Best Examples of AI in Marketing

Best Examples of AI in Marketing

We live in an era where a marketer who does not use artificial intelligence in their marketing plans is already a step behind. Artificial intelligence allows you to execute marketing plans and also create them. Digital Marketers are familiar with artificial intelligence, neural networks, deep learning, big data, and automation. Marketing as we know it now is the result of this terminology and practices. 

AI is still relatively new, and there is a tendency to conceive of it in the future. AI will accomplish this and achieve that in 10 years. These forecasts may be correct, but you don't have to go far into the future to see AI in action. AI is already demonstrating its utility in the corporate sphere, assisting marketing teams in working more innovatively and more efficiently. Here are a few instances of artificial intelligence in marketing. 

 Ads

Several tasks are still performed better by people than by machines. Machines have the upper hand when it comes to monotonous and repetitive jobs. Machine learning is especially adept at spotting minor changes between items and optimising them for better results. It's suitable for advertisements. Machine learning demonstrates to disclose which advertisements perform best and where they place.

Retargeting 

Although remarketing is becoming more intelligent, it is still a process that relies on humans to curate and create Ads. Computers are incredibly effective at predicting what kind of information would appeal to a person based on what they've previously eaten. Retargeting powered by AI is more personal and practical. 

Analytical forecasting 

Predictive analysis, the younger brother of propensity modelling, uses statistical methods, consumer data, and machine learning to forecast various events. It's a more prominent tool that can be used with your existing data to estimate market trends, consumer behaviour, and company results. 

Modelling by propensity

The goal of propensity modelling is to predict future behaviour based on previous behaviour. It's the type of data-intensive procedure that machine learning excels at. When you feed in data about your customers or prospects, propensity modelling may tell you which companies and people are most likely to buy a given product. This type of data is beneficial from a marketing standpoint. 

Chatbots 

Users vary in feelings about Chatbots, but the same can be said about robotic customer care lines. Whether you like them or not, Chatbots are here to stay. They could be used as a stand-alone tool or as a lead-in to a live chat service on your website. It can start visitors chatting before smoothly transferring from machine to human operator for interacting with B2B prospects.

Marketing Automation

Most marketing auto, specifically email automation, is still done by hand, with humans segmenting lists and making decisions based on the data. Thanks to new technologies, machines may now categorise and execute email sequences depending on user behavior. This is a far more efficient method of working. It'll only be a matter of time until it becomes the standard. People create the material and algorithms selecting when, to whom, and in what sequence it delivers. 

Curation of content

We frequently associate content curation with Netflix and Spotify, whose algorithms manage our lives silently. Content curation is a task best left to robots whenever it comes to business. They have the time and patience to comprehend user behaviour and then forecast what other material they'll like. A simple example of content curation in action would be recommending articles for visitors to read next on your site. This technology might suggest relevant items during checkout or the checkout process, or in transactional emails.

Customer service that anticipates your needs 

Consider anticipating when your consumers will contact you and what their questions will be. Consider the possibilities for improving customer service, upselling, and cross-selling if you had access to that information. We are not reaching that point yet, but we're close. Intel's saffron subsidiary develops an artificial intelligence system that blends natural intelligence with machine learning.

Conclusion

The maximum says that nobody knows you're a dog on the internet. Soon, no one will be able to tell you're a dog reading an essay authored by a computer, followed by information curated by a machine. Artificial intelligence is all over the place. It's time to get down to business. 


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