During the fourth quarter of 2024, communication platform WhatsApp Business had over 764.38 million monthly active users (MAU). This represents an increase of over six percent compared to the beginning of the year, when the B2C communication platform had approximately 907 million MAU. Launched in 2018, WhatsApp Business allows users to connect with companies' customer service representatives using the WhatsApp instant chat ecosystem.

In 2024, global users amassed approximately 311 million downloads of WhatsApp Business, up by three percent compared to the previous year. WhatsApp Business was launched in 2018, and it allows users to connect instantly with the company's customer service representatives or interact with small business owners. The platform offers numerous integrations tailor-made for businesses, like the possibility to automate chat messages.

At the heart of countless morning check-ins, urgent family updates, and late-night laughs lies a green icon we all recognize, WhatsApp. What started in 2009 as a simple status update tool has evolved into a global communication powerhouse. In 2025, it’s not just a messaging app; it's where billions live...

With over *** million downloads on Android devices, most WhatsApp Business downloads as of May 2025 came from users in India. Ranking second out of the ** countries analyzed was Pakistan, with approximately *** million lifetime downloads as of the examined period.

In the fourth quarter of 2024, communication platform WhatsApp Business had over 554.7 million daily active users (DAU). WhatsApp Business is a B2C communication platform launched in 2018. WhatsApp Business allows users to send instant messages to companies using WhatsApp environment, as users do not need to download an additional mobile app to receive assistance on products and orders.

Dataset Overview: This meticulously curated dataset amalgamates user reviews of the WhatsApp Business application from the App Stores of three distinct nations: Australia, Canada, and the United States. Encompassing a wealth of insights, the dataset is an invaluable resource for data scientists aiming to delve into consumer feedback, analyze sentiment trends, and extract meaningful patterns relevant to business strategies and app improvements. The dataset brings together a comprehensive collection of user interactions and sentiments, shedding light on various facets of the user experience across different geographic locales. With data ethically mined and responsibly aggregated, it ensures a respectful approach towards user privacy while offering rich analytical opportunities.

Data Science Applications: This dataset serves as a fertile ground for a multitude of data science endeavors including sentiment analysis, trend forecasting, natural language processing, and customer feedback analytics. Researchers and practitioners can employ this dataset to harness predictive insights, gauge app performance, and refine user engagement strategies.

Column Descriptors: - ID: Unique identifier for each review entry. - Date: Timestamp of the review. - UserName (Hashed): Anonymized username of the reviewer. - UserUrl (Hashed): Anonymized URL of the user's review profile. - Version: App version the review pertains to. - Score: User-provided rating for the app. - Title: Title of the review. - Text: Body text of the review, providing detailed feedback. - URL: URL of the review on the App Store (anonymized if containing personal identifiers). - Country: The country from which the review was posted. - AppId: Unique identifier for the WhatsApp Business application.

Ethical Considerations: In the assembly of this dataset, utmost care was taken to ensure the ethical sourcing of data, with a keen focus on maintaining the anonymity of the users. Personal identifiers such as usernames and user URLs have been hashed to uphold privacy and confidentiality. SHA-256 was used.

Acknowledgements: Gratitude is extended to the platforms that facilitated the aggregation of this data, acknowledging their pivotal role in fostering a space where user feedback can thrive and inform better business and technological outcomes.

Introduction

WhatsApp Statistics: WhatsApp is an integral part of our daily lives, connecting us with friends, family, and businesses. The app boasts billions of users and offers features such as text, voice, and video messaging, as well as voice and video calling. Additionally, users can share various forms of content, including images, documents, and user locations.

This report contains current trends and analyses from various insights. It aims to provide statistical analyses to effectively guide you. Let's explore some intriguing statistics to understand the widespread use of WhatsApp.

As of June 2023, WhatsApp Business reported having over 200 million monthly active users (MAU) worldwide. Launched in January 2018, WhatsApp Business is a communication app tailor-made for small businesses to connect with their customers and communicate seamlessly. In July 2020, the app counted around 50 million MAU worldwide.

With over 14.59 thousand dollars in revenue generated worldwide as of August 2025, most WhatsApp Business lifetime earnings came from Brazil, with around 3.4 million U.S. dollars. Of the ten leading countries in IAP revenue, India ranked second, with approximately 1.28 million U.S. dollars generated in revenue. As of May 2025, the app was most popular in India and Pakistan, with 531.2 million downloads and 160.1 million in the respective countries, only then followed by Indonesia and Brazil, with 151.6 million and 90.7 million downloads each.

