Social commerce has become increasingly significant in the e-commerce sector. In 2025, sales through social networks accounted for an estimated ***** percent of total online sales. This figure is expected to continue growing in the coming years. Who has grown a liking for this channel? The term "social commerce" is gaining traction worldwide. In 2024, global revenues generated through social media platforms were forecast to reach nearly *** billion U.S. dollars, an increase of roughly ** percent compared to the previous year. However, some countries have embraced this sales channel more vigorously than others. Leading the way in social shopping are Thailand, Colombia, and China. In 2023, approximately **** out of ten internet users in these countries made purchases through social networks. The future of shopping is live Live commerce has grown in popularity in recent years. Its prevalence is only expected to increase as companies utilize livestreaming technologies more and more for promotional and marketing purposes. Digital shoppers benefit from live commerce because it offers attractive discounts as well as inspiration and ideas. In 2022, Facebook was the leading social network platform where internet users purchased products during live streaming events. As with social commerce, Asian countries have paved the way for this highly interactive shopping experience. In 2023, over ***** in ten consumers engaged in live shopping in China, India, Thailand, and United Arab Emirates.

An October 2020 survey among e-commerce decision makers in North America and Europe revealed that only 12 percent of e-commerce companies planned to introduce direct sales through social media platforms in 2021. Up to 30 percent of these businesses were already selling via social media at that time, while another 33 percent of respondents said they were still evaluating whether to adopt this strategy or not.

In the first half of 2024, roughly *** percent of online sales in beauty came from social commerce in North America. Of this, TikTok Shop contributed to the largest market share with around *** percent, followed by Temu and eBay with *** and *** percent respectively.

According to Cognitive Market Research, the global Social Commerce Market size was USD 769485.2 million in 2024. It will expand at a compound annual growth rate (CAGR) of 32.20% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 307794.08 million in 2024 and will grow at a compound annual growth rate (CAGR) of 30.4% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 230845.56 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 176981.60 million in 2024 and will grow at a compound annual growth rate (CAGR) of 34.2% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 38474.26 million in 2024 and will grow at a compound annual growth rate (CAGR) of 31.6% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 15389.70 million in 2024 and will grow at a compound annual growth rate (CAGR) of 31.9% from 2024 to 2031.
The business to consumer (B2C) held the highest Social Commerce Market revenue share in 2024.

Market Dynamics of Social Commerce Market

Key Drivers for Social Commerce Market

The rise of social media is driving the growth of social commerce: The growth of social commerce is heavily influenced by the rise of social media and its increased usage on mobile devices. Social media platforms such as Facebook, Instagram, TikTok and WhatsApp have become major hubs for online shoppers. Customers are more likely to find and buy products directly from social media platforms than from traditional e-commerce websites since they spend more time on these channels.

For instance,

 5.24 billion use social media worldwide, as of January, 2025.Facebook remains to be the leading social media platform with over 3 billion monthly active users, followed by YouTube with 2.5 billion and Instagram with 2 billion monthly active users.
90% of consumers rely on social media to keep up with trends and cultural moments and nearly half of them interact with brands more often on social media platforms. 

(Source: https://backlinko.com/social-media-users)

https://sproutsocial.com/insights/social-media-statistics/#social-media-usage-statistics)

Advancements in Technology to Propel Market Growth: The Social Commerce Market has witnessed steady growth, driven by advancements in technology. Mobile technology has advanced significantly over the last ten years, and smartphones are now an essential part of people's everyday lives. Users are increasingly choosing to shop straight from their smartphones because to improved smartphone capabilities and internet connectivity, which has expanded mobile commerce. Additionally, more people are using smartphones due to rising disposable incomes, which ultimately enhances the social commerce market value environment.

Key Restraint for the Social Commerce Market

Growing concerns around data privacy restrict market growth: Concerns regarding privacy are hindering the expansion of social commerce, as individuals are reluctant to disclose financial or personal information on various platforms. The apprehension surrounding data breaches and potential misuse diminishes trust and affects transaction volumes. It is imperative for companies to implement secure and transparent practices in order to maintain user confidence and adhere to the growing data protection regulations globally.

Key Trends for the Social Commerce Market

The Emergence of Live Shopping and Influencer Commerce: Live shopping and promotions led by influencers are revolutionizing social media platforms into dynamic marketplaces. Consumers are increasingly placing their trust in the product reviews and recommendations provided by creators, which enhances both engagement and conversion rates. This phenomenon is particularly evident on TikTok and Instagram, where influencers conduct interactive shopping events that are directly connected to in-app purchasing.

