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While many concepts in technology eventually become obsolete or unnecessary, that’s not true of diallers. After decades of serving call centres, they remain essential to operations. And they play an increasing role in driving revenue.
What is true of diallers: They’re evolving to keep pace with the cloud and artificial intelligence (AI) capabilities, as well as meet global regulatory demands. And this is all while needing to deliver better experiences to customers.
Today, opportunities abound with diallers. They can do much more in real time and work efficiently across organisations to deliver comprehensive outbound engagement. Let’s explore how and why call centre dialler software — a tool that’s been around for decades — plays such a major role in an AI-powered world.
Financial institutions frequently use dialler systems in the call centre. If they provide mortgages and loans, they likely service loans. That means there are collections teams whose job is to follow up on past due accounts.
And when your customers owe you money on a loan or credit card, you’ll want to reach out to them — not wait for them to call you. So, these businesses focus more resources on outbound capabilities — and often auto dialler software for the call centre — than on inbound.
New diallers offer more than earlier generations of auto-dialler software. In healthcare, for example, when you make an appointment, automated reminders are sent via phone, text or email — and they’ve proven to be very effective.
But in addition to those appointment reminders, healthcare providers also have a billing department for many of their providers. So, they’re doing the same type of outbound in other departments. Diallers offer value across organisations and they’re absolutely foundational.
A study by the International Customer Management Institute found that across various industries, automated dialing systems can lead to a 50–100% increase in outbound call productivity and a 20–40% reduction in operational costs.
Yet, collections teams still struggle to determine if there really is a “best time to call” to reach a person, considering that people can easily screen calls. The best time is when that customer is on your website, looking at their account balance. That activity demonstrates that they’re actively thinking about the debt, even wondering how to pay it off.
This type of predictive dialler engagement, which helps you identify the best time to engage, can return instant rewards. And it tells your customer service agents when a phone call might be perfectly timed. But this isn’t possible with older generations of the technology.
Previous generations of dialler servers were housed in offices. Businesses would create lists of those who needed to be contacted, often through manual dialing, the next day. Then overnight, they’d send a massive file of that contact list or phone numbers. This process of “batch loading” was very slow, as the file was moved and loaded into a dialing system.
The next day, the dialler system could make all those attempts to contact, many of which reached answering machines. Ideally, some people were reached, and the dialler would collect responses.
At the end of that day of dialing, the file would have to be extracted back out again as another massive file and pushed back to the system it came from. It’s a three-day process of building files, importing and running them, and then exporting them. And many companies still use this approach.
With modern CRM integrations, such as Genesys and Salesforce, that file import process is completely unnecessary. Rules are set up in Salesforce, defining when things are true, or statuses change.
For example, those rules immediately direct who goes into a campaign via API. This has a dramatic impact on customer satisfaction — and can benefit sales teams — because you’re taking action in real time.
Let’s say customer “Jane” calls in and makes a purchase, but Jane had been added to an outbound campaign that’s pending. Rules can instantly remove her from that campaign so she’s not contacted about a product she just purchased.
Previous dialler technology typically requires 24 hours for a batch file to be reconciled with its source system. Now, callable records are dynamic.
In addition to the improvement in customer experience, businesses save on maintenance and resources. This native outbound engagement type of dialler streamlines multiple steps in an ongoing process.
As businesses move into more advanced stages of AI, they’ll be reaching out to customers in even more ways. For example, our customer Jane might have a warranty for a new appliance. In the year 2040, she won’t be calling the vendor for service.
An AI-powered sensor would alert the vendor of any problem — even before Jane is aware of one. An outbound dialler would call Jane to explain the issue that was identified. And she would be asked when someone from the company could come out to repair or replace it.
This concept is similar to the simpler automated alerts that utility companies send out today. These public sector entities learned a long time ago about the power of dialler technology.
It enables them to proactively communicate service delivery issues to certain customers during planned or unplanned outages, thereby preventing a flood of inbound calls. Ultimately, that can lessen the burden on live agents who traditionally would have to field requests.
As AI technologies mature, proactive engagement will continue extending outbound capabilities. It will likely go beyond voice to include SMS and email based on rules that determine when to use each type — and for what.
While it’s possible to add workflows to accomplish something similar, AI will go much further. It will ensure that automated communications follow local or national regulations and that they’re built into campaigns, such as the appropriate time zones where each contact lives.
Outbound will be an essential partner to AI, handling not only compliance but also retry attempts and call analysis. It will understand the outcome of each attempt.
Soon, it will become the dialler’s job to handle all the considerations around proactive outreach. And it will be able to do so in a way that’s better than simply initiating a one-time SMS or a one-time voice phone call.
When transitioning to any new technology, there’s concern about how things will work when familiar processes are no longer needed. With diallers, it’s common to see questions in gap documents that request information on batching, importing and exporting files.
There’s also a misconception that updates done in real time would shut down a dialler. That’s no longer true with a cloud-based dialler such as Genesys Cloud Dialler, which uses the massive compute processing power of Amazon Web Services.
It’s hard to conceptualise a new way of doing things when the old way, although limited and time-consuming, worked for decades. This desire to stick with what’s known is also true with measuring “penetration rates.”
Once widely used, these rates refer to how far a system would get through a long list of contacts in one day. Let’s say a large enterprise wants to target a million records. They might expect a penetration rate of 75% or more.
But even with tracking capabilities to show that, it’s off-target. If the goal is to collect money on past due accounts, penetration rate doesn’t show how many people were spoken to — or how much money was collected.
That focus is shifting as the cloud enables direct connections to outcomes based on goals, and it requires a new way of thinking. When looking at too many other factors, it’s easy to lose sight of that goal as the best measure of success.
A purpose-built, natively blended dialler offers important advantages over those that are bolted on. Suppose you’re a collections agent who just completed an outbound call. You hang up and you’re then automatically delivered an inbound call. If it’s all one system, it knows not to send you another outbound call because you’re occupied on an inbound call. And an inbound call should always take priority over an outbound call.
If you’ve left a message about making a payment, that person could be calling you back and there’s a very good chance they’re going to make that payment or even just have a follow-up question. Either way, that call is top priority.
A cloud-based dialler that’s integrated with systems of record prioritises those inbound calls and blends them seamlessly into the outbound without any customisation. For Genesys Cloud Dialler, it’s an “out-of-the-box” capability that works for voice in the same way it does with email and other channels of engagement.
Most large businesses use some type of outbound dialler. It’s where the revenue comes in and it’s often the lifeblood of business — whether for collections, loan servicing, retail, healthcare or in just about any industry.
Without modern cloud-based outbound engagement capabilities that are integrated into your overall business, you’re missing opportunities. It’s time to discover how to dramatically improve your customer experience and save valuable time and resources.
Read “Seven best practices for building customer loyalty with AI” to learn how harnessing AI in your contact centre can shift your customer service from transactional to transformational.
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