Nat Caesar
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AI & ML (Machine Learning) have their fingers in various areas of the digital marketing pie – and, for good reasons. The two fields are on an inevitable path to changing the way in which brands interact with consumers.
From personalization to targeting, there’s nothing that a healthy dose of AI or ML can’t do. But where to start?
In this article, we’re going to look at the eleven areas in which AI & ML will be making a dent in the upcoming digital marketing industry.
Ready? Let’s dive in.
What Is AI & ML?
Artificial Intelligence (AI) is composed of a set of computer systems, which are designed to house knowledge and expertise. They use this knowledge to create self-learning systems that can learn from data, without needing human input.
Basically, these systems can ingest information, learn from it, and react accordingly.
Machine Learning (ML), on the other hand, is a subset of AI, that can learn from experience without being humanly programmed to do so. Both AI & machine learning have the ability to mimic the thinking process of humans, learning as they go.
11 Ways AI & ML Can Improve Digital Marketing
1. Predictive Analytics
Predictive analytics is quickly gaining momentum, as most marketers agree it’s a powerful tool for leveraging data.
But what is it exactly? Essentially, it’s the process that allows digital marketers to extrapolate data from audiences, to predict what actions will be taken.
Some of the biggest companies in the world use predictive analytics. Gaining a deeper understanding of their clientele allows them to gain a competitive edge, and ultimately, more loyal customers.
Below is the broad process of how predictive analytics work:
It’s also important to know that the more data is collected, the better the results. By refining these algorithms, marketers, and brands can create better results, i.e. more qualified leads and sales.
For example, if you have a complex marketing campaign, a predictive analytics modeling will allow you receive an estimated outcome for how successful your campaign will likely be.
2. Sentiment Analysis
Sentiment Analysis is a process that uses NLP (Natural Language Processing) to detect an individual’s emotional response. This mainly occurs on social media, in response to branded content.
The most common way that marketers use sentiment analysis is to understand how a target audience feels. As a tool, it has been around for many years, having first been developed in the 1950s. Despite its early arrival, it has never been as readily available as it is today, especially with the upsurge of social media.
These insights can help marketers to tweak and adapt their tactics and develop more effective marketing campaigns.
3. Usability Testing
The success of software development is heavily reliant on how seamless it is. This is where usability testing comes in.
The goal? To gain insight into which features are intuitive and which ones can be improved. It’s important for marketers to understand which features appeal to their target audience, as form follows function.
Usability testing is becoming increasingly popular, as AI and ML deliver a better-customized user experience (UX).
One of the most elementary ways that AI is improving usability testing is through facial recognition.
Facial recognition is used to determine user reactions to elements of UX/UI. After facial recognition, the next step is affective computing – which analyzes voice inflection and tone as well. These advances will lead the way for machines to eventually emulate empathy – a trait that humans have developed over many years.
With the use of usability testing, brands are finally able to best understand their users. Spot-checking and error-proofing marketing campaigns has never been easier!
4. Customer Experience (CX)
The use of AI-powered chatbots has exploded in recent years. Virtual assistants such as Alexa and Siri are now famous in their own right, with their popularity set to rise even further. In fact, the way chatbots work has drastically evolved since Eliza, the first ever chatbot.
Chatbots are becoming more and more sophisticated, and are now able to converse with people in a realistic way. Companies that require employees to interact with customers by phone or email often result in an unsatisfactory customer experience.
Because of this, companies are beginning to see the value of using chatbots as an alternative engagement method. Deploying bots can help to fix some of the most common problems with customer service.
A chatbot can even send an automated email to the customer in response to their message, which is more personalized.
5. Social Listening & Analysis
Social listening is the process of analyzing social media data in real-time. It allows companies to gain an understanding of consumer feelings surrounding their product.
This type of analyzing tool is a great way to measure brand sentiment, as brands can determine what they need to do to improve. Additionally, companies can also gain insight into competitors’ current marketing tactics, in order to make improvements.
Social listening is crucial for consumer-based marketing. Interactions that companies have with their audiences, can provide a vast amount of information regarding consumer sentiment and behavior.
Through NLP, AI allows marketers to gain valuable insights, such as understanding whether a product is in demand or if it needs to be improved.
6. Content Creation
Within content creation, AI can also be worked into the mix. Not only will it be arguably more accurate – but it can also be more time and cost-effective…
With AI & machine learning, content creators are able to:
- Provide content that is more personalized and relevant to each visitor e.g. through blogs, emails, landing pages, etc…
- Create large amounts of content quickly
With the ability for content creation to take place quickly, marketers will be able to produce better results in a shorter period of time.
