NOV 25 2021 | 14:25 PM | 4 Mins Read
What Is Artificial Intelligence Marketing?
Artificial intelligence marketing (AI Marketing) is a method of leveraging customer data and AI concepts like machine learning to anticipate your customer’s next move and improve the customer journey.
Advancements in Artificial Intelligence offer companies better ways to do that. AI can help build more effective marketing strategies, improve the customer journey, and change the way businesses attract, nurture, and convert prospects. The graphic below shows how AI and machine learning can be incorporated into every step in the customer’s life-cycle.
Examples of AI in Marketing
AI in marketing may feel more science fiction than fact to many, but it’s not a far-off concept; it’s here right now. According to Sales force, just 29% of marketing leaders used AI in 2018, but that number surged to 84% by 2020. And by the end of 2021, global spending on artificial intelligence hardware, software, and services is expected to exceed $340 billion, per a forecast from IDC.
If you haven’t considered the power of AI for marketing, now’s the time to learn more. To help you get started, we’ve compiled ten impressive artificial intelligence marketing.
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Apply a planned approach to your IT/high tech company’s marketing to rapidly review, find opportunities, build a high-performing team and develop your marketing strategy to reach, acquire and engage more customers.
Marketing using augmented and virtual reality allows brands to craft experiences, engage consumers and encourage conversions in interesting ways.
- More than ever, marketing is being driven by the wants and needs of the customer. As new technology becomes available, customers want brands to deliver experiences that use it.
- This means it is important that marketers keep pace with new advances in order to meet customer expectations and deliver the best possible experiences.
- When you consider the fact that these technologies are already disrupting sectors, failing to utilize them could leave you lagging behind your competition
All companies that operate have options to apply publicly-available algorithms to their site or make use of off-the-shelf machine learning services.
This means that it is easier than ever to gather useful insights and create prediction models based on the behaviour of their customers.
Machine Learning for marketing
- When looking realistically at how AI can be applied by the majority of businesses to aid marketing, it’s easy to see that the focus should be on Machine Learning.
- Machine Learning involves the analysis of historical data from various business interactions with audiences, as well as the audience responses.
- This data will allow for the identification of the success factors of your communications, including targeting, offers, copy and frequency.
- You can then use this learning in future campaigns in order to increase the chances of success.
Predictive analysis insights for marketing
- Algorithms for Machine Learning generate insights via predictive analytics, it is then up to teams and individuals to action these insights or to define rules that allow your AI to act on them.
- For example, you can define a rule that establishes when to send emails aimed at re-targeting your audience, giving you a better chance of a higher ROI.
- Utilizing predictive analytics has been found to give consistently better results across a number of important metrics.
- For businesses using predictive analytics, both the average profit margin per customer and customer lifetime value is twice as high.
Applying Machine Learning and AI across the customer life-cycle
- There are many opportunities to deploy AI and Machine Learning throughout marketing. Our visual shows the wide array of applications for Machine Learning and AI for marketing, all of which can be put in place today.
- None of the technology is speculative or on the horizon, these are current marketing techniques already being utilized by many successful companies.
Since artificial intelligence is a complicated and rapidly evolving technology, it’s sometimes difficult to envision the practical applications it may have in the future.
In the past few years, successful brands have been using artificial intelligence to increase profits, brand reputations, and visibility.
Some of the Global Brands that are successfully leveraging AI for Marketing
Amazon pioneered personalized shopping recommendations, and over time its algorithms have become increasingly advanced. Suggestions are now based on previous purchases and the products you’ve recently purchased. As well as past purchases, other items other customers bought, search and browsing behavior, and many other factors are taken into account
Artificial intelligence is used by Amazon to drive dynamic pricing – reducing prices when sales are low and increasing prices when demand is high. This algorithm enables optimal sales and revenue to be generated.
Amazon has now opened checkout-free physical stores in Seattle, Chicago, and San Francisco, which are equipped with AI-powered sensors and cameras.Using the Amazon Go app, this technology can identify which items a customer has picked up and will automatically charge them as they walk out of the store.
With Echo Look, the company aims to join the trend of AI in the fashion industry with machine-learning algorithms that suggest outfits based on individual preferences, driving more sales of apparel, shoes, and accessories.
Starbucks presented a strategic plan in 2016 for using AI and big data, and the company has since improved its reward program and personalized customer experience to develop a more meaningful relationship with its customers.
Customizing drinks to suit your tastes has always been a key part of the Starbucks customer experience.App for collecting and analyzing customer data, including purchases, where they are made, and at what time.
Using predictive analytics, the company delivers personalized marketing messages to customers including recommendations when they approach their local stores, and offers aimed at increasing their average spend. The AI-powered app also allows customers to place orders directly from their phones via voice commands via a virtual barista.
Starbucks uses its data from 90 million transactions each week to determine where to open new stores and which products to offer as well as to provide a more personalized customer experience.
Alibaba Group, a retail and technology multinational, opened its first “Fashion AI” store earlier this year. Smart garment tags that detect when an item is touched, smart mirrors that display clothing information and suggest matching items, and plans for integration with a virtual wardrobe app that will let customers see the outfits they tried on in-store will help streamline the fashion retail experience for customers.
This is not the company’s first venture into artificial intelligence. Alibaba launched its smart customer service system in 2015, which automated customer service so well that it achieved a higher satisfaction rating than human agents.
Similar to Amazon, Alibaba offers personalized recommendations and search results, as well as automatically generated storefronts that display the most appealing items to individual customers.
Every day, 567 million people use its website and apps, and millions of people visit the company’s website. Having so much data on customer habits is ideal fodder for AI processing, and the company is sure to come up with more ideas to utilize in the future.
In 2006 Nike+, one of the world’s first fitness tracking gadgets was introduced by the mega sports company. They are also known for their innovation in marketing; now, they are combining the two to improve their product offerings and deliver personalized experiences to their customers.
Customers were able to design their own sneakers in-store last year thanks to Nike’s new design system. The gimmick is not only great for driving sales, but it also collects a lot of useful data that machine learning algorithms can use for designing future products and delivering personalized marketing messages and recommendations.
The company has Recently acquired body scanning from Inverter a move that Nike Chief Digital Officer Adam Sussman said would: “deepen our bench of digital talent and further our capabilities in computer vision and artificial intelligence as we create the most compelling Nike consumer experience at every touch-point.”
It’s clear that Nike has big plans from the data it collects and is certainly one to learn from in terms of the applications of AI both now and in the future.
Several different companies are already using AI to power self-driving cars, but BMW is truly embracing the technology and using it at the heart of its manufacturing processes and overall marketing plan.
BMW uses Big Data to power its design and engineering processes, sales, and customer support. Predictive analytics are used to create the car designs of tomorrow, and the company has already built an AI-enhanced sports car that learns about its driver to automatically adjust systems and the cabin experience to suit each individual.
Earlier this year, BMW launched an intelligent personal assistant that enables drivers to communicate with their cars in the same way that they do with their smartphones. The tool also acts as a voice-activated manual, predicts travel routes, delivers alerts, and integrates with other apps. In the future, this technology could be used for marketing for third-party businesses such as parking lots and gas stations, and there’s no doubt the data collected from each individual driver will be put to further use in the company’s marketing intelligence.