10 Examples of Artificial Intelligence in Marketing
Updated: Feb 4
Artificial Intelligence mimics how people think in order to provide tailored client experiences on the size and efficiency of a machine. It learns to execute activities as people do via experience, then utilises machine learning to better replicate and automate those processes. The data it gets determines what and how it learns. The more data Artificial Intelligence collects, the faster it can adjust to an audience's demands. It is available 24 hours a day, seven days a week, and is becoming increasingly capable of more sophisticated activities over time. These types of qualities are what make enable AI in Marketing to transform the business to next level.
1. Search engines
AI has been used by Google and Bing for many years. Google introduced RankBrain in 2015, which employs machine learning to give more relevant search results. Bing launched artificial Intelligent Search in 2017 to deliver more complete responses and pictures to user searches.
Semantic search and natural-language processing assist users in finding more relevant material on search engine results pages, even when their searches are misspelt or wide. For example, if a user searches "brown sandals," they may get a range of results, such as the top 10 brown sandals under $30, summer shoe trends, or strategies to save money on their next pair of espadrilles. This type of research may assist merchants in optimising their content and items for search so that new customers can find them.
2. Content Creation & Strategy
Artificial intelligence in marketing is crucial in determining content strategy. It assists marketing teams in selecting relevant subjects to boost search engine optimization and conduct competitive research.
AI in marketing also includes content generation. Natural language processing, or NLP, is an artificial intelligence (AI) technique that takes data and arranges it into a written tale that sounds like it was written by a person. (This method is also known as natural language generation.) NLP may be used to produce content ranging from articles and white papers to social media postings, depending on the programme. The Associated Press and The Washington Post are two well-known news organisations that employ NLP.
3. Email Personalization
Personalization of email marketing can be aided by artificial intelligence. AI delivers important analytics for marketers and makes use of previous subscriber behavioural data to produce more focused and relevant communications. Marketers may utilise natural language processing (NLP) technology in email to customise:
Subject lines, body content, and call-to-action buttons
Workflows for email automation
Drip marketing campaigns
The Indiana Pacers and Indiana Fever employ Marketing Cloud's Salesforce Einstein technologies to offer targeted information to its fans at the correct moment.
Chatbots employ natural language processing (NLP) to simulate human discussions via text. They simplify conversations, offer 24/7 coverage, and free up time for social media and community managers to focus on more complex discussions. Chatbots may assist marketers in the following ways:
Provide specific material to users.
Help with customer service
Create new leads
One boutique skincare vendor utilises SMS and Facebook Messenger chat technology to assist customers establish their skin type and make product recommendations – no human contact is necessary. Chatbots are appealing to people of all ages, not only the younger generation. Millennials and baby boomers both recognise the usefulness in them.
5. Dynamic Pricing
Dynamic pricing based on AI is becoming a science. Companies use data to evaluate demand and competition, and then use that information to impact pricing in real time. When the price of an Uber increases after a concert, for example, that's artificial intelligence-based dynamic pricing at action, or "surge pricing," as Uber refers to it.
This system can also utilise data using AI to predict how much a buyer is willing to spend for a product. With this knowledge, artificial intelligence may compare a retailer's price to that of its competitors to see where they stand. Have you ever found a fantastic price on Amazon? Their third-party merchants frequently utilise algorithmic pricing to compete with one another.
6. Image & Video Analytics
Image & video recognition enabled by AI recognises persons and objects in still pictures and videos. Image analysis provides marketers with another another option to interact with customers on social media, particularly influencers, and offer them discounts and welcome messages on the moment. Large firms that employ this sort of software include Amazon, Facebook, and Pinterest.
7. Speech Recognition and Virtual Assistants
Today, Siri, Google Assistant, and Alexa seem to be everywhere. Furthermore, technology is improving and becoming more human-like. Customers are becoming more at ease and acquainted with this kind of AI. Take a look at this video of Google Assistant making a restaurant reservation.
However, when it comes to voice-powered ecommerce, customers' top worries remain trust and privacy. In an online and in-person study of 1,000 Americans on voice assistants, half of those polled said they have used a voice assistant to make a purchase. However, they also highlighted concerns about privacy, safe payment, and stopping anybody — particularly children — from buying products without authority.
8. Augmented Reality
Augmented reality (AR) advertising is assisting shops in engaging with customers in a creative, nonintrusive manner. Warby Parker is an ecommerce startup that employs augmented reality. The eyewear store offers an app that allows customers to try on spectacles using a computer-generated overlay over their face. Lowe's uses augmented reality in their Measured by Lowe's app, which functions as a digital tape measure.
9. Programmatic Ad Targeting
Data and predictive analytics may assist merchants in creating marketing campaigns for specific audiences. AI can decide the optimum time of day to display an ad and even modify bidding methods for online adverts.
Retailers such as Lacoste are tailoring advertisements based on client data. During one programmatic ad campaign, Lacoste altered up their creative on a regular basis, resulting in 19,749,380 impressions and 2,290 sales across three countries. Data from programmatic programs may also be used to improve your sponsored search and content marketing strategy.
10. Recommendation Engines
From Amazon to Netflix, AI-powered suggestions are ubiquitous. Predictive algorithms can provide content and product recommendations based on a mix of prior user behaviour and personal preferences. AI may also help retailers save time by removing choice fatigue and the need to manually scan through product pages.
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