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Global Retail Spend via Conversational Commerce to Reach $48b by 2028

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A new study from Juniper Research, the foremost experts in telecommunications markets, has forecast global retail spend via conversational commerce channels will increase to $43 billion by 2028, from $11.4 billion in 2023.

This forecast growth will be driven by the emergence of new personalised services, made possible by incorporating AI and LLMs (Large Language Models).


Conversational commerce is the use of messaging or natural language interfaces; enabling businesses to interact with customers for use cases including inquiries, placing orders, and customer support.

ChatGPT Role in Conversational Commerce

The study predicts automated services provided by AI-based LLMs, such as ChatGPT, will become key differentiators for conversational commerce vendors in 2024.

Juniper Research analysed and scored leading conversational commerce platforms based on product capabilities, depth of services and market presence, and identified the top 5 leading vendors in the market:

1.    Infobip
2.    Twilio
3.    Vonage
4.    Meta
5.    Sinch

Source: Juniper Research

Top Vendors Maximising AI Benefits for Conversational Commerce

The top-ranked conversational commerce vendors offer self-managed, AI-based chatbot solutions to enterprises via multiple channels, including RCS and OTT business messaging apps.

Given growing adoption of conversational commerce via omnichannel communications, the research urges leading vendors to introduce LLM-based conversational services across as many communications channels as possible.

The research identified voice channels as an underserved emerging opportunity for vendors.

Therefore, they must implement LLM-based conversational services into voice channels, including voice assistants and CCaaS (Contact Centre-as-a-Solution) platforms to maximise future revenue. To capitalise on the $43 billion conversational commerce opportunity within retail, vendors must leverage LLMs to immediately support multiple languages.

 

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