The rise of conversational commerce in the online shopping business

May 19th, 2017

With the growing expectations of online customers, and the increasing competition between e-commerce websites and services, it is necessary for online retailers to further develop the options and services provided in order to attract and keep more customers.

One tendency is the growing demand for more visual, written, vocal and predictive capabilities of the personalized extensions, apps and widgets of the retailers and the various brands offering their products online.


The rise of conversational commerce


A survey ordered by Nuance Communications shows that most consumers would prefer to make shopping faster and easier by engaging in real time conversations with virtual assistants to help them find exactly what they need, rather than search and browse through the online store. The same percentage of nearly 90% of the consumers surveyed also want personal interaction and relationship hinges on service. More than 60% claimed that they want proactive messaging when shopping online.

This tendency is now being called “conversational commerce”, and in order to be able to provide this sort of customer service, e-commerce owners should develop the instruments allowing for multi-channel online conversations with their customers.

Customers around the world expect to receive better and more personalized search results when they are shopping, which means that they anticipate that the machines will exhibit indistinguishable and equivalent to that of a human sales person.

This is especially true for the online fashion apparel and accessory commerce where this can be achieved via a capable AI agent that can make personalized recommendations based on images provided by the customer from social media or their phone. The agent should be able to identify the type of style they prefer wearing, the accessories they like, and other relevant information which can affect their choice of clothing, footwear or other fashion accessories and to find the closest match offered by the retailer. Such a system would allow customers to snap a photo of a fashion item they like and search through their preferred brands and retailers for similar products.

The latest generation of AI technologies with predictive analytics uses historical data in order to determine quite accurately the intents for an action of a user, as well as ways to improve the experience, and at the same time aggregates the information to all customers of the retailer.

Currently, consumers are complaining about the difficulties of discovering a product in e-commerce sites which have very large catalogs, where the search and the recommendations are not as accurate and consistent due to the fact that they are indexed on the metadata.

Expectations are that with the development of the newest AI technologies and systems, the search engines in online stores will understand both the explicit as well as the implicit cues from the consumer. In the case of fashion stores, the explicit cues can include: a product, the fit, the price limit, style, etc. The implicit cues can include the gender of the consumer, their favorite brands, their specific shopping style, size and other factors which can help recommend the best product for them quickly and efficiently, just like a human salesperson would.

These innovative services will definitely have a positive effect on the sales, the customer experience as well as the conversions and retention of customers for every e-commerce store.



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