AI is here and there’s no need to be shy about it. Instead, we, marketers, might as well just embrace it and see where it can lead us to.
Here in this article, we talk about the role of AI-powered tools in customer segmentation and how they can help personalize customer experiences.
Even AI-based technologies have been utilized by marketers for quite a while now, it’s the past two or three years that we’ve seen them becoming hugely widespread and easily accessible. Marketers these days use AI to segment customers and personalize their experience to a degree that hasn’t been possible before. They can follow you wherever you go online: from one website to another into your social media profile and out to the streaming services, and even offline sometimes.
It’s no secret that the biggest part of marketing ROI comes from segment-based and targeted campaigns. So, there goes your winning formula: the more precise your segmentation is, the better results you will achieve. And that’s where AI comes in.
AI algorithms can analyze vast amounts of data to identify patterns and create accurate customer segments – much better and faster than humans. As a result, you get to tailor your messaging and campaigns to specific groups of customers, increasing the chances of it resonating with them on a personal level.
Think about it – suddenly learning about a vacuum cleaner going on sale (when you don’t even need one) is one thing, but learning about the exact model of the vacuum cleaner you’ve been thinking about buying for the past day or two but thought it was a bit on the pricier side – that a whole other league.
But it can get even better than this – with personalized marketing. Personalized marketing takes it a step further by delivering highly targeted and relevant content to individual customers.
AI-powered recommendation engines can analyze customer behavior, purchase history, and preferences to provide personalized product recommendations or content suggestions. This level of personalization not only enhances the customer experience but also increases the likelihood of conversion and customer loyalty. When customers feel understood and valued, they are more likely to engage with a brand and become loyal advocates.
If we fast-forward from the ancient times (when marketing and, therefore, segmentation did not exist) to the second half of the 20th century, we will find ourselves in the times when TV started to slowly take over radio.
The post-war economy was booming around the world, and people were willing to spend more and more money on things they did not necessarily need for survival. Right around this time, media moguls and corporations realized they had enough data and means to segment their clients. Why? Because not all customers are the same.
One of the earliest criteria for customer segmentation was demographics (i.e., grouping customers based on factors such as age, gender, income, and education level).
This allowed companies to create marketing messages that were more relevant to specific demographics, rather than trying to appeal to everyone with a one-size-fits-all message.
Need an example? Soap operas! They got their name for a good reason – when marketers noticed that melodrama-filled TV series were mostly watched by housewives, they started to get aired in the daytime (back then it was customary for most married women to stay home and look after the house and children), placing various ads for cleaning products in between since these products were most likely to resonate with the audience. And resonate they did!
As the technology progressed, so did the precision, with which marketers tried to segment their audiences. Print ads, radio and TV commercials, billboards, telemarketing – that was just the beginning.
The real breakthrough came with the rise of the Internet in the early 2000s – that’s when we finally got to pretty much where we are today: search engines, keywords, PPC ads, banners, and so on.
Then, in the late 2000s, when we all got introduced to social media, segmentation reached its peak. People willingly gave away all the information about themselves (not just demographics, but their hobbies, interests, location, shopping preferences, etc.) so that marketers could use them to laser-target their ads.
Sources even refer to this as psychographic segmentation (as opposed to demographic) Now, in this day and age, we have the computing power and smart approach provided by AI algorithms, that can do the same job that humans used to do, but much faster and in real-time.
The personalized approach provided by AI-powered marketing is best exemplified in how services like YouTube, Amazon, and Netflix tailor their content and products to their users. For example, Amazon's recommendation engine uses AI algorithms to analyze customer browsing and purchase history, providing personalized product recommendations that drive sales.
Netflix uses AI to analyze user behavior and preferences, delivering personalized movie and TV show recommendations that keep users engaged and subscribed. These companies have seen significant improvements in customer satisfaction, engagement, and revenue by leveraging the power of AI for personalized marketing.
One of the primary AI-powered tools for enhancing customer experiences are chatbots and assistants. They pack a lot of useful features, some of which include:
Chatbots and virtual assistants can gather user data and preferences to provide tailored experiences. By analyzing user interactions, they can understand individual needs and preferences, allowing them to offer personalized recommendations, suggestions, and solutions.
Chatbots and virtual assistants are available round the clock, providing users with instant support and assistance. This availability ensures that users can access personalized interactions at any time, without the need to wait for human assistance.
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These AI systems continuously learn from user interactions, improving their ability to provide personalized interactions over time. By analyzing user feedback and behavior, they can adapt their responses and recommendations, enhancing the overall user experience.
Chatbots and virtual assistants can be integrated across various platforms and channels, including websites, messaging apps, social media, and voice assistants. This allows users to interact with them through their preferred channels, further personalizing the interaction.
Through user interactions, chatbots and virtual assistants generate valuable data that can be analyzed to gain insights into user preferences, behavior patterns, and pain points. This data can then be used to further personalize interactions and improve overall user experiences
Naturally, you can (and should) use AI to increase conversion rate on your website – here are a few clever ways you can do it.
AI-powered tools analyze customer data, including browsing behavior, purchase history, and demographics, to create personalized experiences. This data can be used to deliver targeted content, recommendations, and offers, increasing the likelihood of conversion.
AI algorithms can analyze historical data to predict future customer behavior and identify potential leads. By understanding which customers are most likely to convert, you can focus your marketing efforts on those individuals, optimizing their conversion rates.
AI-powered marketing tools are capable of continuously monitoring and analyzing customer interactions in real-time. By tracking metrics such as click-through rates, bounce rates, and engagement levels, these tools can identify areas for improvement and make instant adjustments to marketing campaigns.
AI algorithms can analyze market trends, competitor pricing, and customer behavior to optimize pricing and offers. By dynamically adjusting prices and promotions based on demand and customer preferences, you can maximize conversions and revenue.
You set an AI algorithm to run A/B tests on various marketing elements, such as email subject lines, ad copies, and landing page designs.
Even though AI in marketing is relatively harmless, it still needs regulation – mainly, when it comes to data privacy and algorithm biases. The latter is particularly important since AI algorithms are trained on historical data, which can perpetuate biases and discrimination present in the data.
Therefore, organizations deploying AI systems must ensure that they regularly audit and monitor their models for bias and actively mitigate any discriminatory impact.
No one can accurately predict the future of AI in marketing. The technology is developing so rapidly that it evolves almost every month – particularly, through machine learning algorithms and blockchain. However, we can make some assumptions based on the current digital marketing trends.
AI algorithms can analyze social media and customer feedback to understand customer sentiment towards a brand, product, or campaign. Marketers can leverage this data to enhance their reputation management, improve customer service, and respond to customer feedback more effectively.
AI can enhance AR and VR experiences by enabling more immersive and intelligent interactions. Marketers can utilize AI-powered technologies to create unique and engaging AR/VR experiences, allowing customers to visualize products before purchasing.
AI algorithms can curate and recommend content to customers based on their preferences and interests. Marketers can leverage AI to deliver personalized content recommendations, improving customer engagement and loyalty.
AI-based technologies have already revolutionized online marketing as we know it, and they will most likely continue doing so. We strongly encourage you to embrace AI and use it in your marketing strategies to the greatest extent. Cause your competitors are probably already doing it.