Skip to main content

Predictive Dialers-Pros and Cons


Dialers are an integral part of an outbound call center. They improve the agent performance manifold and are an indispensable tool. There are many kinds of dialers and these include predictive, progressive and preview. And just like any thing, we have to be careful to pick the right tool for the job.

At Ozonetel we have deployed more than 500 call centers and deal with more than 20,000 agents on our cloud call center platform, Cloudagent. In most cases, supervisors, when asked to improve the agent performance by management, fall back on a tool and suggest to use a predictive dialer. And in many cases we have worked with the call center teams to understand the core problem and deduced that the problem can be solved by minor process changes instead of upgrading the dialer.
So, when should you use a predictive dialer?
To answer that, you should first understand your requirement.

Do you make outbound calls to people who have subscribed in some means(event, website etc) or just cold calling a random database.

Predictive dialing makes sense only in case of cold calling a generic database.

As the name itself specifies, it is a predictive dialer. It predicts that 1 out of 4 will pick etc. And that prediction is generally made on some statistical analysis.
Now, the important metric there is how good is the prediction. If the prediction is wrong 10% of the times, that means if you make 1000 calls, then there is a possibility that 100 calls which were picked will go unanswered. This is generally bad when the pick ratio itself is low. In some countries, it is in fact illegal to left the unanswered percentage go beyond a certain limit.
Most of the companies we have worked with have said that answering every call was more important and hence they did not opt for predictive dialers.
If you are calling a subscribed list,then it does not make sense as you have to answer every call. Also, if more callers end up in queue based on wrong prediction, then there is a chance that your number will be marked as spam in public databases like Truecaller etc. So, please make sure any prediction you use specifies how many callers end up in queue.

But predictive dialers have their place and that's why we have been experimenting with various stuff. We have put our speech team on coming out with a hidden markov model for prediction. We are even doing a neural network approach where it learns about the campaign. Also, since we are on the cloud we have more data to train. Most predictive dialers in the market just do ratio based dialing with manual control. So if the ratio is 4:1, then every time an agent becomes free we dial out 4 calls predicting that 1 will be answered. This is a hard coded approach and can only scale so much. The hard coded approach is available in Cloudagent and we are coming with a patented new approach in a couple of months. Keep watching this space for more updates.



Popular posts from this blog

Integrating Arborjs with Angular to create a live calls dashboard

Arborjs  is a cool graph visualization library. Angular  is one of the best JavaScript frameworks and we have been using Angular in a lot of our front end development. When you handle millions of calls, proper visualization becomes very important. Without proper visualization, you can get lost in the mountains of data. So we spend a lot of time to come up with good visualizations to represent the data. Since we loved the cool way in which Arbor represented graph data, we could not wait to hook it up with Angular. Because of Angular's two way data binding, when you hook up Angularjs with Arbor.js you can get a dynamically updated visualization of graph data with cool animations. To give back to the community, we have put up the code online at Github . Basically we have created an Angularjs directive for Arborjs. Please feel free to fork the code and add extensions and use it for your own visualizations. The code is self explanatory with comments inline. Best way to ...

First Post

In this blog, I will be talking about my experiences in trying to build a cloud telephony platform , KooKoo . Along the way I will also be talking about different design choices I made, good programming practices and the IVR domain in general. For technoratti: NNFJW8EW86C3

Cloud Telephony-History and state of the art

Well, its been 11 years since Twilio launched their voice API in November 2008. I would say that was a major turning point in the cloud telephony industry. Before that, for people to build telephony applications, you either had to depend on proprietary platforms like Avaya dialog designer or build on arcane technologies like VXML which again was supported at varying degrees by the incumbents. Enter Twilio with their voice API and the industry changed for the better. Since it's been almost 11 years now I thought now might be a good time to do a comprehensive review of the cloud telephony industry as a whole in general and in India in particular. The Beginning Twilio was undoubtedly the startup which ushered in the era of cloud telephony. They started in November 2008. At that time in India, we at Ozonetel had launched a hosted VXML platform. There were no takers. After all who coded in VXML :) So when Twilio launched and we saw them take off, we immediately realized tha...