Digital marketing is currently the fastest growing marketing segment. Its goal is to both reach out to and build relationships with clients. That’s why it is extremely important to optimize your activities on the internet. Optimization allows more frequent and significant changes to the campaign. This is where AI and Machine Learning in digital marketing steps into the game. Additionally, it allows more effective use of collected customers data such as:
•clicks
•impressions
•time spent on the website
•the number of transactions made and many more
Systems based on continuous analysis of up-to-date data will improve the results of your marketing performance in the internet.
Marketing campaigns are more than just delivering messages. Time and the manner of their delivery are also important. Without a data-driven approach, campaign-related opportunities can easily be overlooked. Problems may arise when launching a new campaign. Machine learning in marketing is an ally of everyone who wants to maximize results when putting the same amount of work into tasks and marketing projects.
AI in Digital Marketing for Cost, Time, and Profit Optimization
The aim of Machine learning is to take advantage of the achievements in the field of artificial intelligence (AI). With the help of AI in digital marketing, we are able to create an automatic system that improves performance. Thanks to systems that use machine learning, you can:
•optimize time and costs
•make decisions faster and in a more profitable way
•create better communication tailored to each customer with ML algorithms.
Machine learning could also help to improve content marketing, advertising, and sales processes. This type of software connects to other internal systems such as CRM or marketing automation. Thanks to such solutions, advertising campaigns are conducted more precisely. Additionally, collected data allows you to better target your potential clients.
Optimizing campaigns by using machine learning improves cooperation with potential clients and generates revenue. It can also generate a high return on marketing investment (ROI).
AI in Digital Marketing – use cases
Customer churn prediction
Retention is the main problem in all industries. Retaining a customer is 5 times cheaper than acquiring a new one. By analyzing the changing behavior of customers, algorithms are able to detect the riskiest customers. AI algorithms for digital marketing are able, in an automatic way, to predict which customers are most likely to stop using your product or services. That information would help you react accordingly and retain customers who are planning to leave.
Customer Lifetime Value Prediction (LTV)
Customer Lifetime Value (LTV) measures all the potential profits a particular customer can bring to your business. Machine learning algorithms for marketing will help you to understand the patterns and categorize your customers according to their LTV predictions.
In this way, you will know which categories are likely to spend the most money.
Recommendation engine
AI algorithms can predict customer preferences and propose personalized offers based on the behavioral data of every customer. With the acquired data on the behavior of customers with similar preferences, the algorithm can predict what kind of products or services may draw the attention of the particular buyer in the future. With AI in digital marketing will definitely support and personalize your cross-sell and up-sell activities.
Conversion prediction
This can be divided into 2 rates. First is the probability of purchase (mainly for e-commerce, retail and similar industries). The second one is the probability that leads will convert into an opportunity/customer.
1.Based on historical sales activity AI algorithms can determine the probability of a particular lead convert into an opportunity or customer. The sales team can use that information for better lead segmentation and prioritization. The gained knowledge will help them to understand why leads are likely to convert or not.
2.Machine learning on the basis of users’ demographic data, activity on the online shops, loyalty program activity, preferences, and interests of each user can predict the probability of purchase in a particular time or event. That can be used for real-time marketing (show discount when customer hesitates) and support the product recommendation system.
Customer segmentation
AI algorithms in combination with big data from marketing campaigns can be used for finding your customer segments. Auto-segmentation algorithms will automatically learn on various behavioral data points and give you insights. Using such segments you can understand better what types of people are close to each other. AI in digital marketing will help you to understand customer groups within your business.
Later, you can use this information to improve customer satisfaction and user experience.
Dynamic pricing
Price optimization enables you to adjust the price of products by a particular customer’s ability and willingness to pay. It will give you an opportunity to maximize conversion and revenue. Because people are more likely to buy goods that fit within their budget, AI algorithms will also analyze prices, previous sales, and revenue transactions to set prices, which would maximize your profits and purchase probability.
Messages personalization
Another application of AI in digital marketing is Personalization. Personalization is the creation of messages that correspond to the specific needs of a particular customer. Machine Learning based on demographic data, interests, and behavioral data can create a personalized message. This message for a particular user will be delivered with the right topic at the right time.
If the user receives a marketing message with content that is thematically related to the problem he is looking for, he is much more likely to make a purchase decision.
Personalized content on website
One more example of AI in digital marketing is content personalization. Appropriately personalized content on the website increases content popularity and raises customer involvement. Machine learning can automatically find patterns and match them with the personal preferences of a particular customer based on past activity. That will help you to improve customer experience and customer satisfaction.
AI-powered website builders
AI in digital marketing is also used in website development. One of the real-life examples is the AI-powered web design platform, The Grid. Based on user data and how it interacts with your content, the platform can build a website for you.
Moreover, this platform has an AI developer, who will customize the colors and content blocks for your upcoming web pages. Other AI-powered website design platforms include FireDrop and Wix Artificial Design Intelligence.
How does it work in practice? – AI in Digital Marketing
In practice, the above-mentioned solutions are integrated into companies' internal business applications, CRM systems, or e-commerce platforms or websites. According to Marketing Profs, companies which are implementing AI in digital marketing are seeing 59% better closing rates, 58% more revenue growth, 54% more traffic and engagement, and 52% more conversions.
To Sum Up
What is AI in Digital Marketing?
Artificial Intelligence in digital marketing transforms customer-centric services for digital marketers by improving efficiency and optimizing user experience.
What are the Benefits of AI in Digital Marketing?
AI technology has many uses in digital marketing. Here are some of them:
•customer churn prediction
•messages personalization
•conversion prediction
•customer segmentation
•dynamic pricing
Why are Companies Implementing AI in Digital Marketing?
Today, AI is an effective and valuable tool for digital marketers in companies. With the great potential of AI in digital marketing, companies can maximize revenues, improve customer satisfaction and better target their potential clients.
What are the AI tools in Digital Marketing?
Artificial intelligence (AI) is vital to the success of any marketing campaign. Companies that make full use of AI have a competitive advantage over their competitors and use such AI tools as:
•Google Could AI
•HubSpot
•Atomic Research
•Cortex
•Bramework
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