AI-Enhanced Personalization and Intelligent Chatbots: Social commerce platforms are utilizing artificial intelligence to offer tailored product suggestions and efficient customer support. Intelligent chatbots deliver immediate assistance, thereby enhan...

Discover the explosive growth of the social commerce market, projected to reach $8.6 billion by 2033 at a CAGR of 28.53%! This in-depth analysis explores key drivers, trends, and regional variations across platforms like Amazon, Facebook, and TikTok. Learn about B2C, B2B, and C2C models in social selling. Recent developments include: November 2023: Amazon announced a partnership with Meta (Facebook’s parent company) to revolutionize social commerce. This collaboration aims to integrate Amazon’s e-commerce platform with Meta’s social media platform, providing shoppers with a seamless purchase experience and opening new opportunities for targeted advertising., April 2023: Amazon and Pinterest partnered to deliver third-party ads on Pinterest’s platform. The partnership aimed to make every pin shoppable by integrating Amazon’s e-commerce platform with Pinterest’s social media platform., December 2022: Amazon announced the release of Inspire, a new short-form photo and video feed that lets users browse ideas and goods while shopping from content made by brands, influencers, and other users.. Key drivers for this market are: Growing Number of Social Media Platforms, Shift in Consumer Preferences Toward Online Purchase. Potential restraints include: Privacy Concerns Over Gathering and Using Personal Data, Intense Competition in the Social Commerce Space. Notable trends are: Growing demand for business-to-consumer (B2C) social commerce is driving the market growth.

This dataset provides a comprehensive collection of consumer behavior data that can be used for various market research and statistical analyses. It includes information on purchasing patterns, demographics, product preferences, customer satisfaction, and more, making it ideal for market segmentation, predictive modeling, and understanding customer decision-making processes.

The dataset is designed to help researchers, data scientists, and marketers gain insights into consumer purchasing behavior across a wide range of categories. By analyzing this dataset, users can identify key trends, segment customers, and make data-driven decisions to improve product offerings, marketing strategies, and customer engagement.

Key Features: Customer Demographics: Understand age, income, gender, and education level for better segmentation and targeted marketing. Purchase Behavior: Includes purchase amount, frequency, category, and channel preferences to assess spending patterns. Customer Loyalty: Features like brand loyalty, engagement with ads, and loyalty program membership provide insights into long-term customer retention. Product Feedback: Customer ratings and satisfaction levels allow for analysis of product quality and customer sentiment. Decision-Making: Time spent on product research, time to decision, and purchase intent reflect how customers make purchasing decisions. Influences on Purchase: Factors such as social media influence, discount sensitivity, and return rates are included to analyze how external factors affect purchasing behavior.

Columns Overview: Customer_ID: Unique identifier for each customer. Age: Customer's age (integer). Gender: Customer's gender (categorical: Male, Female, Non-binary, Other). Income_Level: Customer's income level (categorical: Low, Middle, High). Marital_Status: Customer's marital status (categorical: Single, Married, Divorced, Widowed). Education_Level: Highest level of education completed (categorical: High School, Bachelor's, Master's, Doctorate). Occupation: Customer's occupation (categorical: Various job titles). Location: Customer's location (city, region, or country). Purchase_Category: Category of purchased products (e.g., Electronics, Clothing, Groceries). Purchase_Amount: Amount spent during the purchase (decimal). Frequency_of_Purchase: Number of purchases made per month (integer). Purchase_Channel: The purchase method (categorical: Online, In-Store, Mixed). Brand_Loyalty: Loyalty to brands (1-5 scale). Product_Rating: Rating given by the customer to a purchased product (1-5 scale). Time_Spent_on_Product_Research: Time spent researching a product (integer, hours or minutes). Social_Media_Influence: Influence of social media on purchasing decision (categorical: High, Medium, Low, None). Discount_Sensitivity: Sensitivity to discounts (categorical: Very Sensitive, Somewhat Sensitive, Not Sensitive). Return_Rate: Percentage of products returned (decimal). Customer_Satisfaction: Overall satisfaction with the purchase (1-10 scale). Engagement_with_Ads: Engagement level with advertisements (categorical: High, Medium, Low, None). Device_Used_for_Shopping: Device used for shopping (categorical: Smartphone, Desktop, Tablet). Payment_Method: Method of payment used for the purchase (categorical: Credit Card, Debit Card, PayPal, Cash, Other). Time_of_Purchase: Timestamp of when the purchase was made (date/time). Discount_Used: Whether the customer used a discount (Boolean: True/False). Customer_Loyalty_Program_Member: Whether the customer is part of a loyalty program (Boolean: True/False). Purchase_Intent: The intent behind the purchase (categorical: Impulsive, Planned, Need-based, Wants-based). Shipping_Preference: Shipping preference (categorical: Standard, Express, No Preference). Payment_Frequency: Frequency of payment (categorical: One-time, Subscription, Installments). Time_to_Decision: Time taken from consideration to actual purchase (in days).

