According to a survey released in 2024, about one-third of interactions with e-commerce AI chatbots were related to product information such as product advice, product availability, or product details. Another 20 percent of analyzed interactions covered order and shipping, whereas four percent of them were conversations to arrange a product return.

In nearly * out of 10 cases, chatbots answer shoppers' questions perfectly, a U.S. survey from 2023 revealed. However, only ** percent of surveyed customers purchased the product after having successfully interacted with a chatbot.

In 2024, a notable portion of consumers showed a preference for interacting with AI-powered chatbots when seeking support. Specifically, almost half of customers used them for scheduling appointments, around 47 percent for help to place orders, and 46 percent when reporting an issue or starting a return. Additionally, about 45 percent turned to chatbots for tech product support.

Bitext - Retail (eCommerce) Tagged Training Dataset for LLM-based Virtual Assistants

  Overview

This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [Retail (eCommerce)] sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-retail-ecommerce-llm-chatbot-training-dataset.

As per Cognitive Market Research's latest published report, the Global Chatbot market size was USD 3.02 Billion in 2022 and it is forecasted to reach USD 24.58 Billion by 2030. Chatbot Industry's Compound Annual Growth Rate will be 21.58% from 2023 to 2030. Chatbot Market Dynamics

Key Drivers of Chatbot Market

High integration of chatbot in various industrial verticals:

Use of chatbots is rising exponentially in both the business sector as well as in consumer market. It is an instant messaging app that creates natural conversations between businesses and customers. The demand for chatbot has increased in recent years attributed to the rising inclination of people across the world towards online shopping. In online shopping platforms, sales team uses chatbots to answer non-complex product questions which helps in improving the satisfaction level and convenience of customers.

Moreover, the world is moving rapidly towards digitalization. Amid COVID-19 pandemic, the world has been turned totally into digital world. Hence, healthcare industry, like all other industries have started using chatbot aggressively which helps in connecting patients with hospitalists for general diagnosis and treatment. It also allows in scheduling appointments with physicians without needing to travel to the hospital.

Chatbot have been connected through websites, mobile applications, along with social media platforms which further drives the growth of market. As AI implementation in chatbot is rising, it is revolutionizing the business processes in multiple industries. AI-powered chatbot has thus no limits for its usage in various sectors, including BFSI, telecommunication, e-commerce, and others accrediting the growth market across the world.

Increasing need for customer analytics and emergence of messenger apps to drive the market

Key Restrains of Chatbot Market

Drawbacks regarding the full understanding of natural language:

In order to ensure that chatbot is providing correct and relevant information to the customers, it must be updated with the correct information. However, people in today's world widely uses shortforms out of their habit for speedy responses. Such kind of slangs or misspellings are frequently misunderstood by these chatbots. Hence, inability in understanding this kind of natural language may hamper the growth of chatbot market. However, rising use of cloud services by various enterprises will help chatbot to retrieve huge amount of data from the cloud which will enhance the understanding of natural language and further stimulating the growth of chatbot market.

Key Trends in Chatbot market:

AI chatbots with high emotional intelligence will drives the market in coming years:

Using artificial intelligence and real time data, chatbot is now able to do sentiment analysis by using facial emotion recognition, eye tracking technology and video interactions in real-time. This allows it to understand the mood, pitch, and feelings and customize their responses to deliver custom-made communication.

Thus, it will not be wrong to say that AI-powered chatbot is going to enhance values in business sectors by providing limitless applications in large, medium and small enterprises. When more companies use the cloud, their ability to manage customer interactions, data management, and internal communication effectively will greatly increase their business agility without having to worry about increased infrastructure costs or security risks.

What is the impact of the COVID-19 pandemic on Chatbot Market:

Advent of COVID-19 pandemic has reshaped the lives of people across the globe by changing the way of work, shop, and learn. Every sector has been impacted due to the sudden out-break of pandemic. Lockdowns were announced and many customer service centers were closed. Disruption in supply chain occurred and online services failed to handle additional volumes effectively. Hence, to handle this chaos effectively, companies started investing in new technologies to provide additional support and allow workers to adapt to work-from-home setups.

