Cloud Predictive Dialer
Companies across the globe are choosing Ameyo






What is Cloud Predictive Dialer?
A cloud-based predictive dialer is software that dials a list of numbers quickly to deliver more human connections on call. Cloud predictive dialer filters the busy tone, voicemail, unanswered calls, disconnected calls, answering machine to connect the agent only when a human answer a call. Cloud predictive dialer dials bulk numbers using different algorithms using historical stats to calculate agents’ availability for the next call. Cloud predictive dialer helps businesses cut down the manual dialing process. It also allows the agents to work efficiently while the calling is taken care of by the advanced dialer.


Which businesses should use Cloud-based Predictive Dialer?
Cloud predictive dialer is helpful in telemarketing, debt collection, customer service follow-ups, etc. A cloud-based predictive dialer helps the businesses segment the data and dials out the contacts in a programmatic way. In the use-cases above, cloud predictive dialer intelligently assigns the calls based on their wait time, call drop ratio, variance factor, and maximum pacing ratio, helping them qualify the leads more efficiently. For sending out reminders, upselling or cross-selling, scheduling callbacks for HNI customers, cloud predictive dialer works like a workhorse for sales strategies.
Features of Cloud Predictive Dialer Software
Convert Prospects Faster with Cloud-based Predictive Dialer

Intelligent Call Assignment

Missed Call Management

Lead Prioritization

Advanced Monitoring & Reporting

Easy CRM Integrations

DNC Management

Filter-based Calling

Retry Time Configuration

Answering Machine Detection

Dial Time Customization

Callback Management

Call Disposition & Notes
Ready to take your Outbound Calling to the Next Level?
Benefits of Cloud Predictive Dialer Software

Intelligent Call Assignment
Cloud predictive dialer software predicts the average time spent on each call. It further uses that prediction to automate the call assignment with its smart dialing algorithm.

Define Best Time to Call
With the ‘not call before’ feature, the cloud predictive dialer intelligently detects the best time to call an existing customer or a prospect based on previously collected data through past interactions.

Increased Call Connect Rates
Save agents’ time with an automated predictive dialer backed by a powerful answering machine detection feature. This eliminates the need for manual dialing; thus, the agents’ talk time increases.

Driving Contextual Conversations
Integrating the predictive dialer software with in-house or third-party CRM applications allow the agents to have a context-driven interaction with the customers/prospects and deliver a more personalized experience.

Increased Conversion Rate
While predictive dialer helps increase the agents’ productivity, it is also a must-have to increase the sales conversion rate with its smart best time to call, retry time configuration, lead prioritization features.
Ready to Maximize Call Connect Rates with a Cloud Predictive Dialer?
Why Ameyo for Cloud Predictive Dialer?

Quick Implementation
Get your cloud predictive dialer up and running quickly and start reaching out to customers in real-time.

Enterprise-grade Features
Ameyo offers full-stack contact center features with certified public cloud environments across India, APAC, ME, and Africa.

17+ Years of Expertise
Ameyo has been helping brands across verticals with result-focused customer engagement solutions.

Trusted by 2,000+ Brands
With a large pool of customers across the globe, Ameyo has become the choicest platform for 2,000+ customers covering 21+ verticals.

Pay-as-you-go Model
Ameyo offers a highly customizable ‘pay as you go’ solution to lower the CAPEX cost and helps businesses scale with ease.
The Ameyo Advantage
Leader in Customer Experience & Contact Center Solutions
Honorable Mention in Gartner Magic Quadrant for 3 Years
Awarded Frost & Sullivan Asia Pacific CCI Leadership Award
Deloitte Technology Fast 500 ASIA PACIFIC, 2014