Use Cases: Market Segmentation: Segment customers based on demographics, preferences, and behavior. Predictive Analytics: Use data to predict customer spending habits, loyalty, and product preferences. Customer Profiling: Build detailed profiles of different consumer segments based on purchase behavior, social media influence, and decision-making patterns. Retail and E-commerce Insights: Analyze purchase channels, payment methods, and shipping preferences to optimize marketing and sales strategies.

Target Audience: Data scientists and analysts looking for consumer behavior data. Marketers interested in improving customer segmentation and targeting. Researchers are exploring factors influencing consumer decisions and preferences. Companies aiming to improve customer experience and increase sales through data-driven decisions.

This dataset is available in CSV format for easy integration into data analysis tools and platforms such as Python, R, and Excel.

United Kingdom E Commerce: Social Networks: 250-999 Employees data was reported at 78.100 % in 2016. This records an increase from the previous number of 75.900 % for 2015. United Kingdom E Commerce: Social Networks: 250-999 Employees data is updated yearly, averaging 71.700 % from Dec 2012 (Median) to 2016, with 5 observations. The data reached an all-time high of 78.100 % in 2016 and a record low of 63.400 % in 2012. United Kingdom E Commerce: Social Networks: 250-999 Employees data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.S039: E Commerce: Proportion of Businesses Using Social Media: By Size of Business.

In a 2025 survey, nearly ***percent of global consumers rated Facebook as the social media platform delivering the best experience for social commerce. Instagram and TikTok ranked second, with ***percent.

United Kingdom E Commerce: Social Networks: Other Services data was reported at 65.500 % in 2016. This records an increase from the previous number of 58.400 % for 2015. United Kingdom E Commerce: Social Networks: Other Services data is updated yearly, averaging 58.400 % from Dec 2012 (Median) to 2016, with 5 observations. The data reached an all-time high of 65.500 % in 2016 and a record low of 48.400 % in 2013. United Kingdom E Commerce: Social Networks: Other Services data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.S040: E Commerce: Proportion of Businesses Using Social Media: By Industry.

United Kingdom E Commerce: Social Networks: 1000+ Employees data was reported at 90.300 % in 2016. This records an increase from the previous number of 85.200 % for 2015. United Kingdom E Commerce: Social Networks: 1000+ Employees data is updated yearly, averaging 82.200 % from Dec 2012 (Median) to 2016, with 5 observations. The data reached an all-time high of 90.300 % in 2016 and a record low of 77.300 % in 2013. United Kingdom E Commerce: Social Networks: 1000+ Employees data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s UK – Table UK.S039: E Commerce: Proportion of Businesses Using Social Media: By Size of Business.

United Kingdom E Commerce: Social Networks data was reported at 60.300 % in 2016. This records an increase from the previous number of 56.500 % for 2015. United Kingdom E Commerce: Social Networks data is updated yearly, averaging 51.200 % from Dec 2012 (Median) to 2016, with 5 observations. The data reached an all-time high of 60.300 % in 2016 and a record low of 42.200 % in 2013. United Kingdom E Commerce: Social Networks data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.S040: E Commerce: Proportion of Businesses Using Social Media: By Industry.

United Kingdom E Commerce: Social Networks: Utilities data was reported at 44.600 % in 2016. This records a decrease from the previous number of 50.000 % for 2015. United Kingdom E Commerce: Social Networks: Utilities data is updated yearly, averaging 39.400 % from Dec 2012 (Median) to 2016, with 5 observations. The data reached an all-time high of 50.000 % in 2015 and a record low of 26.300 % in 2012. United Kingdom E Commerce: Social Networks: Utilities data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.S040: E Commerce: Proportion of Businesses Using Social Media: By Industry.

Citation-worthy statistics and data points related to Social eCommerce & Shoppable Live Streams. This dataset provides key metrics and statistical information.