Lockdown during year 2020, embraced digital world like never before. Thus, digital literacy rate during the pandemic increases exponentially which results in stimulation of chatbot use. Retail businesses increases the use of chatbot during COVID-19 to fulfil consumer needs and giving retailers...

Ecommerce FAQ Chatbot Dataset Overview The Ecommerce FAQ Chatbot Dataset is a valuable collection of questions and corresponding answers, meticulously curated for training and evaluating chatbot models in the context of an Ecommerce environment. This dataset is designed to assist developers, researchers, and data scientists in building effective chatbots that can handle customer inquiries related to an Ecommerce platform. Contents The dataset comprises a total of 79 question-answer pairs… See the full description on the dataset page: https://huggingface.co/datasets/Andyrasika/Ecommerce_FAQ.

This dataset contains responses from 400 e-commerce users on AI chatbot services. It includes variables such as response time, information quality, perceived usefulness, perceived ease of use, customer satisfaction, and customer loyalty.

Chatbots bring multiple advantages to online shopping. About *** in *** U.S. consumers answering a 2023 survey thought that chatbots saved their time because they are always available. Another ** percent of respondents appreciated that chatbots immediately answered their questions.

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Chatbot Market Size 2025-2029

The chatbot market size is forecast to increase by USD 9.63 billion, at a CAGR of 42.9% between 2024 and 2029.

The market is witnessing significant growth, driven by the integration of chatbots with various communication channels such as social media, websites, and messaging apps. This integration enables businesses to engage with customers in real-time, providing instant responses and enhancing customer experience. However, the market faces challenges, including the lack of awareness and standardization of chatbot services. Despite these obstacles, the potential benefits of chatbots, including cost savings, increased efficiency, and improved customer engagement, make it an attractive investment for businesses seeking to enhance their digital presence and streamline operations. Companies looking to capitalize on this market opportunity should focus on developing chatbot solutions that offer customizable features, seamless integration with existing systems, and natural language processing capabilities to deliver human-like interactions. Navigating the challenges of awareness and standardization will require targeted marketing efforts and collaborations with industry partners to establish best practices and industry standards.

What will be the Size of the Chatbot Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe market continues to evolve, with dynamic market dynamics shaping its growth and applications across various sectors. Conversational AI, a key component of chatbots, is advancing with the integration of sentiment analysis, emotional intelligence, and meteor score to enhance user experience. Pre-trained models and language understanding are being utilized to improve performance metrics, while neural networks and contextual awareness enable more accurate intent recognition. Deployment strategies, including policy learning and cloud platforms, are evolving to support cross-platform compatibility and multi-lingual support. Performance metrics, such as F1-score and response time, are crucial in evaluating model effectiveness. Reinforcement learning and knowledge base integration are essential for chatbot development and lead generation. Error rate and character error rate are critical in speech recognition, while API integration and dialogue state tracking facilitate seamless conversational experiences. Technical support and customer engagement are primary applications of chatbots, with sales conversion and automated responses optimizing business operations. Deep learning architectures and transfer learning are driving advancements in question answering and natural language processing. Contextualized word embeddings and dialogue management are essential for effective user interaction. Overall, the market is an ever-evolving landscape, with continuous innovation and integration of advanced technologies shaping its future.

How is this Chatbot Industry segmented?

The chatbot industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. End-userRetailBFSIGovernmentTravel and hospitalityOthersProductSolutionsServicesDeploymentCloud-BasedOn-PremiseHybridApplicationCustomer ServiceSales and MarketingHealthcare SupportE-Commerce AssistanceGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKMiddle East and AfricaEgyptKSAOmanUAEAPACChinaIndiaJapanSouth AmericaArgentinaBrazilRest of World (ROW)

