Update Frequency: N/A

A log of the Unified Call Center's service requests.

To download XML and JSON files, click the CSV option below and click the down arrow next to the Download button in the upper right on its page.

The Global Call Centre market is projected to grow significantly, from USD 37,411.0 Million in 2025 to USD 76,831.3 Million by 2035 an it is reflecting a strong CAGR of 7.4%.

Semi-Annual Market Update

Country-wise Insights

Category-wise Insights

1) Data Introduction • The Call Center Data includes a variety of data related to call center operations, including customer inquiries, call times, agent information, and service types that occur routinely at the call center.

2) Data Utilization (1) Call Center Data has characteristics that: • This dataset provides key indicators and details of call operation, including call ID, customer ID, counselor ID, call start/end time, call length, inquiry type, and call results. (2) Call Center Data can be used to: • Service Quality and Efficiency Analysis: Use call time, call result data to assess the performance of the counselor and the quality of service of the call center. • Analysis of trends by type of customer inquiry: By analyzing inquiry type and frequency data, you can identify key customer needs and trends, and use them to improve service.

In 2024, the ************* was the country with the highest number of call centers that were opened or expanded in that year. The majority of countries or regions featured in this survey including the United States decreased the number of call centers that were newly opened or expanded since 2020. As the United States opened less call centers in 2024, the number of contact center employees accordingly decreased between 2020 and 2024.

ArXiv Paper Publication Here: "Real-World En Call Center Transcripts Dataset with PII Redaction" This dataset includes 91,706 high-quality transcriptions corresponding to approximately 10,500 hours of real-world call center conversations in English, collected across various industries and global regions. The dataset features both inbound and outbound calls and spans multiple accents, including Indian, American, and Filipino English. All transcripts have been carefully redacted for PII and… See the full description on the dataset page: https://huggingface.co/datasets/AIxBlock/92k-real-world-call-center-scripts-english.

Update Frequency: "An automated scan for dataset updates occurs every day at 3:45 a.m."

For up to date information on service requests please visit, https://city.milwaukee.gov/ucc .

A log of the Unified Call Center's service requests.

From potholes, abandoned vehicles, high weeds on vacant lots, and curbside trash to faulty traffic signals, the City of Milwaukee's Unified Call Center (UCC) makes it easy to submit service requests to solve problems. The UCC also allows you to track your service requests. Each time you complete a service request online, you will be assigned a tracking number that you can use to see when a City of Milwaukee representative expects to investigate or take care of your request.

To download XML and JSON files, click the CSV option below and click the down arrow next to the Download button in the upper right on its page.

Explore a rich Arabic customer speech dataset designed for call center customer care applications. Perfect for training AI models and enhancing customer service solutions.

Introduction

This Vietnamese Call Center Speech Dataset for the Telecom industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for Vietnamese-speaking telecom customers. Featuring over 30 hours of real-world, unscripted audio, it delivers authentic customer-agent interactions across key telecom support scenarios to help train robust ASR models.

Curated by FutureBeeAI, this dataset empowers voice AI engineers, telecom automation teams, and NLP researchers to build high-accuracy, production-ready models for telecom-specific use cases.

Speech Data

The dataset contains 30 hours of dual-channel call center recordings between native Vietnamese speakers. Captured in realistic customer support settings, these conversations span a wide range of telecom topics from network complaints to billing issues, offering a strong foundation for training and evaluating telecom voice AI solutions.

Topic Diversity

This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral ensuring broad scenario coverage for telecom AI development.

This variety helps train telecom-specific models to manage real-world customer interactions and understand context-specific voice patterns.

Transcription

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

These transcriptions are production-ready, allowing for faster development of ASR and conversational AI systems in the Telecom domain.

Metadata

Rich metadata is available for each participant and conversation:

Between 2014 and 2023, the number of employees working in the contact center industry in the United States increased overall, despite some fluctuations. In 2023, there were roughly **** million people working in contact centers, a decrease when compared to the previous year.

Introduction

This Mexican Spanish Call Center Speech Dataset for the Telecom industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for Spanish-speaking telecom customers. Featuring over 30 hours of real-world, unscripted audio, it delivers authentic customer-agent interactions across key telecom support scenarios to help train robust ASR models.

Curated by FutureBeeAI, this dataset empowers voice AI engineers, telecom automation teams, and NLP researchers to build high-accuracy, production-ready models for telecom-specific use cases.

Speech Data

The dataset contains 30 hours of dual-channel call center recordings between native Mexican Spanish speakers. Captured in realistic customer support settings, these conversations span a wide range of telecom topics from network complaints to billing issues, offering a strong foundation for training and evaluating telecom voice AI solutions.

Topic Diversity

This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral ensuring broad scenario coverage for telecom AI development.

This variety helps train telecom-specific models to manage real-world customer interactions and understand context-specific voice patterns.

