10 Brilliant Examples of AI in Marketing
We live in an era where if a marketer isn’t using artificial intelligence in his marketing strategies, he’s already lagged behind. Artificial intelligence not only helps marketers in executing their marketing strategies but are also used to form one. Artificial intelligence, neural networks, deep learning, big data, automation etc. are not new terms to marketers. These terms and practices give rise to marketing as we know it today. You’ll agree with us after reading the following examples of AI in marketing.
What if we tell you that the last customer executive you’ve had a chat with was a bot, or the unique newsfeed that you get on Facebook is because a bot is monitoring your every activity? Artificial intelligence is a very important tool for marketers as it removes the occurrence of human errors like delay, biased approach, and other petty errors. According to Facebook’s artificial research scientists, artificial intelligence systems are going to be an extension to our brains the same way cars are extensions to our legs.
Don’t you just love how Siri/Google assistant/ Cortana/ Alexa answers all of your questions? Don’t you just love when you receive instant replies on some websites’ chat-boxes no matter what the time is? Marketers know you love them and this is the reason why they are there.
A chatbot is a service, powered by rules and sometimes artificial intelligence, that you interact with via a chat interface – Chatbotsmagazine.com
It’s one of the best examples of automation and artificial intelligence in marketing. Two main types of chatbots exist today –
- Chatbots designed to serve one or more purposes to the customers. For example, a chatbot operating in a chat screen of a website, or a bot operating in any social networking website’s chatbox. National Geographic lets you chat with Albert Einstein on Facebook messenger to raise awareness of the launch of its new original series Genius that dissects the psyche of the physicist Albert Einstein.
- Assistants like Apple’s Siri, Google Assistant, Amazon’s Alexa, and Microsoft’s Cortana. These AI-powered chatbots are made to converse with users and help them by providing a variety of information and fulfilling their other information wants. Amazon’s echo look even rates your look based on machine learning algorithms with advice from fashion specialists.
Recommendations / Content curation
Recommendation is one of the best examples of AI in marketing. E-commerce websites, blogs, and many social networking and media websites use artificial intelligence to analyse your activities on the internet and recommend you products and content for better conversions and to make you spend more time at their websites.
Marketers look for ways to engage with you. They want you to spend maximum time on their website/application and to fulfil the same they use AI to act as an intelligent salesman and give you recommendations based on your activities, interests, and opinions.
Has it ever happened to you that when you are looking for a product to buy on the internet, you seldom get discounts or less price for that product? It’s because the bots on these websites know when you actually need a product. Your cookies, searches, and other activities are monitored to provide you with personalized pricing in response to your customer profile which that e-commerce website is generating in real-time.
Dynamic pricing (often referred to as personalized pricing) is a pricing strategy where the price is determined depending upon the demand, the availability and the profile of the customer. AI technologies are even used to decide and design personalized offers based on customer profiles.
Your activities, interests, and device are taken into consideration before serving you an advertisement. Marketers want to make the most out of advertisements by making them relevant for you. Advertisements relating to a product you recently searched about or from a website you recently visited are common on the internet.
The computers now have a vision just like we do. Computer vision helps bots gaining high-level understanding from digital images or videos. It utilizes pattern recognition and machine learning technology to gain the accuracy of the human visual system. Visual recognition is used by Facebook, Google, Snapchat and other applications to provide a better experience to you. It’s possible to search all the cat photos on your phone by just typing cats in the search section of the Google photos application.
Facebook and Google photos recognize a person face with the help of computer vision. Many new applications use this technology to create image filters and other engaging features.
Bots now recognize your voice and understand everything you say. Siri, Google Assistant, Alexa and most of the other chatbots now comes with speech recognition technology. Speech recognition is also used in applications like Shazam, google search, GPS maps, and other hands-free systems.
Including speech recognition in the operating model of your product/application is a great idea as users now look for hands-free features for more convenience.
One of the most useful examples of AI in marketing is data analysis. These days you don’t have to guess what will work for what audience. There are thousands of data points attached to the target audience that can be accurately analysed by bots to understand which message is going to appeal to whom.
AI closes the gap by moving far past human limitations to consume and analyze data on a scale no human can. The “intelligence” in artificial intelligence is the ability to think independently, to grow more knowledgeable from being exposed to more information and to adapt and adjust when things change.
AI technologies can be used to analyze data at a speed and accuracy better than any human. There are systems to analyze and forecast market fluctuations. These can also be programmed to respond to changes on the spot depending upon the conditions.
Many tools, like wordsmith, are used by marketers to convert data into sensible text. This auto content generation technology involves artificial intelligence and saves their lot of time. The best part about this AI-generated content is that readers are not able to discern automated content from content written by a human.
The bots are so good at authoring content that according to Gartner “By 2018, 20% of all business content will be authored by machines.”
Ever wondered how Google knows everything you want to search? How can it convert your wrong spellings, grammar, and spoken words into correct queries and come out with exact results what you were looking for?
Google uses Rankbrain, a machine learning technology, to analyze your search queries (both spoken and written) and to process them into search results that are most likely to be what you’re looking for.
“If you’re searching for an ambiguous query, or you’re using colloquial terms or talking to Google like it was a person, traditionally, computers will break down, because they can’t understand your query or they haven’t seen that phrase before. RankBrain can generalize it: ‘That phrase seems like something I’ve seen in the past, so I’m going to assume that you meant this.’ It’s much like a person hearing you talking to them in a crowded bar – they can’t hear everything you’re saying, but they still can guess what you’re meaning and have a conversation with you.” – Greg Corrado
There are many factors and forces that influence the present and future of a business in the market. They are complex, highly correlated, and sometimes difficult to measure. One of the challenges marketers face is how to predict the exact future of the business or a product using a complex set of inputs under tight time constraints. Many machine learning processes have been designed to automatically learn patterns in the numerous data inputs and help marketers to predict the future of anything they want to.
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