Machine learning (ML) and artificial intelligence (AI) are ingrained in the lives of most people in ways we can’t even imagine.
We see AI whenever we unlock our phones and browse social media. AI is at work at some of the simplest things like smart thermostats and smart fridges. We get some first-hand interaction with AI when we talk to Alexa, Siri, Cortana, or whoever your choice is for a digital voice assistant.
It shouldn’t come as a surprise that businesses and corporations are set to profit off of the latest AI and machine learning advancements. Almost every business industry right now can benefit from utilizing AI and machine learning in marketing analytics and sales.
But how does AI fit into the whole business narrative? How can it help businesses generate revenue? In what ways can machine learning improve business sales and marketing efforts? And finally, how do companies use AI and machine learning marketing?
Relevance of Machine Learning in Marketing Analytics
The main goal of market research is for a business to gain a better understanding of its target audience by interpreting big data. It allows companies to gain insight into customers’ needs and wants. It provides companies with baselines for marketing strategies. Analyzing big data and data sets makes it possible for businesses to stay relevant in a highly competitive marketplace.
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Market research and data science are big parts of service and product-centered businesses. Here we have a few benefits of integrating AI and machine learning in marketing analytics:
- Requires fewer tools – Analyzing data is hard work. As a marketer, you’d want to stay on top of the latest tools and technologies that provide you with valuable results. This is time-consuming and requires huge budgets though. By choosing AI software that works for your business, you can minimize the number of tools required to get optimal results.
- Requires less time – Without proper interpretation of complex data, big data remains just that – data. This is where analysts and data scientists come in. They manually turn data into something that marketers could use and profit from.
However, this interpretation can take time, so companies sometimes turn to automation and machine learning to aid in analytics and decision-making. An analyst often uses a test automation platform to perform big data testing and big data analysis. - Simplifies results – Research tools powered by text mining can help transform text data from databases, feeds, or documents into easy-to-understand structured data. AI uses natural language processing to mine text for analysis or to further drive machine learning.
AI Marketing and Big Data
AI has already proven that there is a bright future waiting for those who understand its importance in marketing analytics. It’s understandable for companies to want to jump at the chance to use AI and machine learning in digital marketing, too.
What Makes AI Marketing Powerful?
The many applications and growing AI capabilities make it a powerful business tool. Not only is it getting better and better in understanding human language, but it’s also getting better in understanding and responding to human emotions, too.
Growth hackers are always searching for ways to revolutionize the way people do business. There is amazing potential in AI technology, and there is nothing wrong with trying to make it work for your benefit.
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Just How Big Is the Machine Learning Market?
According to Forbes, they expect the machine learning market to grow more than 400% from 2020 to 2024. Here are other key facts and forecasts about machine learning in enterprises:
- One in ten companies now uses some form of AI-powered technology to deliver services and perform day-to-day business.
- The three most popular reasons why companies invest in AI are: reducing costs, gaining customer insight, and improving customer services.
- The machine learning market-making news isn’t exactly new. ML platforms and applications were the top categories for AI investments last Q1 2019. This amounted to more than 50% of all AI investments for the quarter.
- AI startups received a record-breaking total funding amount of $7.4B in Q2 2019.
7 Ways Machine Learning Improves Marketing and Sales
How exactly can marketers use AI and machine learning in marketing? Can any of these ways improve sales?
Remember that investing in machine learning applications and artificial intelligence tools isn’t a light decision to make, so measuring the ROI of AI initiatives is always a good idea. Anyhow, listed are 7 of the most common ways that AI and machine learning models for marketing are being used:
Personalizing Customer Services
A big number of service-providing entities choose to focus on personalizing customer services, and these are usually the businesses on the right path. Take, for example, Netflix.
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Netflix provides its customers with recommendations based on a wide variety of factors: previously watched movies, rated movies, ignored movies, search queries, and so much more. Netflix is also known to recommend personalized artworks catered to a viewer’s personal preferences, resulting in more views.
A Netflix series launched in 2019 called Love, Death + Robots even had four different episode orders that they say are based on the site’s understanding of your browsing behaviors and viewing habits.
Overhauling the Customer Service Experience
These days, the fastest way to get customer service is via chatbots. The rising popularity of chatbots can be attributed to zero waiting times, round-the-clock availability, and extensive knowledge databases.
With chatbots, you can get instant answers without having to talk to an actual human representative. You won’t have to call anyone on the phone or wait for an email reply. You can pick or type your replies, and chatbots will provide you with answers or direct you to helpful articles. Providing this option to your customers lessens the chances of them wanting to get routed to customer service representatives.
Crafting Compelling Promotional Content
Machine learning and digital marketing are a match made in heaven. In most business models, saving time equates to saving money, because this means that more can be accomplished with more time. This is true with content creation, too.
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Using machine learning marketing is a great way for content creators and copywriters to up their game.
- Automate keyword research
- Get better research materials to work with
- Make whole articles with just a topic input
- Craft shorts and product descriptions with natural language processing applications.