Metadata

Title: E-commerce Customer Engagement and Demographics Dataset

Description: This dataset contains comprehensive details about customer engagement, demographics, and purchasing behavior from an e-commerce platform. It consists of 10,000 entries with 23 features, covering various aspects of customer interaction, including registration details, engagement rates, conversion rates, and satisfaction scores.

Dataset Columns: 1. CustomerID: Unique identifier for each customer (492 missing values). 2. RegistrationDate: Date when the customer registered (496 missing values). 3. Age: Age of the customer (515 missing values). 4. Gender: Gender of the customer (2,612 missing values). 5. IncomeLevel: Income level of the customer (2,503 missing values). 6. Country: Country of residence (493 missing values). 7. City: City of residence (483 missing values). 8. TotalPurchases: Total number of purchases made by the customer (530 missing values). 9. AverageOrderValue: Average value of orders placed by the customer (519 missing values). 10. CustomerLifetimeValue: Estimated lifetime value of the customer (493 missing values). 11. FavoriteCategory: Customer's favorite product category (1,589 missing values). 12. SecondFavoriteCategory: Customer's second favorite product category (1,550 missing values). 13. EmailEngagementRate: Engagement rate of the customer with email marketing campaigns (476 missing values). 14. SocialMediaEngagementRate: Engagement rate of the customer on social media platforms (528 missing values). 15. MobileAppUsage: Frequency of mobile app usage by the customer (2,457 missing values). 16. CustomerServiceInteractions: Number of interactions with customer service (518 missing values). 17. AverageSatisfactionScore: Average satisfaction score of the customer (496 missing values). 18. EmailConversionRate: Conversion rate from email marketing (523 missing values). 19. SocialMediaConversionRate: Conversion rate from social media campaigns (494 missing values). 20. SearchEngineConversionRate: Conversion rate from search engine marketing (505 missing values). 21. RepeatCustomer: Whether the customer is a repeat customer (475 missing values). 22. PremiumMember: Whether the customer is a premium member (494 missing values). 23. HasReturnedItems: Whether the customer has returned items (529 missing values).

Additional Information: - Number of Duplicate Rows: The dataset contains some duplicate rows that may need to be cleaned. - Total Number of Entries: 10,000. - Data Types: The dataset includes both numerical and categorical data, with a significant number of missing values across multiple columns.

What Can Be Done with This Data: - Customer Segmentation: Group customers based on demographics, purchasing behavior, and engagement metrics. - Churn Prediction: Build models to predict customer churn based on interaction and satisfaction scores. - Lifetime Value Prediction: Estimate customer lifetime value using demographic and purchase data. - Engagement Analysis: Explore the effectiveness of email and social media campaigns on customer conversion rates. - Satisfaction Analysis: Investigate the factors that influence customer satisfaction and loyalty. - Market Segmentation: Identify key market segments based on country, income level, and purchasing patterns. - Behavioral Analysis: Analyze how different demographics engage with the platform and respond to marketing efforts.

Snapshot img

Digital Commerce Market Size 2024-2028

The digital commerce market size is forecast to increase by USD 3,634 billion at a CAGR of 16.6% between 2023 and 2028. The market is experiencing significant growth, driven by vigorous internet penetration and advancements in technological digital commerce platforms. The increasing use of smartphones and the convenience they offer for online shopping have contributed to the market's expansion. Additionally, the trend towards contactless transactions and social distancing during the COVID-19 pandemic has accelerated the shift towards digital commerce. Robotics and advanced technologies like smartphones and laptops facilitate seamless transactions. However, challenges persist, including growing data privacy and security concerns, which require strong security measures and transparency from digital commerce platforms to maintain consumer trust. The market's future growth is expected to be fueled by continued technological advancements and the increasing adoption of digital commerce solutions by businesses of all sizes.

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The market refers to the buying and selling of goods and services through an electronic network, specifically the Internet. This market encompasses various types of transactions, including Business-to-Consumer (B2C), Business-to-Business (B2B), Consumer-to-Business (C2B), and Consumer-to-Consumer (C2C). The market is driven by the increasing use of the Internet in homes and offices, and the widespread adoption of computers, tablets, cell phones, and broadband connections. E-commerce sector players require digital marketing expertise to establish an online presence and attract customers. Retailers in industries such as industrial and logistics are increasingly leveraging e-commerce to reach a broader audience. Women and social networking sites also play a significant role in driving e-business growth. Overall, the market is transforming traditional business models and offering new opportunities for businesses and consumers alike.