We can expect to see this practice, of using AI, become more widespread as technology becomes easier to harness. AI writing assistants like Jasper are already starting to become common tools within marketing departments and content producers.
The use of AI in content marketing can offer many benefits such as:
- saving time to create content
- increasing workforce productivity
- reducing the number of errors in copy
- overcoming language barriers
- optimizing articles for better SEO results
7. Content Optimization
Search Engine Optimization (SEO) is the process by which content marketers optimize content to increase a website’s visibility. Having a higher ranking within SEO will encourage engagement with any given brand.
Because of these benefits, SEO has become one of the most preferred digital marketing techniques. The AI-powered tool, Surfer SEO, for instance, is popular SEO software, and is being used by more and more SEO experts. By analyzing data points in the SERP, this content optimization tool scans top results to come up with optimization guidelines and provides a score to tell you how optimized your blog posts are.
With so much potential to affect SEO, AI & machine learning can help to improve how marketers approach their SEO strategies. Creating better content and making it stand out in the SERPs is something every leading business what’s a piece of…
8. Cross-Channel Marketing
Cross-Channel Marketing, in a nutshell, can help increase every marketing metric. Why? Because it involves everything from e-mail marketing to social media, creating a cohesive and consistent digital marketing strategy.
Strong brands use cross-channel marketing to develop a targeted approach, allowing them to reach users in many different ways.
AI and ML can play a huge role in this process.
For instance, AI can be used to segment and classify potential customers based on what marketing channels they prefer. This allows brands to track the types of content users respond to, and use that information for future marketing initiatives.
AI can also ensure brands are targeting consumers at the correct stages in the funnel. For instance, if a user is interested in a product but hasn’t yet purchased it, an automated, personalized message can be delivered in order to encourage conversion. That way, companies can prime users to buy products at a later date.
Brands can also use AI to set customer expectations. They do this by monitoring what a consumer searches for online, and aligning their brand messaging accordingly.
9. Purchase Decision-Making
Purchasing decisions are can see many forms: long summarizing times to decide on an expensive purchase, or, impulse buys.
Retailers have already jumped the bandwagon, and have implemented AI into their services, to predict purchases. Another nifty tactic is having AI make suggestions at the precise moment the consumer needs it most.
Having an AI take care of the customer means more time is spent on other parts of the marketing strategy.
AI can also reduce the uncertainty that comes with purchasing a product. For example, chatbots can be trained to answer product queries in a way that is more personalized to a customer’s needs.
To summarise, AI-powered chatbots deliver customized services depending on the customer. It takes into account their purchasing preferences, and delivers the most effective marketing messages based on their answers. As a result, this can reduce customer frustration and help increase conversion rates.
10. Social Media Analytics
Social Media Analytics is increasing in importance as social media usage continues to grow exponentially. But what if there was a way to make things even easier? Say hello to AI and ML.
With AI, marketers could have more data to review and use to make better-informed social media marketing decisions. Machine learning offers many benefits to social media marketers such as:
- a greater ability for predictive analytics
- faster data processing
- better user targeting capabilities that allow for custom audience lists
- the ability to measure ROI from campaigns and ad copy with improved accuracy
Pairing AI with ML can help develop a more robust and comprehensive social media analytics solution. This can be used to better understand what is working and what isn’t, increasing the chances of success for future campaigns.
11. Data Insights and Analytics
Another great way for brands to capitalize on AI is through Data Analytics.
Because of the increasing amount of data, marketers can acquire greater insights into their audience. This can lead to more targeted campaigns, better SEO efforts, and higher levels of customer engagement.
The use of AI can also provide important insights into the customer experience. This means that marketers can be able to find critical patterns in user behavior, such as:
- What brought a visitor to a certain page in the first place
- Which pages consumers are returning to frequently
- Which section of an article is most consumed
These insights can help marketers know what content or offers to create for maximum impact. Data science, a buzzword of the last few years, has become increasingly important in marketing.
AI offers companies a powerful way to better understand their consumers, and increase the effectiveness of their campaigns.
Wrapping up
AI & machine learning have similar underlying philosophies. However, their approaches are entirely different. In digital marketing, both solutions can automate projects, content, teamwork, increase user engagement with brands, and so on.
With the rise of technology, it’s realistic to say that AI will have a significant impact on digital marketing in years to come.
The possibilities for what AI can bring to the table for organizations are endless. Allowing marketers the potential to have more control over their data, reduce marketing costs, increase work efficiency, and drive improved results is an exciting development.
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