At first things like Machine Learning and Artificial Intelligence do sound weird in the field of digital marketing.
And once you get to know about the advances we get from them, you are surely going to be so keen to implement them in your marketing activities.
In this article, we will look at how Artificial Intelligence and Machine Learning can be used in marketing to their full potential.
We’ll start by understanding the fundamental concepts, firstly followed by their uses and the benefits that we can derive from them.
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So, let us begin with the journey.
What is AI & ML? Basics of AI & ML
Introducing AI and ML tools in the digital marketing industry helps marketers to scale their marketing strategies easily.
These tools make businesses more effective than ever.
And people always used to confuse these two concepts as the same, but these are two unique entities whose roles complement each other.
Thus, Artificial Intelligence is a vaster concept that makes intelligent machines simulate human thinking capability and behavior.
Whereas Machine Learning is an application or is a subset of AI.
ML enables those machines to solve problems and to read and provide certain information/data for the user in a more effective manner with the help of AI.
Thus, these were the two interesting facts about AI and ML. Now, let’s dive into its purpose in Digital marketing.
How Artificial Intelligence/Machine Learning Powers Business?
Artificial intelligence and machine learning are actually transforming and impacting a lot of industries.
From fashion to retail and from tech to finance. Above all, AI and ML are transforming the way business brands usually do.
And these two factors are also changing the way how a digital marketer interacts with their audience.
Machines nowadays are replacing humans as they are working in tasks such as voice-recognition, translation, visual perception,etc.
And we also use them in decision-making sectors, which involve human intelligence.
Artificial intelligence and machine learning involved together can accomplish these kinds of tasks independently.
Some future AI and ML predictions are that within 2025 there will be a lot of positive technology revolution momentums.
And this industry is going to grow in a fast phase and is going to cross across $190 billion.
What is Artificial Intelligence in Digital Marketing?
Artificial Intelligence in marketing uses online and offline customer data and analyzes it.
And then organizations act on that information to help drive conversions or influence human behavior.
So basically AI allows you to target users with the appropriate actions at the ideal time.
And through the right marketing, medium to advance them through the marketing funnel.
What Is Machine Learning in Digital Marketing?
Back in 1939 during World War II, Bombe was used. And It is a machine that was used to decipher the German Enigma messages.
Therefore, it was the first implementation of machine learning in its archaic form.
Machine learning is a subset of artificial intelligence that uses algorithms and statistical methods.
So it enables computers to learn and improve with no explicit programming.
Today, machine learning is commonly used in marketing for a variety of reasons like segmentation, predictions, etc.
Purpose of Artificial Intelligence and Machine Learning in Digital Marketing?
The digital marketing industry’s most famous key innovations were the use and implementation of AI tools.
This helps to assist and establish the marketing promotional strategies and to create businesses more practical.
And 90% of the marketing gurus believe that the digital marketing future lies in the hand of marketers who work with ML-based Tools.
As AI and ML come under a commonplace, it’s obvious that marketers will use and learn about how to use ML and AI in their digital promotional methods.
So, now you might have got an overview of AI and ML in digital marketing, so let’s look at a few examples of AI and ML in digital marketing.
Thus, these examples will help you understand how to get started with AI and how AI helps us improve marketing functions.
Computers creating content on their own was considered fantasy decades ago, but today we are at the vanguard of this vision becoming a reality.
Thus, Marketers, Bloggers, & Businesses of all sectors’ major goal is to create valuable content in order to be engaging for their targeted audience.
These content forms include informative blogs, articles, testimonials, webinars, vlogging, etc, as everything we see online is content.
ML and AI tools play an important role in this content creation process.
Therefore, they help digital marketers to understand, uncover, and to create data in a better way.
They allow marketers to get more reach with your content.
Thus, these tools keep track of the customers’ trends and produce actionable insights.
AI-driven content creation tools can create fresh stories and industry reports, such as financial and sports reports.
This makes it simple for people to understand the particular concept of that specific content.
And hence they could perceive the thought, they’ll be able to provide the insights in a lot more of proper and easier manner.
These tools function as specifically as a human brain.
They provide precise insights that people want to know in every business aspect.
Copywriting is also one of the creative aspects of content creation that AI is just getting into.
In the past couple of years, the digital world has witnessed the rapid adoption of chatbots and digital assistants.
So we can use them for various purposes from customer support to sales.
And the usage of this technology increases as people all around the world increase their usage of online messaging applications and Voice assistants.
Therefore, this has helped conversational AI gain prominence.