Transcription

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

These transcriptions are production-ready, allowing for faster development of ASR and conversational AI systems in the Telecom domain.

Metadata

Rich metadata is available for each participant and conversation:

Call Center Analytics Market Outlook

The global call center analytics market size is projected to grow from $2.5 billion in 2023 to $9.2 billion by 2032, reflecting a compound annual growth rate (CAGR) of 15.3% from 2024 to 2032. This growth is primarily driven by the increasing demand for enhanced customer experience management and the rising adoption of advanced analytics solutions in call centers across various sectors.

One of the significant growth factors in the call center analytics market is the need for organizations to analyze and improve customer interactions. As businesses strive to offer superior customer service and experience, they are increasingly turning to analytics solutions that can provide insights into customer behavior, preferences, and pain points. This, in turn, helps businesses to enhance their service quality, reduce costs, and increase customer satisfaction and loyalty. Additionally, the integration of artificial intelligence (AI) and machine learning (ML) in analytics tools is further propelling the market growth by enabling more accurate predictions and personalized customer interactions.

Another key driver is the growing importance of workforce optimization in call centers. Call center analytics solutions play a crucial role in managing and optimizing the performance of call center agents. These solutions can track and analyze various performance metrics, such as call handling time, first-call resolution rate, and customer satisfaction scores. By leveraging such data, organizations can identify areas for improvement, provide targeted training to agents, and ensure efficient resource allocation. This focus on enhancing workforce productivity and efficiency is significantly contributing to the market's expansion.

The increasing regulatory scrutiny and the need for compliance management are also fueling the demand for call center analytics. In sectors such as BFSI and healthcare, organizations are required to adhere to strict regulatory standards to ensure data security and privacy. Call center analytics solutions help these organizations to monitor and report compliance-related metrics, identify potential risks, and take proactive measures to mitigate them. This capability is becoming increasingly important, given the rising incidences of data breaches and the growing emphasis on regulatory compliance across industries.

Regionally, North America is expected to dominate the call center analytics market during the forecast period. This is attributed to the presence of key market players, the high adoption rate of advanced technologies, and the strong focus on customer experience management in the region. However, Asia Pacific is anticipated to witness the highest growth rate, driven by the rapid digital transformation, the increasing number of call centers, and the rising investments in analytics solutions by organizations in countries such as India and China.

Component Analysis

The component segment of the call center analytics market is broadly categorized into software and services. The software segment includes various analytics tools and platforms that enable call centers to collect, analyze, and interpret data related to customer interactions. The services segment encompasses consulting, implementation, and support services that help organizations integrate and optimize these analytics solutions within their existing infrastructure.

In the software segment, the adoption of AI and ML-powered analytics tools is significantly transforming the way call centers operate. These advanced tools can analyze vast amounts of data in real-time, offering actionable insights that help call centers to enhance customer experience, improve agent performance, and achieve operational efficiency. Moreover, the increasing preference for cloud-based analytics solutions is further driving the growth of this segment, as they offer scalability, flexibility, and cost-effectiveness compared to traditional on-premises solutions.

The services segment is also witnessing substantial growth, as organizations seek expert guidance to implement and manage analytics solutions effectively. Consulting services are particularly in demand, as they provide organizations with strategic advice on selecting the right analytics tools, defining key performance indicators (KPIs), and developing data-driven decision-making processes. Additionally, the need for ongoing support and maintenance services to ensure the seamless functioning of analytics solutions is contributing to the expansion of this segment.

Introduction

This Indian English Call Center Speech Dataset for the Healthcare industry is purpose-built to accelerate the development of English speech recognition, spoken language understanding, and conversational AI systems. With 30 Hours of unscripted, real-world conversations, it delivers the linguistic and contextual depth needed to build high-performance ASR models for medical and wellness-related customer service.

Created by FutureBeeAI, this dataset empowers voice AI teams, NLP researchers, and data scientists to develop domain-specific models for hospitals, clinics, insurance providers, and telemedicine platforms.

Speech Data

The dataset features 30 Hours of dual-channel call center conversations between native Indian English speakers. These recordings cover a variety of healthcare support topics, enabling the development of speech technologies that are contextually aware and linguistically rich.

Topic Diversity

The dataset spans inbound and outbound calls, capturing a broad range of healthcare-specific interactions and sentiment types (positive, neutral, negative).

These real-world interactions help build speech models that understand healthcare domain nuances and user intent.

Transcription

Every audio file is accompanied by high-quality, manually created transcriptions in JSON format.

Metadata

Each conversation and speaker includes detailed metadata to support fine-tuned training and analysis.

