Boost the Growth in 2022

Artificial Intelligence in Marketing
Illustration: © IoT For All

Industry leaders around the world are using artificial intelligence to enhance their business with marketing technology. Whether it’s analyzing consumer interests and data, guiding sales decisions and social media campaigns or other applications, artificial intelligence is changing the way we understand marketing in many industries. Let’s talk about the latest ways that businesses can utilize these powerful tools to achieve their marketing goals.

Core Concepts of AI in Marketing

Technology changes every day. A lot can change over several years, especially in trending artificial intelligence technologies. The same goes for AI in marketing applications. Understanding the basic ideas behind applications of AI in marketing solutions can generate unique ideas that can break new ground in various industries.

AI can help automate projects to make businesses more efficient. According to Accenture, the productivity of businesses can be improved by 40 percent when utilizing AI. This not only can save time and money but can enable your company to focus their efforts on providing quality experiences for customers rather than spending too much time moving things from one spreadsheet to another.

AI can also help minimize errors in marketing processes. Artificial intelligence can complete specialized tasks with greater efficiency than humans can so long as supervision and guidance are involved. Often in cases where AI fails to provide the right results, human error was involved in setting up the AI ​​program with appropriate data or it was used in a way that was not intended.

Because AI can campaign speed up the process of marketings, reduce costs, and improve efficiency, artificial intelligence is much more likely to result in an increased return on investment (ROI).

Conducting Market Research with Artificial Intelligence

Artificial intelligence is a strong tool when used alongside high-quality data. Many companies have had positive results in the real world when combining their market research data with artificial intelligence. This enables them to do all sorts of things. A big part of this trending use case is target group segmentation. AI is far quicker and more efficient at performing this task than humans are.

By investigating their target audiences more deeply, businesses can make more personalized offers to them that they are more likely to accept.

When we examine how this looks up close, we can get a better understanding of how it works. A nationwide department store can take a look at the data they’ve collected on their customers and narrow down their search to those interested in food. Using artificial intelligence, we can identify customers that have a strong preference for organic foods. By quickly using AI to analyze the habits and preferences of these consumers, campaigns can be tailored toward them with greater efficiency to improve sales.

AI in Predictive Marketing Analytics and Personalization

Target group segmentation is one of the keystone elements of personalizing a marketing campaign, but there are many other ways that artificial intelligence can help businesses personalize experiences for their audiences and customers. According to Salesforce, 76 percent of customers want businesses to have a clear understanding of their personal expectations.

One way that businesses do this with AI is to use predictive marketing analytics. By having AI analyze data of past events, it can reasonably and accurately infer how performance will look in the future based on a variety of factors. More importantly, analyzing what users like most can be useful when looking to suggest products to them.

For example, Amazon is the champion of this strategy. When browsing on their site, Amazon’s artificial intelligence knows about what you have bought in the past. Based on this, it can suggest products to you in your feed. It also knows what other users like you are interested in, meaning that they can provide suggestions based on that activity. This results in very personalized suggestions that can lead to higher conversions.

Spotify also takes advantage of this to make more effective music suggestions for you. It also uses this data to invest in artists to create new music that will be generally liked by a wider audience on a broader scale.

However, most personalization methods with AI tend to start from the top-down and personalize to the individual instead of an entire group. The more that the system can understand the individual user, the more likely that conversions can be made. Every user has variations that differentiate them from the larger group, so no group marketing campaign will ever be as effective as a campaign that targets specific individuals and their own interests.

The ability to use artificial intelligence to predict the success of marketing campaigns and to better personalize experiences for users is a powerful technological trend that will continue for years to come. Adaptation to include this tool in your arsenal is critical for relevancy at scale.

Dynamic Pricing & Demand Forecasting

One of the most difficult challenges of the onset of the 2020 COVID-19 pandemic was a surge in sales of various products by stockpilers. Shortages of toilet paper became a notorious meme on the Internet as stores struggled to maintain stock in the face of the buying panic. Eventually, stock would be controlled by buying limitations. However, there was an important lesson to be learned here: demand forecasting and dynamic pricing could have prevented a great deal of this struggle.

Earlier we established that artificial intelligence is a powerful tool for analyzing past data in order to predict future activity. The same principle can be applied here. It’s possible that AI can be used to analyze consumer interests, world events, and other sources to determine if there will be a rise in demand for certain products.

Using the pandemic as an example, BlueDot is a program that already can analyze the likelihood of a disease spreading across the world. If worldwide or nationwide emergencies can be predicted in this manner, stores can automatically begin ordering more products like toilet paper, medicine, and more. Not only can this help maintain stock and improve sales for stores, but it can also help the public better manage the disaster and lead to a swifter recovery.

This can also be used to dynamically and automatically raise prices. This can be used to better control stock during times of high demand and panic buying, naturally dissuading customers from bulk buying beyond reasonable amounts, as well as optimizing revenue for your business.

Dynamic pricing and demand forecasting for every business is unique. From the types of items that you carry to the types of consumers that you are serving, a custom solution made by your team or by an external vendor may be the best option for creating a system that can accomplish your goals.

AI in Content Creation

Providing unique and engaging content can be challenging. While AI can automatically generate content, it often can be more trouble than it’s worth.

Although this technology is improving and can be very effective in some contexts, a more widely accessible and reliable possibility is for AI to offer intelligent suggestions to human writers. AI-guided suggestions for writers form the basis of features in applications like Grammarly, Microsoft Editor, Google Docs, Microsoft Word, Yoast, SEMRush, and more.

Adobe Premiere Pro uses AI for a variety of purposes, such as automatically matching colors and managing sound mixing against voiceovers. What’s great about content creation is that humans can create unique and interesting content that AI cannot, but AI can help us augment our talents to improve the quality of the final product.

AI can also help us with image generation and manipulation tasks:

  • Creating copyright-free images of non-existent people, animals, and objects
  • Turning photos into sketches and painting of various styles
  • Inpainting and restoring parts of images
  • Upscaling images
  • Face frontal view and new human poses generation

All this can be done with the help of generative adversarial networks (GANs) that learn the structure of the complex real-world data examples and generate similar synthetic examples.

Does it mean that robots can replace designers? Absolutely not. The power of AI in design is mostly about optimization and speed. Designers armed with AI tools can work faster and more effectively.

Language Optimization for Email Marketing

One particular avenue of AI in content creation comes from its role in marketing campaigns via email. eBay is a particularly good example of AI email marketing, utilizing a third-party service called Phrasee and natural language processing to improve email open rates by 15.8 percent and improve clicks by 31.2 percent.

This technology is used to optimize the subject text and headline copy automatically to find the most effective variation to use with eBay’s audience. The AI-generated portions of the emails are attentive to the tone of voice to maximize their success.

Aside from the fact that natural language processing is improving as years go by, AI-based email marketing at its most basic can be automated with a series of A/B testing. However, the more demographic data and natural language processing that can be incorporated into the project, the better the results. Advanced artificial intelligence algorithms can improve the dynamic optimization of email marketing greatly, as seen in eBay’s case.

Future of AI in Marketing

Ultimately, the future of AI’s role in marketing technologies will be determined by imagination and innovation. Combining different technologies together can result in businesses outcompeting other leading players in the market for years. At the bare minimum, understanding what’s already in use is important for bringing your company up to speed to remain relevant and competitive in the market.

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