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How is conversational AI shaping up eCommerce?

According to Gartner reports that during the past four years, there has been a 270% increase in the number of enterprises implementing artificial intelligence. However, there are many misunderstandings about everything AI-related. In contrast to popular belief, the area of AI has been studied for almost 70 years. As a result, this decade (and mainly 2022) will be crucial for AI and its related sectors because three fundamental causes are anticipated to cause a significant shift towards AI and intelligent automation: to decrease staff costs and reliance on human capital, to boost productivity the accessibility and affordability of AI-based methods.


Artificial Intelligence (AI) Use Cases in eCommerce:

The data on the use of AI in eCommerce helps put the technology's extensive use into context. However, the statistics only give a bird's-eye view of a complicated field of business with multiple distinct implementations motivated by various goals.

Analytics for Big Data:

eCommerce companies have access to staggering amounts of data that include crucial parameters that may be utilized to develop more effective sales, marketing, and production plans and make better data-driven decisions in general. Additionally, eCommerce companies are employing AI and big data analytics to routinely scan their website to identify fraudulent reviews and search the internet for trigger words in social media posts, blogs, and even tweets.

Retargeting and Lead Engagement:

eCommerce companies get a lot of information about leads or potential clients. AI can contact warm and cold leads, some of whom may not be familiar with the brand. Additionally, it has been demonstrated that AI is a highly effective tool for remarketing clients. Retargeting is a type of marketing that aims to attract clients who are in the buying process but have not made a purchase. Conversational AI is one of the most personalized business messaging types.

Conversational AI Chatbots:

A new breed of virtual agents uses recent advancements in natural language processing (NLP) and natural language comprehension (NLU). These chatbots can have realistic conversations by analyzing the conversation's context, figuring out the customer's goal, and even creating new responses utilizing a vast knowledge library.

Contextual Search:

Websites and Mobile Apps can use contextual search, a potent AI tool, to deliver more precise search results. To improve the accuracy of search results, contextual search utilizes an AI engine that examines external data such as seasons, popular subjects, and more. An extension of the contextual search engine uses outside data, such as browser history and cookie data that may have earlier searches, purchase history, etc., to provide tailored recommendations of goods most likely to interest the particular customer.

Visual and Voice Search:

Implementing these technologies into your website or mobile app will probably be beneficial as home automation and hands-free searches continue to gain popularity (Alexa and Google Home are two examples of intelligent assistants).

Wrapping Up:

Many online and offline businesses have historically resisted the adoption of AI, but shifting consumer habits and market conditions are strong predictors of AI's long-term viability as a critical eCommerce technology in this decade. The cost to develop these solutions has never been lower, and the advantages of AI are now too significant to ignore.

Talk to an expert immediately if you would like to know more about how your eCommerce company can prepare for conversational AI's future.

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