Usage and Applications

This dataset can be used across a range of healthcare and voice AI use cases:

In 20223 there was a slight increase in the number of call center jobs created in several countries and regions. In the Philippines, for example, there were approximately ****** more call center jobs created than in 2022. India created the highest number of jobs globally within this industry, approximately ****** more when compared to the previous year. In 2022, the region that created the most call center jobs in the United States was in the *********.

Telemarketing and call centers have navigated a dynamic economic landscape in recent years, grappling with challenges and opportunities alike. The initial impact of the pandemic at the onset of the period led to a temporary dip in demand as businesses curbed outsourcing due to reduced consumer spending and corporate profit. However, quick transitions to remote operations and an improving economic landscape in the latter part of the period increased demand for the industry, specifically from the healthcare sector. There was an increase in demand for the industry’s services as consumers returned to traditional shopping and corporate profit soared, spurred by expansionary fiscal and monetary policies. This uptick, however, was only one side of the coin. Increasing inflationary pressures in 2022, driven by a massive jump in demand, forced businesses to tighten budgets, reducing spending on telemarketing and call center services. This caused revenue to drop significantly, with further challenges posed by rising interest rates and offshoring trends. The growing use of AI and automation spurred an influx of new entrants as smaller players were better able to compete with larger and established players, raising internal competition. While technological advancements like IVR and speech analytics have reduced costs and improved efficiency, the competition from global markets, particularly emerging economies, has diluted some of the industry's growth potential. Overall, revenue for telemarketing and call centers has inched downward at a CAGR of 0.1% to $28.1 billion over the past five years, including an expected increase of 3.6% in 2025 alone. Industry profit has climbed and will account for 13.4% of revenue in the current year. Looking ahead, providers are anticipated to benefit from stable economic growth and the continued expansion of online activities. Cooling inflation and reduced interest rates are expected to boost consumer spending and corporate investment, bolstering demand for telemarketing and call center services. Technological advancements will further enhance operational efficiency, although high wage costs will continue to challenge profit. The ongoing migration towards e-commerce will necessitate greater investment in call centers as companies look to better serve online customers. Despite the inherent challenges, the industry's capacity to leverage technological innovations and explore new geographical markets provides a promising outlook. Overall, revenue for telemarketing and call centers is forecast to expand at a CAGR of 3.7% to $33.6 billion over the five years to 2030.

Introduction

This French Call Center Speech Dataset for the Telecom industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for French-speaking telecom customers. Featuring over 30 hours of real-world, unscripted audio, it delivers authentic customer-agent interactions across key telecom support scenarios to help train robust ASR models.

Curated by FutureBeeAI, this dataset empowers voice AI engineers, telecom automation teams, and NLP researchers to build high-accuracy, production-ready models for telecom-specific use cases.

Speech Data

The dataset contains 30 hours of dual-channel call center recordings between native French speakers. Captured in realistic customer support settings, these conversations span a wide range of telecom topics from network complaints to billing issues, offering a strong foundation for training and evaluating telecom voice AI solutions.

Topic Diversity

This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral ensuring broad scenario coverage for telecom AI development.

This variety helps train telecom-specific models to manage real-world customer interactions and understand context-specific voice patterns.

Transcription

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

These transcriptions are production-ready, allowing for faster development of ASR and conversational AI systems in the Telecom domain.

Metadata

Rich metadata is available for each participant and conversation:

This statistic shows the share of cloud-based and premise-based call centers in North America as of April 2017. During the survey, ** percent of respondents said their call center was a cloud-based call center.

This statistic depicts the call center market size in 2018, with a breakdown by region or country. In 2018, the call center market size in the United States was estimated to amount to around **** billion U.S. dollars.

Between 2020 and 2023, the number of jobs created in the global call center industry fluctuated significantly. The industry with the highest amount of new jobs created in 2023 was **************************** (BPO), totaling almost *******.

With almost ****** call center employees in 2018, Alorica, a California-based provider of outsourced customer management solutions (such as call centers), manages the largest call center operation in the country. While most of the largest call centers in the United States belong to familiar U.S. companies such as AT&T and Wells Fargo, number one on the list is conspicuous through not being a household name.

Call centers versus contact centers

A call center is a centralized office used to make or receive large volumes of telephone-based customer interactions. Often call centers also handle additional forms of customer interaction, with online forms of interaction such as email, live chat and social media becoming an increasingly important part of customer service. Strictly speaking, a call center that handles such additional channels is called a contact center.

U.S. call center industry

Despite the cliché of call centers being increasingly offshored, the number of call center operators in the United States has been consistently growing for the last five years (881114). Thousands of new jobs have been created in the call center industry over the last few years alone, mainly concentrated in Southwest and Southeast (802250). This pattern of growth coincides with the states that have the highest number of existing call center jobs. Most likely, this regional distribution of call center employment is connected to the higher wages in the northeastern states.

Explore a rich Call Center Customer Speech Dataset in English designed for customer care insights, improving service quality, and enhancing customer experiences.