WhatsApp Business API Enablement Market Outlook

According to our latest research, the global WhatsApp Business API Enablement market size reached USD 2.1 billion in 2024, reflecting robust adoption across industries. The market is experiencing a strong growth trajectory with a CAGR of 21.7% from 2025 to 2033. By 2033, the market is forecasted to attain a value of USD 14.6 billion. This impressive expansion is primarily driven by the increased demand for real-time customer engagement, automation in business communications, and the growing penetration of mobile messaging platforms in both emerging and developed economies.

A significant growth factor fueling the WhatsApp Business API Enablement market is the intensifying need for businesses to deliver seamless, personalized, and instant communication to customers. As enterprises across sectors such as retail, BFSI, healthcare, and travel increasingly shift towards digital transformation, the WhatsApp Business API has emerged as a critical tool for automating interactions, streamlining customer support, and driving conversational commerce. The API’s capability to integrate with CRM systems, chatbots, and other business tools enables organizations to provide round-the-clock support, send timely notifications, and execute targeted marketing campaigns, all of which contribute to enhanced customer satisfaction and loyalty. With WhatsApp’s massive active user base, businesses are leveraging the API to tap into new customer segments and expand their reach globally.

Another pivotal driver is the escalating adoption of cloud-based deployment models, which offer scalability, flexibility, and cost efficiency. Cloud deployment enables even small and medium-sized enterprises (SMEs) to harness the power of the WhatsApp Business API without significant upfront investments in IT infrastructure. This democratization of access to advanced communication tools has led to a surge in API enablement among SMEs, allowing them to compete effectively with larger enterprises. Furthermore, the integration of AI-powered chatbots and analytics solutions with the WhatsApp Business API is enabling organizations to gain actionable insights into customer behavior, optimize workflows, and deliver hyper-personalized experiences, further propelling market growth.

Regulatory support and evolving data privacy frameworks are also shaping the WhatsApp Business API Enablement market. Governments and industry bodies in regions like Europe and North America are implementing stringent data protection regulations, prompting businesses to adopt secure and compliant communication solutions. The WhatsApp Business API, with its end-to-end encryption and robust security features, is increasingly being chosen by organizations seeking to ensure compliance while maintaining high standards of customer engagement. Additionally, the API’s compatibility with various enterprise applications and its ability to support multilingual communication are making it a preferred choice for global businesses looking to cater to diverse customer bases and expand internationally.

Regionally, the Asia Pacific market is witnessing the fastest growth, driven by the rapid digitization of businesses, increasing smartphone penetration, and the widespread popularity of WhatsApp as a primary communication channel. North America and Europe continue to dominate in terms of market share due to early adoption of API-driven business communication and the presence of tech-savvy enterprises. Meanwhile, Latin America and the Middle East & Africa are emerging as promising markets, bolstered by expanding internet connectivity and growing investments in digital customer engagement solutions. Overall, the WhatsApp Business API Enablement market is poised for sustained expansion, with regional dynamics and technological advancements shaping its evolution over the forecast period.

Component Analysis

The WhatsApp Business API Enablement market by component is segmented into Solution</b&g

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In 2023, WhatsApp Business was estimated to have an average revenue per user (ARPU) of approximately **** U.S. dollars worldwide. Australia and Oceania was estimated to be the global region with the highest ARPU for WhatsApp Business, with **** U.S. dollars in revenues per user on the platform. In 2023, it is estimated that WhatsApp Business generated around over ***** million U.S. dollars in revenues worldwide, with Asia and Europe generating the largest share of revenues.WhatsApp Business was launched in 2018 and is available to download for small businesses and companies. Regular WhatsApp users do not need an additional app, but can connect instantly with company representatives or automated chatbots from their regular app interface.

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Abstract

The proliferation of mis- and disinformation threatens to erode the credibility of public institutions and limit their capacity to implement policies that enhance public well-being. While misinformation represents an urgent global challenge, relatively little research has examined solutions in low- and middle-income countries. We experimentally test the impact of a novel WhatsApp chatbot game prebunking inoculation intervention in Jordan to boost capacity to identify common misinformation techniques and reduce the likelihood of sharing misleading headlines with others?effectively ‘inoculating’ them against misinformation. A sample of 2,851 participants was recruited online and randomly assigned to five study arms: (1) comprehensive game-based inoculation, (2) brief game-based inoculation that highlighted examples of only misinformation, (3) infographics-based inoculation, (4) exposure to placebo infographics unrelated to misinformation, and (5) pure control. To evaluate the impact of our intervention, we assess two main outcomes: (i) ability to accurately discern headlines using misinformation techniques and headlines that do not use misinformation techniques, and (ii) discernment in sharing the two types of headlines.