Chatbots are a fantastic boon in delivering the best customer service. And they are one of the popular forms of automation.
Thus, the difference between AI chatbots and regular chatbots is that it’s doable for chatbots to learn customers’ mindsets.
And it can understand users by following their data patterns.
Therefore, they then apply those patterns to similar kinds of issues or slightly different chats/queries.
Chatbots can converse with customers like a human.
And their round-the-clock availability allows customer care personnel to focus on more complicated concerns.
As said earlier, if a customer continues to embrace messenger apps like WhatsApp, Facebook, etc, are the utilities of a chatbot.
And they will continue to grow in the future.
Consumers are becoming reliant on digital assistants such as Amazon Alexa, Apple Siri, Microsoft Cortana, and Google Now day by day.
This has pushed brands to optimize their content for voice search.
A digital assistant pulls information from multiple resources and puts it into context.
The advanced language process provides it with the flexibility to enable them about whatever you are speaking or writing.
Search algorithms like Google Rank brain and Hummingbird have encouraged content that is conversational and focuses on long-tail keywords.
And In order to know the different ways, you can include bots, check this link out: https://neilpatel.com/blog/bots-digital-marketing-strategy/
These traditional segmentation criteria are restricted depending on their demographics.
That includes their gender & age, firmographics, psychographics, etc.
Whereas, if we talk about AI-driven segmentation, then it allows marketers to segment their audience on a more atomic level.
The various MarTech tools collect thousands of data points that can be put to good use by using AI to uncover trends and patterns.
So, by using Machine learning algorithms, we can analyze the heaps of data.
And can categorize users depending on their characteristics, interests, past behavior, or purchase pattern.
For example, based on product usage and subscription data, you can identify customers that are discontinuing your services.
Thus, with the help of this information, you can start a marketing campaign to reduce the number.
Our next point, Predictive Analytics, helps in doing the groundwork to identify the customers showing signs of discontinuing product usage.
Predictive analytics uses customer’s offline and online data to predict their future actions and behaviors.
They help us provide effective prerequisites strategy, such as,
- When we provide the machine learning algorithm with an enormous amount of customer data.
- These algorithms create a prediction/propensity model that predicts the outcome.
- You can use predictive analytics to predict customer lifetime value.
- And you can also identify the right marketing channels and messages, and predict customer behavior.
- The key to the success of this approach is the quality of data provided to the algorithm.
- If the data provided is inconsistent or error-prone, then the output will not be accurate and precise.
- When we provide the machine learning algorithm with an enormous amount of customer data.
When a new visitor lands on your site, you need to give him/her a reason to keep them coming back.
Therefore, 1:1 personalization helps you in connecting with your visitors and customers directly.
The connection can be through your website, apps, emails, and other digital platforms.
When someone leaves your website without completing their purchase, you can do two things.
One is that you can send a cart abandonment email.
And the other is that we can provide a special offer to motivate them to complete the purchase.
Similarly, when a user registers for your product, you can send them an onboarding email.
And also notifications to help them understand the different aspects and features of your product.
Optimizing paid ads is one of the biggest advantages of using artificial intelligence in marketing.
Artificial Intelligence (AI) is changing the entire industry, it is also providing fresh ways to promote and monitor the paid ad campaigns.
This is having a key influence on how we approach these ad campaigns and how to begin with.
Google and Facebook’s advertising platforms are both integrating AI features into their frameworks.
As a result, there is going to get a large no. of opportunities for AI-driven ad campaigns.
And this helps to unlock more strategy development time.
So, these tools help you by providing metrics you need that help you drive more traffic and help your business grow forward.
Based on top performance drivers, they help marketers to make better strategic plans and decisions.
They help you overcome the struggles, which kept you away from achieving your paid ad goals.
It is an iterative process, and AI can help you in the following ways:
Programmatic Ad Targeting
AI helps us by gathering and organizing a massive amount of data about every visitor who uses online means.
This data helps marketers to separate audiences and helps to serve more applicable and personalized ad content for those users.
Sometimes, it is even possible to use AI to adjust the creative ads, based on the targeted user who is going to see that ad.
Above all, marketers constantly need to monitor ads performance.
This helps them to understand which type of ad is performing better. And also helps them to know the optimal time of the day to serve ads, and so on.
Therefore, AI can perform these activities on its own.
And it can also automate the bidding process itself to help you use your ad budget effectively.
Re-targeting and Lookalike Audience
Re-targeting campaigns are reminders for your visitors and motivate them to come back to your website.
Complete a particular action, or they can also keep existing customers.
