Feature
The Gist
- AI-powered advantage. AI-driven personalization enhances customer experiences.
- Striking balance. AI facilitates trade-offs for efficient personalization.
- Skills matter. Expertise in AI, ML and search tech is vital.
As organizations make greater efforts to engage with both customers and employees, many are investing in digital experience platforms (DXPs), which support the management, delivery and optimization of digital experiences. Now, with AI-driven personalization promising to revolutionize customer experiences, many organizations are wondering what tangible benefits they can really anticipate by infusing AI into their engagement efforts.
Overcoming Barriers to AI-Driven Personalization
While the value of personalization is clear to digital marketing leaders, the added value of AI isn’t always obvious to other corporate leaders.
“Challenges to using AI on these platforms for purposes such as personalization, include defining and measuring value and the ability to leverage data adequately,” said Bern Elliot, research vice president and distinguished analyst at Gartner Inc.
As evidence of both trends, a recent survey by Gartner found that 79% of corporate strategists said that technologies such as analytics, artificial intelligence and automation will be critical for their success over the next two years. Still, Gartner data also shows that the top two barriers to AI adoption are the difficulty or inability to measure the value of AI, and the lack of understanding of AI benefits and uses, both cited by 19% of business leaders.
Related Article: Hyper-Personalization: How AI & ML Are Building a New Framework for Ecommerce CX
The Goals of AI-Driven Personalization
The main goal of personalization is to give every customer a unique experience tailored to their preferences and interests, hoping to increase their satisfaction and consequently retention, explained Hans Sayyadi, head of engineering at Uber Eats. Sayyadi is responsible for activities and investments around AI, machine learning, search and personalization for the transportation firm. Adding AI to the personalization effort is akin to an athlete taking steroids to boost performance.
“AI can enhance our understanding of content through descriptions and images. We can use it to build classifiers to detect low-quality or harmful content that should be filtered based on policies or regulations,” Sayyadi explained.
Developing Personalization From User-Based Models
“AI enables us to learn from user interactions and develop usage-based or model-based recommender algorithms, which have shown superiority over content-based systems,” Sayyadi continued. “Such models can automatically learn similarity and connection between products purely from user interaction. They can also automatically learn complex patterns in user behaviors, and then apply them during the prediction/ranking.”
Given that personalization and recommendation systems often involve high-cardinality problems, where ranking a large set of items is slow and resource-intensive, AI techniques such as vector search can efficiently generate a smaller, yet relevant, subset of items, known as candidates, Sayyadi explained. This initial step narrows down the selection before applying the final, more computationally intensive personalized model.
“Additionally, personalization involves multiple factors around user satisfaction or business metrics that require trade-offs and efficient mixing. AI can help build each component and optimize their combination for the most effective personalized experience,” Sayyadi said.
Related Article: AI’s Role in Digital and Retail Personalization, Part 1: The Big Picture
How AI-Driven Personalization Impacts Consumer Behavior, and Vice Versa
For consumers, AI-driven personalization has the potential to significantly transform user experiences by reducing friction, minimizing the number of clicks, and decreasing the time users spend before consuming content or placing an order,” Sayyadi explained.
Consider the scenario of opening a favorite streaming app on television and having to search for a favorite show each time, navigating through multiple seasons and episodes to resume watching a show in progress.
“Such a process can be frustrating and time-consuming,” Sayyadi said.
Learning Opportunities
Webinar
Jul
17
Turning Partial Prospect Data Into Solid Gold: Adobe Real-Time CDP + Acxiom
Join us for an exclusive webinar to witness the transformative impact of the Adobe + Acxiom solution on prospecting.
Register
Webinar
Jul
18
Power Up Your Content Lifecycle
Join this webinar to learn how to achieve more with less by leveraging powerful tools and automation.
Register
Addressing Consumer Challenges With AI Tools
Without personalization, users might also be presented with a disambiguation screen each time they make a request via a voice remote, Sayyadi explained. For example, viewers in Chicago might encounter a challenge with the query "Chicago Fire," which refers to both a TV show and an MLS soccer team.
“Personalization can address such challenges by presenting users with relevant content upon opening the app, making recommendations tailored to their preferences, and inspiring them to discover new and relevant offerings,” Sayyadi explained. “By personalizing the user experience, AI-driven personalization can make browsing, searching, and discovery more efficient and enjoyable.”
Similarly, when it comes to discovery, users often struggle to determine what they're in the mood for or even formulate a search query, Sayyadi continued. “Even if they have a specific query, they might end up with hundreds or thousands of results.”
Personalization can address the challenge by presenting users with more relevant results based on their preferences, or recommending relevant content as soon as they open the app, even without a specific query, Sayyadi explained.
Personalized Algorithms & Inspiration to Find Relevant Content
“Personalization algorithms can inspire users to not only find what's relevant to them, but also discover new types of content or explore new products and offerings from businesses,” Sayyadi said. “Ultimately, AI-driven personalization aims to enhance the user experience by tailoring it to individual needs and preferences, making interactions more efficient, engaging, and personalized.”
Organizations should be aware that when properly done, the use of AI-driven personalization will improve the experience for users due to better matching. But when the challenges are not met, the result can be a poorer experience for the customer, Elliot said.
“In those cases, simpler approaches to targeting of material than personalization, such as basic segmentation, may be more effective,” Elliot explained.
Getting Started, Moving on to AI-Driven Personalization
Getting started with personalization is relatively easy, even without expertise in building custom solutions, Sayyadi explained.
“Many popular cloud services offer tools and offerings that provide decent personalization capabilities. However, as organizations advance in their personalization journey, they will require AI, machine learning and personalization expertise to develop custom-made solutions tailored to their specific data, policies, and requirements,” Sayyadi said.
Adequate hardware and resources are also necessary for building and maintaining large-scale data processing, indexing, and serving infrastructure, Sayyadi continued. ML Ops practices should be in place to ensure that models remain up-to-date and avoid stagnation.
AI, ML & Search Technologies Needed for Success
“Lastly, having skilled individuals experienced in the intersection of AI, ML, search technologies, and large-scale distributed systems is crucial for success,” Sayyadi stressed.
Once an organization has been able to develop or acquire these skill combinations, in the short term, they can maximize user engagement, conversions, and revenue, Sayyadi said.
“By offering personalized experiences tailored to individual customers, organizations can increase stickiness and retain users over time. When users feel that a product understands and caters to their needs, they are less likely to switch to a competitor, resulting in long-term benefits,” Sayyadi said. “Personalization also allows organizations to optimize customer journeys and funnels, making tasks easier for users and driving satisfaction and loyalty.”
