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Let’s say you’re out with friends when the question of where to go to dinner arises. A search on your phone for what’s “nearby” greets you with a buffet of options, and you spend what feels like forever deciding on the right one, only to give up and opt for a place you’ve been a million times before. This is the paradox of choice: The more choices we have, the more overwhelmed we feel. Eventually that overwhelm leads to “decision fatigue,” or settling for a subpar option because it’s easier.
But this problem isn’t limited to restaurant selection. As eCommerce platforms rapidly expand, smaller brands are entering the fray alongside established, global retailers. Now that consumers have more to choose from than ever—and the online web experiences of these brands are largely identical—shoppers are struggling to find exactly what they want. This can negatively impact their business KPIs, especially as shoppers jump to competitors’ websites or abandon their carts.
Abandoned carts are abandoned revenue, so what can retailers do to combat decision fatigue? I chatted with Lior Delouya, Product Manager at Dynamic Yield by Mastercard, about streamlining the decision-making process with personalization. Drawing from his 8+ years of experience in leading teams in customer success, he has a unique perspective on alleviating choice overload.
JR: What are some factors that pile up and contribute to decision fatigue?
Lior: Even seemingly minor tasks can significantly impact the shopping experience. You may not think of the following as decisions, but they are:
Each decision, however small, can collectively drain the consumer’s energy, leading to mental exhaustion and dissatisfaction with the shopping process over time. This exhaustion can spur customers to take long breaks (averaging about a week) in between product searches, according to a joint paper from NYU and UCLA Anderson. That break time didn’t necessarily lead to a sale—76% of shoppers didn’t make a purchase after their initial click on a fashion website.
Why might people give up on buying when searching from one website to another?
The effort and time required to navigate multiple websites—and compare prices, features, and reviews across those sites—can frustrate shoppers, especially if the process doesn’t quickly lead to a gratifying decision. Some have the nagging feeling that they are paying too much, which can create a situation in which they obsessively search for a better deal. The problem is, this comparison process could go on endlessly, considering the wealth of options at our fingertips.
Eventually, those shoppers become overwhelmed and paralyzed, abandon their shopping carts, and leave sites empty-handed.
Typically, expanding a brand’s product catalog is in its best interest. But how can brands achieve that goal without stressing out their customers?
Brands should strike a balance between offering a broad selection and organizing their offerings effectively. Of course, one of the best ways to do that is through personalization, which enables retailers to deliver bespoke product recommendations that streamline the shopping experience.
Personalized conversational experiences can play a pivotal role here. They excel in providing inspiration and recommendations, which is particularly useful for customers who don’t have a specific product in mind. They can also mitigate the negative impact of a sprawling product catalog by ensuring customers don’t have to sift through irrelevant options to find what they’re looking for.
By doing so, conversational AI also reduces the impact of the paradox of choice: Shoppers have a limited number of options to pick from, curated based on prior interactions and their own preferences.
How does AI help narrow down decisions for users with no prior data?
AI can start by making initial recommendations based on contextual data (such as geolocation or local weather conditions), basic demographic information, and even comparisons with similar user profiles. It can then adapt when it interacts with the user.
Some believe AI is pulling us further away from the human experience—but it may actually be the other way around. How will the interplay between humans and AI evolve in the future?
As advancements in deep learning—and large language models (LLMs) in particular—gain momentum, the online shopping experience will begin to resemble a brick-and-mortar store. Imagine a personal stylist who is not only well-versed in the latest trends and fits but also deeply understands your unique style preferences and needs, meticulously selecting items tailored just for you. With the power of AI, every customer will have access to an expert guide that can lead them through their purchasing journey. It could spell the end for our decision-heavy shopping woes—and the impersonal, transactional nature of shopping online. In many ways, AI shopping assistants will be more intuitive than the older model of endlessly browsing product listing pages (PLPs) once consumers try them out. We’re all used to searching for items in “Googlish”—brief two-word search queries—because of older technological limitations. We grew up with them. Now everything is turned upside down. We’ll have to relearn how to communicate with tech in a more human way.
But AI is driven by humans as well. It’s crucial for brands to nurture internal talent to operate and refine these technologies effectively. Investing in skilled professionals who can manage, analyze, and drive innovation with these systems will keep brands one step ahead of the competition over the coming years.
What advice do you have for companies interested in using AI-driven shopping assistants but hesitant about whether shoppers will embrace them?
As with any new technology, there’s an adoption curve. Well-defined entry points to the chat experience, targeted marketing campaigns that emphasize their usefulness, and clear, straightforward tutorials can help educate shoppers. Seamless integration into the online shopping environment is essential to ensure a smooth user experience. By showcasing how AI assistants can surpass the limitations of conventional search tools and offering incentives like discounts or personalized deals, companies can motivate users to embrace these innovative search methods, leading to a more efficient and satisfying shopping experience.
Decision fatigue is now a fact of modern life—and its especially pervasive in the eCommerce industry. As customers encounter a mounting number of infinitesimal shopping dilemmas, they are more apt to abandon their carts and take their business elsewhere. But the adoption of highly capable, empathetic AI shopping assistants could spell the end of consumers’ shopping woes—if retailers are willing to take the plunge.
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