It permits advertisers, easily reach out to their customers who have already engaged with their product/service.
As a result, this increases connection, relation, exactness, and the rate of engagement.
Lookalike audience uses your existing audience base to find new audiences.
This audience shares similar characteristics, interests, behavior, etc., and helps in building a network.
Sales forecasting uses past sales data, trends, patterns, and information about upcoming events to predict product demand and sales.
Accurate sales forecasting directly affect the short-term and long-term growth of an organization.
We usually do forecast everything in our life, but the forecast made in Digital marketing helps us to provide lots of insights.
It will be served as one of many data points.
It allows marketers to guide reps about what is the exact time to take a step for our next move.
Along with the data of real-time sales forecast helps AI/ML to score.
AI also strengthens the lead scoring process, which helps in identifying the leads that are most likely to buy from you.
Similarly, AI also helps in sales forecasting by improving deal closure, customer retention rate, and increasing customer lifetime value.
So, AI-powered sales forecasting enables organizations to plan their future better while ensuring the resources and personnel are efficiently utilized.
Discounts or coupon codes are great motivators to complete a purchase rather than to push general sales. But improper planning can hinder your sales.
Above all, dynamic pricing can solve this issue as it considers past purchases and purchase patterns. With minimum alterations in pricing, they try to motivate the consumer to buy.
So, if the user history states that the user completes a purchase and then they received a special discount, so what to do next to make them purchase?
You could offer a coupon that would compel them to make the purchase.
It also ensures that you’re generating sales without taking a hit on your profits.
Recommendation engines are tools that improve customer experience and increase engagement by providing content and product recommendations.
Thus, these engines will considerably boost revenues, Click-Through Rates (CTRs), conversions, and different essential metrics.
As a result, it will have positive effects on the user expertise, so translating to higher client satisfaction and retention.
They are widely used by e-commerce websites, e-learning, online gaming, and audio/video streaming services to increase product stickiness.
And then you must have seen suggestions such as ‘people who bought Product A also bought Product B.
This is a recommendation engine in action.
However, recommendation engines use three different algorithms.
They are collaborative filtering, content-based filtering, and hybrid recommendation algorithms.
These collaborative filtering algorithms analyzes the behavior of multiple users and draws similar characteristics to recommend products.
Similarly, a content-based filtering algorithm uses the correlation between description, words, brands, and colors, etc. to suggest products.
Using Artificial Intelligence Across the Buyer’s Journey
Firstly a buyer’s journey comprises three phases: Awareness, consideration, and decision.
In the awareness stage, the customer identifies a need or a problem and starts looking for its solution.
After that, it is followed by the consideration stage where the customer searches for alternatives.
And finally, he/she reaches the decision stage, where the prospect zeroes down on one solution.
Besides it, you can implement Artificial Intelligence and machine learning solutions in the buyer’s journey.
That would significantly improve your marketing efforts.
For the awareness stage, you can focus on creating and optimizing your content for voice search.
Moreover, we can also do that by using chatbots to deliver content and attracting visitors with personalized content.
Therefore, when a user is in the consideration stage, and the organizations can focus on remarketing ads to grab the user’s attention.
And the user will be in the decision stage, with the help of dynamic pricing and chatbots.
And in this way, organizations can drive the visitor to the purchase.
The Benefits of Artificial Intelligence in Digital Marketing
So now we have got to know that AI is going to be an integral part of digital marketing. Let us look at how AI continues to benefit organizations.
Predicts Customer Behavior
Firstly, AI makes it simple to predict your customers’ future behavior.
When you collect data points that help you understand how your users are using your product and interacting with your brand.
Then AI helps you to use this data to predict their future actions.
Scales Marketing Campaigns
Before initiating a large-scale marketing program and investing all your money into it.
And also you can test it out on a focus group to verify its feasibility and response.
This is called the minimum viable campaign and also minimum viable marketing.
With this, you can scale your marketing to its maximum potential.
Improves Customer Experience
In this age, customers expect more from brands.
And AI enhances marketing efforts throughout the buyer’s journey.
Therefore, chatbots have access to the customer’s history, so they can help customers more than human agents.
So, now you might have understood the importance of implementing artificial intelligence in your marketing activities.
Above all, each advertiser and publisher likes the application of AI in programmatic advertising.
However, they’re not the only ones who get profited by implementing AI, but even customers as well.
Therefore, Personalization has become a core aspect of marketing, and AI is the core facilitator of personalization.
Above all, this concludes that the sooner you start with AI, the faster you will adapt. And also will be prepared for a future that’s powered by AI.