3 Limitations of Chatbots (and How to Overcome Them)

The relentless advancement in artificial intelligence (AI) has forced every retail organization to look at ways to make the most of the technology. Whether in the form of Copilots or chatbots, AI has seeped into every business operation. While AI chatbots find applications across various use cases, from customer service to lead generation and product purchasing, they come with a few apparent limitations.

This blog will showcase chatbots' top 3 limitations in the retail industry and how technologies like Augmented Reality (AR) and Virtual Reality (VR) can help customer experience-focused brands overcome them.

The Inherent Challenges of Chatbots

Chatbots have become widespread on most business websites. Primarily used for simple interaction-driven customer service, today, bots are also increasingly being adopted for marketing purposes too. From enabling real-time interactions to on-the-spot personalization, chatbot adoption in marketing is constantly growing.

However, despite their use for lead generation, qualification, conversion, customer engagement, and support, chatbots have several limitations that dilute their impact and benefits. Let’s look at the top 3 challenges of chatbots:

1. Static:

AI chatbots respond to customer queries and requests in a static manner. Since they rely on predefined rules and responses, they lack interaction capabilities. Such rule-based bots have a less flexible conversation flow and do not enable an intuitive or engaging user experience. Even conversational bots that enrich rule-based bots with visual UI elements struggle with complex tasks and might need human intervention. Their inability to understand complex situations or provide personalized attention makes them a perfect fit only for simple tasks.

For example, if a customer asks for eye-wear recommendations on an e-commerce website, the chatbot can only suggest options based on the customer’s past browsing history. It cannot advise products that would fit perfectly or match their style because it has limited insight into these aspects.

Perhaps most crucially, even the most adept chatbots, are clearly robotic and “non-human”. Users interacting with them, do so dispassionately and without emotion. This does very little to “connect” the brand with its users and elevate the interaction beyond being merely transactional.

2. Limited Context:

AI chatbots are only as good as the data they’re trained on. If they rely on a limited number of data sources and formats, they tend to deliver outcomes that are limited in context. They can only respond to questions and queries based on the keywords and phrases they have been programmed to recognize. Such a lack of contextual understanding makes adapting to new situations and requirements difficult, leading to confusion and misinterpretation. Any attempt to widen the application requires the skills and efforts of qualified experts that are difficult to find and costly to hire.

For example, a customer surfing for footwear on a website can only get color or size recommendations from a chatbot. Without a virtual try-on feature, the customer cannot get a hyper-realistic feel of products, leading to limited sales or costly returns.

3. Biased Results:

AI chatbots learn from data. The results will be biased or subjective if the data is incomplete or incomprehensive. Many chatbots also face bias in their algorithms due to skewed training data or design flaws. Some others also adapt based on user interactions. If they predominantly engage only with a particular group of people, their responses might not align with those of people from other groups.

For example, conversational chatbots trained in styling trends in America can have difficulty comprehending the modest trends of customers from the Middle East. They might deliver product recommendations based on the average American customer, which might be a misfit in this region.

Real-life Experiences:

AR-powered tools with virtual try-on (VTO) features can enable companies to deliver exceptional shopping experiences to customers. Offering a true-to-life virtual experience of apparel or accessories, these tools can enhance customer satisfaction while enabling businesses to build relationships and boost conversions.

Tailored Products:

Digital ambassadors can offer bespoke styling recommendations to customers based on their face shape, skin color, hairline, and gender. Customers can use advanced 3D configurators to personalize or configure their preferences and enjoy an intuitive shopping experience. For example, customers can personalize a jewelry item in different colors, materials, or stones and enjoy a realistic depiction of the products of their choice.

Virtual Stores on the Metaverse:

AR/VR technology also allows brands to launch virtual stores on the Metaverse and deliver immersive shopping experiences to customers traversing through. Customers can explore the store layouts, browse products from shelves, handers, or displays, and even order virtually.