Most brands, online businesses and digital marketing have begun to utilize Artificial Intelligence (AI) when interacting with potential clients to boost conversion rates and ROI (Return on Investment).
With power of Artificial Intelligence and Machine Learning, we can customize buying processes and construct simulation models via predictions and suggestions based of previous marketing data and consumer habits. This helps us identify future trends and make accurate forecasts.
Most e-commerce ventures utilize AI in their digital marketing campaigns as well, indicating that marketers have realized the potential of this technology. Below is a list of areas of “how” and “where” Artificial Intelligence is being used in modern marketing.
Programmatic Media Bidding
Programmatic Media Bidding entails the complete automation of the selling and buying of Ad spaces. These technology-based models have machine-learning features, utilize potential clients’ data, and display relevant ads to the target clients.
Since machine learning and AI algorithms support these models, the produced results are much more accurate and with minimal errors. Algorithms help analyze the customers’ behaviors to adapt them and craft personalized Ad content. Client and Consumer information is gathered regularly and used to further improve Ad content optimization.
Ad Targeting
AI utilizes machine learning algorithms to analyze clients’ historical data to establish the ads that suit the target customers. Using data and trends, Google advertising + Artificial Intelligence enables you as an ideal marketer with optimization advantages to deliver content at the right time and the right place.
Most clients want to see ads that address their concerns and those that relate to their liking. Ad targeting allows marketers to custom-tailor ads to suitable clients to ensure they communicate with those likely to respond and become successful conversions.
Marketers can develop an effective ad-targeting campaign with the help of algorithms and the digital superintelligence of AI models. Targeted marketing campaigns allow marketers to reap big from the full advantages of Artificial Intelligence to stay ahead of the competition who are still stuck on traditional methods.
Case Study: Ezoic
We have a similar example of this with the Ad-Publisher Company “Ezoic”. They are a Google-Ads partner who utilize the power of AI and Machine Learning to create “intelligent Ad layouts”. Thousands of different Ad-layout combinations are tested in different positions and size to find the “optimal” solution with the best UX and Revenue.
These techniques allow them to generate 2-3x as much revenue as compared to Google AdSense. If Ezoic can use AI and ML to boost revenue, so can you!
Predictive Analysis
Most people are excellent at extracting insights from an extensive volume of data, while others take time when extracting helpful information from complex data. AI can extend a helping hand to marketers in such cases to save time and ease their work.
Predictive analysis utilizes the available data to allow marketers to obtain helpful insights and make future prediction. It also helps you diagnose your website/business by identifying what’s wrong or right based of past experiences.
Most importantly, It lets you know what your target audience wants and is willing to buy. It takes into account many variables which effect our target audience and their decisions, such as “Season”, “Exchange rates” and “Current trends” to give an accurate prediction.
Retargeting
If you’re fond of purchasing e-commerce products online, you must have come across this marketing tactic. Clients get bombarded with numerous ads of those products they have on their wish list or those that they viewed recently.
The above approach allows marketers to display targeted ads to potential clients once they develop an interest in specific services or products. Obtaining extra information about the User, such as their e-mail helps improve re-targeting efforts by sending them emails for topics they may be interested.
AI in digital marketing plays a crucial role in creating successful retargeting tactics. The technology utilizes deep learning algorithms and machine learning to analyze clients’ purchase history and behavior. Machine learning helps marketers distinguish between actual conversion and prospects’ behavior to allow them to retarget customers.
Chatbots
Chatbots are voice-based or text-based AI-based interfaces that help simulate human intelligence by completing customer orders by interpreting clients’ queries. There are various forms that a chatbot can take, but the end result is the same. They are excellent tools for providing excellent customer service, solving problems quickly, generating leads, completing customer orders, and interpreting client queries.
Chatbots make use of Machine learning and Natural Language Processing (NLP) learning to evolve with over time as they gain more experience (by talking to Users and evaluating responses).
These flexible, intelligent, and extensive tools provide users with a lifelike experience of talking to an actual person. Chatbots are valuable for e-commerce ventures as they help them gather data efficiently, reducing barriers and staffing requirements.
Predictive Customer Service
Propensity modeling helps predict which clients are likely to unsubscribe from your products or services. These tools help marketers analyze more standard features in clients who unsubscribe more often.
It’s now easier to contact these clients to extend prompts, assistance and offers to retain them. AI enables you to provide customers with easy, convenient, and intelligent services anytime during the client’s journey. It’s crucial for the optimal and integrated client experience.
AI allows marketers to utilize technology to do those tasks that require human intelligence. The approach is crucial in e-commerce ventures as it helps businesses achieve specific goals, including developing personalized ads for clients based on their preferences.
Marketing Automation
Marketing automation approaches help automate repetitive marketing activities and tasks. It involves a set of rules that help initiate interactions that generate leads in the long run. Marketing automation measures success beforehand aside from generating new leads.
AI marketing plays a crucial role in marketing automation to facilitate the application of customer data and insights on a massive scale. AI helps in sorting, segmenting, and prioritizing client data, which increases the success of online enterprises.
App and Web Personalization
Apps and web personalization help optimize clients’ experience, allowing them to achieve their goals. AI helps marketers develop bespoke apps or website content and services which create meaningful customer engagement.
Tailoring the content and services of an app or website allows you to match with the target audience’s goals, which positions them in a better place to convert. AI helps power proactive marketing automation tools to help marketers mark their clients’ journeys by analyzing their behavior and interests.
This concludes our article on the Role of Artificial Intelligence in Modern Marketing. Any suggestions or contributions for CodersLegacy are more than welcome. Questions regarding the tutorial content can be asked in the comments section below.
