Marketers are increasingly relying on technology to simplify some time-consuming aspects of their job. The marketing industry today is abuzz with various high-tech prospects that are up-and-coming. The most significant of these are artificial intelligence (AI) and machine learning (ML).
About 34\% of sales and marketing leaders believe that AI will be the most important technology for improving customer experience.
So, in this article, we’ll discuss the top 7 use cases of AI in martech. But before moving on to that, we’ll first understand the basics of martech.
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What is MarTech?
As evident from the name itself, MarTech is the blending of ‘marketing’ and ‘technology’. It is a general term to refer to the technology used for assisting the marketing team in their work.
Martech describes a range of software and tools that facilitate achieving marketing goals and objectives. It applies to major tools, efforts, and initiatives that utilize technology to achieve marketing objectives and goals. Martech is a staple in the sphere of digital marketing and is also used for optimizing offline marketing channels.
As per Statista, the number of MarTech solutions has grown from 150 to over 8000 during the last decade.
Martech is important since it facilitates greater growth in the organization. It makes organizations more efficient and effective. It also helps provide actionable insights into the ROI of an organization’s marketing efforts.
Additionally, martech helps teams become more effective in customer acquisition and retention.
Top 7 Use Cases Of AI in MarTech
Let’s talk about the top 7 use cases of AI in martech.
1. Filter data
Data is playing an important role in improving customer experiences. Marketing is now relying on more data than ever. But since analyzing a large amount of data can be a difficult task for humans, it needs AI to make sense of it.
AI is helping marketing teams carry out complex tasks and analyses. AI can filter the target audience so that the marketing teams can focus their attention on a certain customer segment.
AI makes it easier to bring together disparate data, automate data models, and shrink optimization cycles by automating insights. Marketers can use AI to significantly enhance data processing speed.
2. Personalize product recommendations
With more than 1.83 billion websites striving for users’ attention, superior customer experience has become a powerful differentiator in the overcrowded digital landscape. That is a big reason why personalization is becoming a defining factor to get attention from customers.
Marketers understand that today’s customers value user experience a lot. As per a report, 57\% of customers are willing to share their information in exchange for personalized offers. Consumers react to brands that cater to their preferences and deliver accordingly.
AI can help marketers achieve this personalization. It can be used to shape up the customers’ product recommendation strategy.
Marketers can use AI and ML algorithms to help transform customer engagement data to provide suitable product recommendations. It also helps marketers stay updated on the personal preferences of consumers and auto-populate the right recommendations on a real-time basis.
3. Optimize automated email delivery
AI can help marketers optimize the send time for emails. It can draw upon a smart analysis pattern by considering various factors like email opening history, frequency, and opening time, etc.
Accordingly, AI and ML can help marketers determine the best possible time for sending emails to their audience. For marketers, it only makes sense to know when a customer preferably reads emails.
This is also the time when a customer is more likely to engage with marketing emails and in turn, boost conversion rates.
4. Predict the performance of marketing campaigns
Martech has led to the popularity of predictive analytics – the process of using data, statistical algorithms, and ML to identify the likelihood of future outcomes based on analyzing historical data. The goal is to offer a best guess on what will happen in the future based on previous experiences.
Marketers can use predictive analytics to create stronger campaigns that resonate more with customers. They can also use it to identify leads that might proceed to the next stage of the sales funnel.
5. Provide dynamic pricing
Dynamic pricing means updating your prices based on changing market demands. Marketers can use AI to offer customers dynamic pricing after analyzing their data and behavior. It helps them target customers better to offer them discounted prices based on customer expectations.
Businesses have seen an increase in revenue through dynamic pricing.
6. Improve customer service
Using AI-powered chatbots, marketers can enhance their customer service efforts. There are several AI chatbot tools that can be easily added to your website or product page, allowing customers to get access to instant information.
Chatbots can be used to make customers aware of the latest offers, product details, upcoming webinars, or even blog post updates.
7. Manage social media
Managing social media is probably one of the most useful ways of utilizing AI in marketing efforts. Marketers can easily use AI to automate their content distribution and promotion efforts at scale. This frees up valuable resources.
Moreover, marketers can use various social media management tools to schedule posts, manage comments, create content strategies, and even respond to messages. It is also easy to manage multiple accounts using AI-powered tools.
Conclusion
So, these were a few top use cases of AI in martech. The field of martech is constantly evolving and AI is playing a big role in this rapid evolution.
If used wisely, AI can help transform the marketing industry. It has only increased profitability for businesses and will continue to do so in the coming years as well.
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