Machine learning tools like these can help speed up the content creation process. Though the final results will still mostly benefit from the scrutiny of a content editor, these tools can help produce interesting, engaging, and informative content.
Building Beautiful Websites
Website design is more than just good appearances. A good-looking website is nothing if the whole user experience is no good. Machine learning can help marketers make sense of visitor data to create websites that are stunning in both the UI and UX aspects.
WixADI (Wix Artificial Design Intelligence) is an example, and this is how it works.
- Step 1: You tell WixADI what kind of website you want to create.
- Step 2: You input some basic business information like business name, logo, and location.
- Step 3: WixADI searches the web for publicly available and business-related information, and crafts a website based on them.
- Step 4: You choose from a set of styles offered by the ADI.
- Step 5: You get the chance to make minor adjustments or start from scratch.
- Step 6: Push the site live or park your finished design.
Optimizing Marketing and Advertising Efforts
It’s difficult to undermine the many applications of machine learning in marketing and sales. They can be particularly helpful in marketing campaigns, predictive analytics, mix modeling, and even attribution. AI and machine learning consultants are even a thing now.
Automating and optimizing your marketing and advertising efforts can lead to higher revenues and better leads. It can help you build more accurate customer segments so you can personalize your strategies and make better customer interactions. You can even use ML tools to help in deciding how much to spend on advertising and figuring out the best timing and duration for the advertisement.
Managing Social Media Marketing
Social networking sites are known to use AI and ML tools to provide better user experiences. Some of the most widely-used examples are Twitter’s curated feeds; Instagram’s customized contents; and Facebook’s face recognition features.
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Not all comments were made equal. Some require carefully-crafted responses because they can make or break your brand. Companies use ML to determine complaints and reviews that take top priority as part of a process more commonly known as reputation management.
Perfect timing is as important as the content itself, because what good is great content when the reach isn’t as wide? Sometimes, all it takes is the perfect timing for posts and brands to go viral, and AI and ML tools can help determine this perfect timing and analyze the consumers’ sentiment.
Handling Machine Learning Email Marketing
Email marketing is an old practice, but it doesn’t mean it’s not as useful as the other ways of marketing in the digital era. There have been so many changes to the way people use, read, and send emails.
You can automate content, optimize subject lines, retarget customers, and many more with the help of AI. Other AI tools can help with the timing, segmentation, email delivery, and solutions for e-commerce, too.
Many e-retailers use customer retargeting. A few hours after browsing through several products and product recommendations, they’d send an email to customers to remind them about a product in their cart and offer the user vouchers and discounts to help seal the deal.
Companies That Use AI-Powered Marketing
There are countless companies and apps that use machine learning, but here are some of the most impressive ways of AI and ML we’ve found over the web.
Google – DeepMind
This project began in 2010 and was acquired by Google in 2014. They deal in multiple fields of interest in nature, space science, research, energy consumption, and many others. Most popularly, their AI is the first program to ever beat a professional player at the game Go. It has also learned how to play 49 different Atari games from studying the games by pixels.
Alibaba – FashionAI and City Brain
Alibaba is the largest e-commerce platform in China and the world. Its FashionAI store uses artificial intelligence to display clothing items in smart mirrors, and then goes on to suggest clothing items that go best with what the buyer has chosen to “try on”.
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They’re also involved with City Brain, a project that aims to monitor vehicles in the city and reduce traffic jams.
Amazon – Go
Amazon is primarily an e-commerce platform, but it uses AI in many aspects of the business too. It uses machine learning and marketing to learn a user’s buying and browsing habits. Predictive analytics even help them suggest things to buy even before you think about buying them. Amazon Go is a concept that allows people to shop at stores without having to checkout with an actual cashier. Cameras and AI technologies track the items that you pick up, and you’ll be charged with the corresponding total on the Amazon Go mobile app.
Nike – Nike By You
Nike By You is an interactive and in-store AI app that allows customers to customize their own Nike shoes and have them printed in under 90 minutes. It gave customers the chance to create highly personalized products, but it also helped Nike determine customers’ demands and style preferences.
Conclusion
Artificial intelligence and machine learning are everywhere. There is continuous learning, ever-expanding knowledge, and unending potential in this field of technology. It has transformed and it continues to transform businesses of all sizes.
And apart from its huge importance in interpreting big data in analytics, machine learning marketing can also help marketers offer or optimize the following:
- Personalized services
- Customer service experiences
- Content creation
- UI/UX websites
- Automated marketing and advertising
- Social media management
- Email handling
Companies and enterprises use AI and ML for both customer-facing apps and internal software systems. They’re not limited to more popular brands and enterprises. There is enough interest and funding for the AI, automation testing, and machine learning market, making more AI start-ups further want to develop and enhance AI technology and ML applications.
Author Bio:
Dan has been building teams and coaching others to foster innovation and solve real-time problems. Dan also enjoys photography and traveling.
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