The future of AI in building digital experiences online

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Business Experience

Artificial intelligence (AI) is one of the most talked about topics in technology these days. Many developers are using AI to build applications that can act like intelligent agents and help you accomplish tasks more efficiently. However, if you’re a marketer or customer service representative, chances are that you don’t have much knowledge about AI. So what exactly is artificial intelligence? What can it do for your business? And how will it affect digital experiences? If you want answers to these questions, read on!


Digital experience platforms

Digital experience platforms (DXPs) are the future of online. They will help with personalization, customer experience, marketing and data.

DXPs will help you understand your customers better so you can create better interactions with them. You'll be able to see what they do on your website or app and how they interact with it so that you can personalize the experience based on their preferences.


Use of AI in business applications

AI is becoming an increasingly important part of business applications. AI is being used for tasks like customer service, marketing, and sales. AI can help businesses understand their customers and employees better by providing insights into data. AI can also help companies improve their products through machine learning.


AI is going to be a key part of DXPs

AI can deliver personalized experiences, content personalization, and customer service, as well as help with marketing, analytics, and automating processes. In addition, it brings many benefits with regards to security, risk management, and compliance. 

AI can help the DXP to make better decisions, predict what will happen next, or find solutions to problems it encounters. It can also automate processes and tasks that would otherwise be done by humans.


Personalization is key for DXPs

AI is going to be essential for personalization in DXPs, and it's something we're already seeing today. Personalization can be based on user behavior, on a user profile (such as location), or on the preferences of the user.

Let's look at an example of what this might look like in practice: you're browsing your favorite retail website looking for a new pair of shoes, but all you see are sneakers. You decide you want a pair that has more support for running but still looks good with your favorite jeans—so you enter "running sneakers" into the search bar and get back results that match your query but also include some additional information about prices and availability in nearby stores etc. 

This type of personalization can help make websites more useful by serving up relevant information without forcing visitors through hoops such as clicking through links within each page before finding what they need—which may be especially important if people aren't familiar with how websites work yet (e.g., someone visiting their first site ever).


AI is making it easier to understand audience behavior

AI can help marketers understand what content is popular and why, which allows them to be more strategic in their marketing efforts. For example, if a piece of content is really well received by your audience then you should consider creating more pieces like that. On the other hand, if a piece of content isn't as well received by your audience then you don't want to create more like it.

AI also provides an opportunity for marketers to understand why certain strategies work or don't work. This means they can learn from previous mistakes and improve upon current approaches in order to make sure they're reaching the right people with their messaging at the right time in order to get results from their campaigns.


AI helps improve customer experience on websites

Customer experience is the key to success in the digital world. The more satisfying your website is for customers, the better their experience will be and the more likely they are to return. AI helps improve customer experience by enabling you to:

  • Provide better customer service by understanding what customers want when they talk about their needs or problems with AI-powered chatbots that respond in real time.
  • Personalize content for each user based on preferences and behaviors, adding a personal touch at scale.
  • Optimize marketing campaigns so that you can reach the right audience with well-timed offers and messages.


Data will help AI get smarter every day

AI is data-driven; it learns from the past and present. The more data you feed to your AI system, the smarter it gets. And that's not only true for training AI models on your own data—it also applies to other AI systems as well.

If you're using an open-source model, there are other AIs out there that will have learned from some of your users' behavior too! This means that if you've trained a specific model in one app and want to use it in another, all those learnings from your users will be available for use as well—no need for retraining or starting again from scratch.

This is what's known as transfer learning. Transfer learning is when a machine learns from one set of data and applies it to another, similar task. It allows us to reap the benefits of having trained models without needing to start over every time we want to use them in different contexts.


Marketing and customer service applications will be the biggest beneficiaries of AI innovations in coming years

AI is already being used to improve personalization in the B2C world; one of the best-known examples is Amazon’s recommendation engine which suggests products based on your past purchases. But AI will soon be able to take this one step further by recommending specific items based on a combination of factors including your past buying history, but also what other people with similar interests have bought as well.

In addition, AI will be used to improve customer experience by making interactions more efficient and effective. For example, chatbots are already being deployed within most businesses today – they can answer basic questions about products or services, provide product information (including prices), process orders and payments and alert customers when an order has shipped.

However, these existing chatbots can only do so much with their limited set of capabilities today; tomorrow’s chatbots will be able to offer up customized recommendations based on each individual user’s preferences and purchase history—so if you buy a new pair of shoes one week and then return them two weeks later because they weren’t quite right for you then you won't get recommended those same shoes again next time around!

AI will also be used extensively across digital marketing campaigns over the next few years—from improving performance reporting through better attribution modeling by machine learning algorithms which analyze click data; understanding consumer behavior patterns across social media channels using natural language processing techniques; optimizing ad spend through predictive analytics models which automate campaign planning processes etc.



Hand holding up abstract digital brain

The future of AI is bright, and we expect to see the technology becoming more sophisticated over time. It has the potential to transform businesses, but it also means that marketers will have to adapt their approach in order to not just survive but thrive in an increasingly competitive landscape. 

No matter what happens next however, there are a few things we can be sure about: DXPs will continue growing as more companies recognize their value for improving customer experience online; data will only become more important as we move towards an era where AI does most of the decision making; and digital experiences will remain at the forefront of innovation because they’re so closely linked with human emotions!