The Role of AI in Personalizing User Journeys

Case Studies Across Industries

Incorporating AI within the user journey is a great way to make the most of the data you gather. However, you don’t need to reinvent the wheel to pioneer innovation in personalization. Instead, consider borrowing from the playbooks of well-established companies that have used personalized marketing successfully. Let’s consider a few examples.

Penguin Random House

Book lovers enjoy receiving recommendations from well-informed sources. So Penguin’s marketing team produces quizzes that help folks discover their next read. This soft-sell approach to personalization works well because it gives consumers something of value as they navigate Penguin’s Web site.

You could follow suit by using AI to produce product recommendations that are based on the user’s activities. For example, a company that sells protein powders could partner with a macronutrient-tracking company to provide insights on their consumers’ diets and help them produce hyper-personalized shopping recommendations.

Vidyard

Sales company Vidyard uses video-based sales strategies to help firms increase their conversion rates and leads. They take a personalized approach to appeal to customers, sending their leads personalized videos that use their names and emphasize client-tailored data points.

While this approach is time consuming, it could be perfect if your firm sells to only a few high-profile customers each month. You could use AI to gain a comprehensive understanding of each potential lead in your CRM system and gather data for valuable KPIs relating to session lengths, bounce rates, and pageviews.

Spotify

Spotify provides a perfect example of the power of personalization. Customers post their yearly Wrapped recaps across social media because they want to show their musical tastes to their friends and family. Spotify also uses AI to develop taste profiles that let them provide accurate listening recommendations.

You could leverage AI to develop personalized user interfaces that encourage visitors to remain on your Web site or app longer. For example, a company that provides an app that suggests workouts to fitness enthusiasts could use AI to keep track of the most popular exercises and recommend modifications to future workouts. This approach could increase engagement and enhance customer loyalty.

Security Challenges

Personalization can help you achieve your UX goals by meaningfully improving the customer journey. Even simple enhancements such as chatbots that greet returning customers by name could impact your Web site’s performance. However, increasing your use of personalization does represent a meaningful security challenge because you must keep the personal data that you store secure to prevent its falling into the hands of malicious actors.

Improving network security is particularly important if you’re using devices such as smart speakers to gather data from the IoT. You can improve your network security by doing the following:

• using a network-monitoring system that blocks new devices from entering the network
• installing asset-management technology to ensure that you regularly update and account for all IoT devices
• monitoring external intrusion detection prevention systems (IDPSs) to detect anomalous activity and alert human agents to any suspicious use
• leveraging virtual private networks (VPNs) that can push firmware updates and enhance patch-management efforts

Adopting these practices increases the integrity of your network and reduces the risk of a malicious actors’ gaining access to the data you employ in personalizing user journeys. Plus, by proactively working to prevent data breaches, you can help protect your brand’s reputation. Improving network security can ensure that your customers trust you to protect the data you need to effectively personalize the customer experience.

Conclusion

AI can transform your approach to personalizing your Web site or app and enable you to improve its user journey. Automation makes personalization much more efficient, too. This efficiency is key if you want to use AI in UX design, but don’t have a large team that is capable of crunching data sets and filling out CRMs to track user behaviors. Using AI to personalize the user journey can empower your in-house sales team, too. The salespeople who call clients and send email messages to customers are sure to benefit from the insights that machine-learning (ML) algorithms can produce.