The global predictive dialer software market size is expected to reach USD 25.52 billion by 2030, according to a new report by Grand View Research, Inc. It is expected to expand at a CAGR of 42.3% from 2025 to 2030. Predictive dialer software uses statistical algorithms to predict the availability of contact center agents and estimates the normal time for phone calls to be answered. The dialing rate is then adjusted accordingly considering these two factors.
Businesses are widely adopting predictive dialer systems to reach out to a large number of customers automatically. Furthermore, predictive dialer dials from a list of phone numbers and can detect disconnected phone numbers, voicemail messages, busy signals, and unanswered numbers. Such a system potentially allows companies to keep their customers updated about a service issue or emergency.
Numerous businesses across the globe are adopting predictive dialer software to leverage automated dialer technology to connect with their customers in real-time. The software allows contact center agents to adjust the calling rate efficiently according to the sales benchmarks and quotas. The software also allows agents to access valuable customer information related to the next call in the lineup.
Predictive dialer software can allow contact center agents to effectively handle high call volumes. The software can also help businesses in improving agent efficiency and productivity with a lesser workforce. The outbreak of COVID-19 is anticipated to drive the demand for predictive dialer software as companies prefer working with a limited workforce amid the pandemic.
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By component, the software segment is expected to continue dominating the market over the forecast period. The capability of the software to help agents in handling blended calls and deal with both outbound and inbound calls prompts businesses to adopt the software to deliver higher customer satisfaction.
On the basis of deployment, cloud-based predictive dialer software assists businesses with the processes related to voice broadcasting and live call transfer. Its key features include voicemail detection, concurrent calling, campaign analytics, and text-to-speech conversion.
In terms of enterprise size, small and medium enterprises need efficient communication systems, which can potentially boost their business. Predictive dialer systems are suitable for small and medium enterprises as they can autodial call efficiently as per the business needs.
Based on end use, government agencies are widely adopting predictive dialer systems as they are affordable, can be easily installed on a desktop, and require no additional hardware. As a result, even smaller government organizations are adopting these systems to effectively communicate with citizens and staff.
Continued adoption of the latest technologies in emerging economies, such as China and India, is expected to create growth opportunities for the market in Asia Pacific.
Grand View Research has segmented the global predictive dialer software market report based on component, deployment, enterprise size, end use, and region:
Predictive Dialer Software Component Outlook (Revenue, USD Million, 2018 - 2030)
Software
Services
Integration & Deployment
Support & Maintenance
Training & Consulting
Managed Services
Predictive Dialer Software Deployment Outlook (Revenue, USD Million, 2018 - 2030)
On-premise
Cloud
Predictive Dialer Software Enterprise Size Outlook (Revenue, USD Million, 2018 - 2030)
Large Enterprise
Small & Medium Enterprise
Predictive Dialer Software End Use Outlook (Revenue, USD Million; 2018 - 2030)
BFSI
Government
Healthcare
IT & Telecom
Others
Predictive Dialer Software Regional Outlook (Revenue, USD Million, 2018 - 2030)
North America
U.S.
Canada
Mexico
Europe
U.K
Germany
France
Asia Pacific
China
India
Japan
South Korea
Australia
Latin America
Brazil
MEA
Kingdom of Saudi Arabia
UAE
South Africa
List of Key Players of Predictive Dialer Software Market
agilecrm.com
DialedIn
Convoso
Five9, Inc.
NICE
PhoneBurner
RingCentral, Inc.
Star2Billing S.L.
VanillaSoft
Ytel Inc.
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