Kind of data

Sample survey data [ssd]

Sampling procedure

We conducted this study between October 27, 2022 and November 23, 2022. Participants were recruited through Facebook advertisements targeting users aged 18 years or older and located in Jordan with WhatsApp installed. The advertisements marketed our chatbot-based game under the title “Find the Fake”, inviting people to play a challenge related to the spread of misinformation online for a chance to win 70 Jordanian Dinar (roughly equivalent to US$ 100).

After participants clicked the ads, they were automatically directed to a WhatsApp business line, and the chatbot began after participants sent an initial message to the line. In response to the first message sent by participants, the chatbot replied with a message briefly describing the game and participants were asked if they wanted to continue. Participants who opted in were then provided additional background information about the study and contact information for the researchers, completing the informed consent protocol. For more information, please find our Working Paper.

A total of 2,851 participants completed the study. Of them, 63% identified as male and 33% as female; 49% reported having completed secondary education (3% with no education, 12% with primary, and 3% with tertiary education); 53% reported being between the ages of 18 and 29, 25% in their 30s, 13% in their 40s, and 5% over the age of 50. Finally, 85% reported being vaccinated for COVID-19, 5% unvaccinated but willing to vaccinate, and 5% unvaccinated and unwilling to vaccinate. None of the treatment arms reported significant differences in demographics and vaccination status compared to the control group. For more information, please find our Working Paper at https://hdl.handle.net/10986/42216.

Mode of data collection

Internet [int]

Research instrument

Judgements of Misinformation Adapted from Roozenbeek et al. (2022), participants were presented with six headlines: three using misinformation tactics and three that did not use common misinformation tactics. When presented with each headline, participants were asked to respond to the question ‘Does this headline use any misinformation techniques?’ on a 4-point scale: Definitely is misinformation, Probably is misinformation, Probably is not misinformation, Definitely is not misinformation. For ease of interpretation, ratings were scored such that higher scores represent stronger belief that a headline was misinformation (Definitely is misinformation = 4 and Definitely is not misinformation = 1). We chose phrasing that highlighted the term misinformation to increase relevance to policymakers and practitioners, but it is worth noting that much prior research on inoculation measures perceptions of misleadingness rather than misinformation classifications per se (e.g., Roozenbeek et al., 2022). In line with prior literature, we compute three scores to assess accuracy in misinformation detection (Basol et al., 2021; Maertens et al., 2021). First, we calculate a measure of discernment, defined as a participant’s average misinformation scores for misleading headlines minus their average score for headlines without misleading content. With this operationalization, discernment scores could range from -3 to +3 where a score of +3 indicates a participant rated all misinformation headlines as ‘Definitely misinformation’ and all non-misinformation headlines as ‘Definitely not misinformation’ for perfect discernment. We also examine the disaggregated discernment score including the average ratings for the three misleading headlines and ratings for the three non-misleading headlines. As higher ratings correspond to judgements that a headline is using misinformation tactics, more accurate scores would be represented by higher scores on the misleading headlines (representing true positives) and lower scores on the non-misleading headlines (representing true negatives).

Sharing Misinformation Adapted from Basol et al. (2021) and Roozenbeek and van der Linden (2020), sharing of misinformation was assessed with two headlines: one that did not use misinformation tactics and a headline that used misinformation tactics. Each participant was randomly assigned to one of two misleading headlines, a headline that used extreme emotion or a headline that used a false expert. Participants were asked to rate their likelihood of sharing each of the headlines on a four-point scale: (1) Very unlikely to share, (2) Unlikely to share, (3) Likely to share, (4) Very likely to share. As with judgements of misinformation, we report three scores for sharing—discernment of sharing, likelihood of sharing misleading headlines, and likelihood of sharing non-misleading headlines. Discernment of sharing was calculated as the sharing score for non-misleading headline minus the sharing score for the misleading headline. Accordingly, participants with high positive discernment of sharing have lower intentions of sharing misinformation, relative to sharing more non-misinformation.

Self-Report Outcomes Complementing the evaluation of the intervention’s impact on detection and sharing of misinformation, we examined differences in attitudes toward the chatbot game.

Confidence Participants were asked to indicate the extent to which they felt more, the same, or less confident in detecting misinformation after completing the game.

Perceived Difficulty Participants were asked to report whether they thought the game was too difficult, the right level of difficulty, or too easy.

Recommending the Game Participants were asked to indicate the extent to which they would recommend the game to others with three possible response categories: yes, maybe, and no.

For more information, please find our Working Paper.

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