By End-user Insights

The retail segment is estimated to witness significant growth during the forecast period.The market is experiencing significant growth, particularly in the retail sector. E-commerce giants like Amazon, Flipkart, Alibaba, and Snapdeal are leading this trend, integrating chatbots to improve customer experience during online product searches. These AI-powered bots facilitate quick and effective resolution of payment-related queries, enhancing the shopping experience. However, retailers face challenges in ensuring a seamless user experience, as consumers increasingly prefer mobile shopping. Deep learning architectures and natural language processing (NLP) are crucial components of chatbot development. NLP enables intent recognition, sentiment analysis, and entity extraction, while deep learning models provide contextual awareness and dialogue management. Speech recognition and dialogue state tracking further enhance the user experience. Cross-platform compatibility and multi-lingual support are essential features for chatbots, catering to diverse user bases. Pre-trained models and transfer learning enable faster development and deployment. Reinforcement learning and policy learning optimize bot

This dataset contains survey responses collected to examine the impact of AI-driven chatbot affordances on purchase intention in the e-commerce sector in Sri Lanka. It includes data on key mediators such as customer engagement, trust, and satisfaction, along with demographic variables such as age, gender, employment type, and online shopping frequency. The dataset is structured using a 5-point Likert scale and supports analyses using PLS-SEM. It is valuable for researchers exploring consumer behavior, AI applications, and digital marketing strategies in online retail.

Introduction

This Swedish Call Center Speech Dataset for the Retail and E-commerce industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for Swedish speakers. Featuring over 30 hours of real-world, unscripted audio, it provides authentic human-to-human customer service conversations vital for training robust ASR models.

Curated by FutureBeeAI, this dataset empowers voice AI developers, data scientists, and language model researchers to build high-accuracy, production-ready models across retail-focused use cases.

Speech Data

The dataset contains 30 hours of dual-channel call center recordings between native Swedish speakers. Captured in realistic scenarios, these conversations span diverse retail topics from product inquiries to order cancellations, providing a wide context range for model training and testing.

Topic Diversity

This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral, ensuring real-world scenario coverage.

Such variety enhances your model’s ability to generalize across retail-specific voice interactions.

Transcription

All audio files are accompanied by manually curated, time-coded verbatim transcriptions in JSON format.

These transcriptions are production-ready, making model training faster and more accurate.

Metadata

Rich metadata is available for each participant and conversation:

This granularity supports advanced analytics, dialect filtering, and fine-tuned model evaluation.

Usage and Applications

This dataset is ideal for a range of voice AI and NLP applications:

Vietnam chatbot market size reached USD 31.2 Million in 2024. Looking forward, IMARC Group expects the market to reach USD 207.1 Million by 2033, exhibiting a growth rate (CAGR) of 18.50% during 2025-2033. The market is being driven by several key factors, including an increasing need for improved customer service, a rising trend in using messaging platforms to offer efficient customer solutions, and a growing uptake of over-the-top (OTT) platforms for streaming movies, series, and documentaries.

IMARC Group provides an analysis of the key trends in each segment of the market, along with forecasts at the country level for 2025-2033. Our report has categorized the market based on type, product, application, organization size, and vertical.

The chatbot market attained a value of USD 839.33 Million in 2024. The market is expected to grow at a CAGR of 24.90% during the forecast period of 2025-2034. By 2034, the market is expected to reach USD 7754.56 Million.

The chatbot market revenue is expanding with businesses increasingly recognizing the importance of providing round-the-clock customer service. Chatbots meet this demand by offering instant, consistent responses without breaks or delays. With global customers operating in different time zones, companies leverage chatbots to ensure uninterrupted support. In May 2025, French AI startup Mistral AI launched Le Chat Enterprise, a corporate-focused chatbot designed for deep integration with enterprise content systems and offer scalable solution for global businesses. Such launches improve customer satisfaction, reduces churn, and allows human agents to focus on complex issues.

The chatbot industry is revolutionizing e-commerce via conversational interfaces that guide users from product discovery to purchase. Consumers increasingly prefer real-time conversations over static websites, particularly on mobile. Brands use chatbots to simulate the in-store assistant experience, reducing cart abandonment and increasing sales. In June 2025, Walmart launched its new generative AI shopping chatbot Sparky to help users find, plan, compare, and repurchase products effortlessly. As digital transactions rise and mobile commerce dominates, the need for interactive, conversational sales channels propels the market forward.

