This branch of Artificial Intelligence is called Natural Language Processing and opens various use cases in digital marketing. If AI algorithms cannot write long-form content or creative copy yet, they are a great asset for marketers to build a content strategy and personalize recommendations.
The challenge of a successful content strategy is not only to write content that is valuable to your audience, but also to make sure they access this content at the right time of the buyers’ journey. AI technologies can predict the type of content a visitor is most likely to be interested in.
AI-powered content management maps your content to the different segments of your audience based on their past consumed content and their readiness to buy your product. As a result, they show content that is most appealing to specific individuals in a highly personalized manner.
Personalization: Powering intelligent experiences
Personalization has always been a big thing in digital marketing. According to a Salesforce study, 64% of consumers expect personalized experiences based on past interactions with brands. Marketers try their best to resonate with the audience and individualize their messaging to achieve better conversion rates.
Pre-programmed personalization —e.g. adding names in emails, changing subject lines or currency based on location— is a manual process that requires marketers to guess what is appealing to each customer segment. AI-boosted personalization allows for personalization at the individual level instead of group segment.
The ability to capture and process complex customer data opens the opportunity to offer a hyper-personalized customer experience and boost customer engagement.
Promotion: Optimizing online advertisement
Artificial intelligence has also become a critical tool for online advertisement. Through predictive analysis, algorithms can help optimize targeting, ad content, and channels. They increase flexibility to better meet advertisers and customer needs.
Traditionally, marketers have been using A/B testing to determine better-performing ads content, and guessing the best channels and placements to reach their audience. Now, AI algorithms can continuously optimize ads placements and messaging based on response and engagement without human intervention. The more they are used, the more accurate they become.
On social networks, AI algorithms analyze customers’ interests to show ads only to relevant audiences. Programmatic advertising platforms also use machine learning algorithms to determine and bid on the best advertising space in real-time.
Performance: Turning data into intelligence
As data gathered by marketers grows exponentially, processing and analyzing that data manual has become inconceivable. The risk for improper interpretation and error in decision-making is too high. Businesses must rely on intelligent tools to consolidate data, remove inaccurate information and automate insights.
AI technologies are critical to make marketing analysis more agile and flexible. It allows marketers to identify patterns and predict future outcomes. AI analytics technologies can also uncover anomalies before they escalate and enable businesses to make data-driven decisions.
Predictive analysis is a tool for marketers to better understand the potential effects of the strategies implemented and adjust according to the desired outcomes.
Are customer action predictions changing the future of digital marketing?
The evolution of predictive analytics creates incredible opportunities for marketers. It took more than 20 years to go from simple reporting to predicting future actions.
Artificial intelligence and machine learning algorithms can anticipate customer behavior and predict future outcomes. Marketers use these insights to determine the best course of action and optimize results.
Customer prediction allows marketers to adopt a proactive attitude and improve customer interactions. Marketers use customer action prediction to make strategic decisions for the business.
- Churn: anticipate if a customer is about to cease the relationship with your company and know which action must be taken to retain the customer.
- Retention: measure and understand the customer’s experience with your product to resolve their issue before they arise.
- Satisfaction: improve customer satisfaction to increase loyalty, return rate and higher spendings.
- Engagement: discover the motivations behind your customers’ use of your solution in order to increase engagement.
Leveraging data to make informed decisions should be at the center of every business. Artificial intelligence and machine learning technologies augment marketers with advanced analytics capabilities and automate repetitive tasks to let them focus on more strategic activities.
If you’re looking to take your marketing planning and analytics to the next level, reach out to our team to discover how we can help your business generate more revenue with AI-powered technologies.