Market Segmentation

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Business Segment

  Business to business
  Business to consumer


Geography

  APAC

    China
    Japan


  North America

    US


  Europe

    Germany
    UK


  South America



  Middle East and Africa

By Business Segment Insights

The business to business segment is estimated to witness significant growth during the forecast period. The market is experiencing significant growth due to the proliferation of smart phones, multiple payment modes, and cross-border e-commerce. CXOs are increasingly focusing on digital commerce visibility to expand their businesses, leveraging AI, machine learning, and in-memory technologies. Small and medium-sized businesses are embracing SaaS delivery models to enhance their online presence and reach a wider customer base. Cyber security issues and online frauds are major concerns, necessitating the implementation of advanced security measures such as block chain and memorandums of understanding with logistics, warehouse, and transportation service providers. Online sales are no longer limited to homes and offices, with the rise of mobile commerce, social commerce, and local commerce.

Additionally, digital marketing expertise is essential for retailers to effectively engage with consumers through web contacts, social media, and mobile payments. The e-commerce sector is transforming rapidly, offering immense opportunities for innovation and growth.

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The business to business segment accounted for USD 1,294.40 billion in 2018 and showed a gradual increase during the forecast period.

Regional Insights

APAC is estimated to contribute 54% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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Digital commerce refers to the buying and selling of goods and services through an electronic network, specifically the Internet. This encompasses various business models such as business-to-consumer (B2C), business-to-business (B2B), consumer-to-business (C2B), and consumer-to-consumer (C2C). E-commerce and e-business are interchangeable terms used to describe this phenomenon, with e-tail being a specific term for businesses that sell products online. Digital commerce software and inventory management solutions facilitate the process, enabling retailers to manage sales and marketing efforts across multiple channels. The automotive segment, manufacturing, retail h

Discover the booming social commerce market! Explore key trends, growth drivers, and leading players like Meta, TikTok, and more. This in-depth analysis projects a 25% CAGR through 2033, revealing lucrative investment opportunities. Learn how social media is transforming e-commerce.

United Kingdom E Commerce: Social Media User (SM) data was reported at 63.100 % in 2016. This records an increase from the previous number of 58.500 % for 2015. United Kingdom E Commerce: Social Media User (SM) data is updated yearly, averaging 53.700 % from Dec 2012 (Median) to 2016, with 5 observations. The data reached an all-time high of 63.100 % in 2016 and a record low of 42.800 % in 2012. United Kingdom E Commerce: Social Media User (SM) data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.S039: E Commerce: Proportion of Businesses Using Social Media: By Size of Business.

United Kingdom E Commerce: Social Networks: Construction data was reported at 41.200 % in 2016. This records an increase from the previous number of 36.100 % for 2015. United Kingdom E Commerce: Social Networks: Construction data is updated yearly, averaging 27.100 % from Dec 2012 (Median) to 2016, with 5 observations. The data reached an all-time high of 41.200 % in 2016 and a record low of 18.600 % in 2012. United Kingdom E Commerce: Social Networks: Construction data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.S040: E Commerce: Proportion of Businesses Using Social Media: By Industry.

Context

Typically e-commerce datasets are proprietary and consequently hard to find among publicly available data. However, The UCI Machine Learning Repository has made this dataset containing actual transactions from 2010 and 2011. The dataset is maintained on their site, where it can be found by the title "Online Retail".

Content

"This is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail.The company mainly sells unique all-occasion gifts. Many customers of the company are wholesalers."

Acknowledgements

Per the UCI Machine Learning Repository, this data was made available by Dr Daqing Chen, Director: Public Analytics group. chend '@' lsbu.ac.uk, School of Engineering, London South Bank University, London SE1 0AA, UK.

Image from stocksnap.io.

Inspiration

Analyses for this dataset could include time series, clustering, classification and more.

United Kingdom E Commerce: Social Networks: Accommodation & Food Services data was reported at 72.300 % in 2016. This records a decrease from the previous number of 75.000 % for 2015. United Kingdom E Commerce: Social Networks: Accommodation & Food Services data is updated yearly, averaging 66.800 % from Dec 2012 (Median) to 2016, with 5 observations. The data reached an all-time high of 75.000 % in 2015 and a record low of 44.700 % in 2013. United Kingdom E Commerce: Social Networks: Accommodation & Food Services data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.S040: E Commerce: Proportion of Businesses Using Social Media: By Industry.