AI in E-Commerce Market Outlook

According to our latest research, the global AI in E-Commerce market size reached USD 8.9 billion in 2024 and is expected to grow at a robust CAGR of 18.6% from 2025 to 2033. By the end of the forecast period, the market is projected to attain a value of USD 44.2 billion by 2033. This substantial growth is primarily driven by the accelerating adoption of artificial intelligence technologies across online retail platforms, as businesses seek to enhance customer experiences, streamline operations, and optimize decision-making processes.

The rapid expansion of the AI in E-Commerce market is underpinned by several critical growth factors. Foremost among these is the increasing consumer demand for personalized shopping experiences. Retailers are leveraging AI-driven algorithms to analyze vast datasets, enabling them to deliver tailored product recommendations, dynamic pricing, and targeted marketing campaigns. The proliferation of digital touchpoints—ranging from mobile apps to voice assistants—has further amplified the need for intelligent automation, making AI an indispensable tool for e-commerce businesses aiming to boost conversion rates and foster customer loyalty. Additionally, the integration of AI-powered chatbots and virtual assistants is revolutionizing customer service by providing real-time, 24/7 support, thereby reducing operational costs and improving customer satisfaction.

Another significant driver propelling the growth of the AI in E-Commerce market is the ongoing digital transformation across the retail sector. As e-commerce platforms contend with rising competition and shifting consumer behaviors, AI technologies offer a competitive edge by automating inventory management, optimizing supply chains, and detecting fraudulent activities. Retailers are increasingly investing in advanced analytics, computer vision, and natural language processing to enhance operational efficiency and mitigate risks. The adoption of cloud-based AI solutions has also lowered entry barriers for small and medium-sized enterprises, enabling them to harness sophisticated tools without substantial upfront investments in infrastructure.

Moreover, the global expansion of e-commerce, particularly in emerging markets, is fueling the demand for AI-driven solutions. The surge in online transactions, coupled with the rise of omnichannel retail strategies, has created a complex ecosystem that necessitates intelligent automation and data-driven insights. AI is facilitating seamless integration across various sales channels, improving inventory visibility, and enabling predictive analytics for demand forecasting. As regulatory frameworks around data privacy and security continue to evolve, e-commerce companies are prioritizing investments in AI technologies that enhance compliance and build consumer trust.

From a regional perspective, North America currently leads the AI in E-Commerce market, accounting for the largest share in 2024. This dominance is attributed to the presence of major technology providers, high consumer adoption rates, and significant investments in research and development. However, Asia Pacific is poised to witness the fastest growth during the forecast period, driven by rapid digitalization, increasing internet penetration, and the emergence of tech-savvy consumers in countries such as China, India, and Southeast Asia. Europe is also experiencing steady growth, supported by robust e-commerce infrastructure and regulatory support for digital innovation. Latin America and the Middle East & Africa are gradually catching up, as local retailers embrace AI to address unique market challenges and capitalize on new opportunities.

Component Analysis

The AI in E-Commerce market is segmented by component into software, services, and hardware, each playing a pivotal role in the ecosystem. The software segment dominates the market, as AI-powered platforms and applications are crucial for delivering personalized recommendations, automating customer interaction

According to a global 2022 survey, Indian consumers appreciated customer service via chatbots the most, with ** percent of them finding it useful when shopping on mobile devices. Respondents from the United Arab Emirates and Indonesia followed with ** percent each, while ** percent of Mexican shoppers had the same opinion. Scandinavian respondents showed the biggest skepticism regarding the use of this AI tool in mobile shopping, as only * percent of consumers in both Denmark and Sweden valued chatbots. Chatbots drive conversational commerce By simulating natural language, chatbots go under so-called conversational commerce, a shopping channel expected to generate increasing revenue in the upcoming years. All players, from marketplaces to online e-commerce brands, implemented chatbots to automate pre-and post-sale services. In Europe, one in five direct-to-consumer (D2C) e-commerce companies planned to invest in Artificial Intelligence (AI) and chatbots, a survey from 2022 revealed. Messaging apps in conversational commerce Even more than chatbots, established messaging apps such as WhatsApp or chat apps connected to social media are the main tools for conversational commerce. In Southeast Asia, ** percent of online consumers used Facebook for this type of shopping in 2022. Besides product recommendations, messaging apps are used for information on delivery as an alternative to email or SMS. In 2021, WhatsApp remained the*********** preferred channel for delivery notifications in Europe.

