Welcome to the forefront of conversational AI as we explore the fascinating world of AI chatbots in our dedicated blog series. Discover the latest advancements, applications, and strategies that propel the evolution of chatbot technology. From enhancing customer interactions to streamlining business processes, these articles delve into the innovative ways artificial intelligence is shaping the landscape of automated conversational agents. Whether you’re a business owner, developer, or simply intrigued by the future of interactive technology, join us on this journey to unravel the transformative power and endless possibilities of AI chatbots.
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The goal of marketing teams at product and service enterprises is to deliver the right product to the right person at the right time.
Personalization tailors products and services to the specific needs of the individual users, and using the power of big data and machine learning algorithms, organizations can build detailed profiles of each individual and automatically customize offerings to those individuals.
It is through this combination of AI and content marketing that organizations have achieved an even more in-depth look at their potential customers and current users through hyperpersonalization.
Through hyperpersonalization, organizations can build a unique profile of individual users and customers and have that profile learn and adapt over time based on behavior.
Hyperpersonalization uses customer information to provide personalized content, products and services to match customers’ preferences. The data used includes profile data, user location, browsing history and purchasing decisions.
AI-based personalization aims to deliver optimal customer experiences in real time, targeted specifically to that individuals’ needs instead of grouping people together into broader categories.
Personalization is dependent on the ability to make offers that adjust to changing consumer behavior and preferences. It also must be able to respond to organizational requirements and other external influences.
AI personalization helps organizations increase engagement, improve customer loyalty, increase sales and better understand their customers. While some use cases are industry-specific, such as personalized healthcare and treatment, other use cases can be applied more broadly.
Additionally, some companies such as Starbucks and McDonalds are looking to personalize the user experience at the point of purchase. In 2019, McDonalds announced that it was working to personalize menu boards at drive-throughs for customers. With the power of machine learning, the digital menu boards at the drive-through can take into account factors that may influence diners’ ordering decisions and dynamically change the menu accordingly. For example, in colder weather the menu may push hot coffee or tea.
This idea is being further applied by Thread, a UK-based fashion company. The company uses AI to provide personalized clothing recommendations for each customer. Customers take style quizzes to give the company data on their style and the company can come back with personalized recommendations based on that specific customer’s likes and dislikes.
With the help of AI, companies are able to automatically customize the content on their website based on the user to provide a higher likelihood of conversion. For example, many websites now know where a user is located and may automatically translate the website into the common language of that location, correct time zone and local currency. Additionally, if they know I’m a first-time user on the site, they might provide more explanation of their product or service verses. If they know I’m a repeat visitor, they might provide images to products I’ve previously purchased.
One of the big challenges of using AI for hyperpersonalization is the cost and complexity of setting up AI-based personalization systems. The need for data, compute power and complicated systems can entail significant costs, given the complexity of engineering that goes into building these systems. Additionally, these smart systems require investment in data, tools and content. In order to streamline and scale personalization efforts, companies need to switch from a manual personalization strategy to one powered by AI.
Additionally, as companies begin to make messaging and offerings more personal, they need to watch out for user pushback against personalization features. This illustrates the “uncanny valley” of data. The uncanny valley is the concept that as robots appear more humanlike, they become more appealing, but only up to a certain point when the object becomes too human like that feeling of unease and uncanny feelings occur.
So, too, can this uncanny valley occur with data. When companies and marketers are applying hyperpersonalization to customers they need to constantly be monitoring customer sentiment to make sure they provide just enough information to be beneficial without providing too much information or personalization to start to become creepy or make the customer feel uneasy using their product or service.
The promises of hyperpersonalization are significant, and the lure of making products and services better and more targeted to their ideal customer base makes the allure of AI-based personalization an inevitability.
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