The global social messaging chatbot market is experiencing robust growth, driven by the increasing adoption of messaging apps and the rising demand for automated customer service and engagement solutions across various sectors. The market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 25% from 2025 to 2033, reaching approximately $70 billion by 2033. This expansion is fueled by several key factors. Firstly, businesses across sectors like BFSI, retail, and e-commerce are increasingly leveraging chatbots to enhance customer experience, streamline operations, and reduce operational costs. Secondly, advancements in natural language processing (NLP) and artificial intelligence (AI) are leading to more sophisticated and human-like chatbot interactions, improving user satisfaction and engagement. Finally, the growing preference for self-service options among consumers contributes significantly to the market's growth trajectory. The market is segmented by application (BFSI, Retail & e-commerce, IT & Telecom, Government, Travel & Hospitality, Others) and type (Software, Services, Chatbot Platforms), providing diverse avenues for growth depending on specific technological advancements and industry adoption rates. The competitive landscape is marked by a mix of established technology giants like Google, IBM, and AWS, alongside agile startups specializing in chatbot development and deployment. This dynamic competition stimulates innovation and ensures continuous improvement in chatbot capabilities. While the market demonstrates significant growth potential, certain restraints exist. These include concerns about data privacy and security, the need for continuous improvement in NLP to address nuanced conversational needs, and the challenge of integrating chatbots seamlessly into existing business workflows. However, ongoing technological advancements and increasing user acceptance are expected to mitigate these challenges over the forecast period. The regional distribution is expected to be heavily weighted towards North America and Europe initially, reflecting higher technological adoption rates in these regions. However, rapid growth is anticipated in Asia-Pacific, particularly in India and China, driven by burgeoning digital economies and increasing smartphone penetration. This geographic diversification will play a vital role in the overall market expansion.

The global AI-based chatbot market is projected to be valued at $1.1 billion in 2024, driven by factors such as increasing consumer awareness and the rising prevalence of industry-specific trends. The market is expected to grow at a CAGR of 18.6%, reaching approximately $6.0 billion by 2034.

Categorisation of computational and non-computational characteristics of reviewed chatbot research work

The Conversational AI market for retail and e-commerce is experiencing rapid growth, driven by increasing consumer demand for personalized and efficient customer service experiences. This is fueled by the rising adoption of chatbots, virtual assistants (IVAs), and other conversational AI technologies across large enterprises and SMEs. The market's expansion is further propelled by advancements in natural language processing (NLP) and machine learning (ML), enabling more human-like interactions and improved customer understanding. While precise figures for market size aren't available from the provided data, a reasonable estimation based on industry reports and the stated CAGR (let's assume a CAGR of 25% for illustrative purposes, this should be replaced with the actual CAGR from the source data) suggests significant expansion. If we assume a 2025 market size of $5 billion (this needs to be replaced with the actual value from the provided data), the market would reach approximately $10 billion by 2028, growing to over $20 billion by 2033 based on the assumed 25% CAGR. The market is segmented by solution type (IVA, Chatbots) and application (large enterprises, SMEs), with significant opportunities across various geographical regions. North America and Europe currently dominate, but strong growth is anticipated in Asia-Pacific driven by expanding e-commerce markets and increasing technology adoption. The continued success of conversational AI in retail and e-commerce hinges on factors like improved accuracy in natural language understanding, seamless integration across various platforms, and enhanced security and data privacy measures. Challenges include the need for ongoing training and maintenance of AI models, concerns regarding bias in algorithms, and the need to effectively manage customer expectations regarding AI capabilities. Companies such as Google, Microsoft, IBM, and Amazon Web Services are at the forefront of innovation, offering a range of solutions to meet the evolving needs of businesses in this dynamic market. Competitive landscape analysis highlights strategic partnerships, acquisitions, and technological advancements as key drivers shaping the market's future. The focus will remain on improving personalization, enhancing customer experience, and streamlining operational efficiency through AI-powered conversational interfaces. This will create numerous opportunities for both technology providers and retail businesses alike.