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Everything you need to know about buying call center automation software
43% of customers think long wait times are the most frustrating aspect of customer service. The good news? It’s a fairly easy fix thanks to call center automation software.
When you look at the numbers, it’s clear there’s a big opportunity here to differentiate your customer service. 57% of customers have waited for support for over an hour, and 26% have waited for more than two hours. This means you can get ahead of your competitors by merely minimizing long wait times — but you’ll need call center software and a powerful voice AI system to do it.
Selecting the right call center automation software can be overwhelming, and there’s reputation and money at stake. In this guide, we explain everything you need to know before buying call center automation software.
- What is call center automation?
- Why do you need call center automation?
- Which tasks does call center software automate?
- Key features to look for in call center software
- How do you automate a call center?
- Maximize ROI with a powerful AI agent
What is call center automation?
Call center automation refers to using software to automate tasks like call scheduling, appointment reminders, and call routing within a call center environment.
Most modern call center solutions are AI-powered. They automate tasks like answering customers over the phone, routing customer calls to agents, and performing repetitive tasks using a combination of technologies like natural language processing (NLP) and robotic process automation (RPA).
Why do you need call center automation?
Whether you have an in-house support desk or a virtual call center, there’s money to be saved with automation. Of course, you also risk your reputation by not automating your call center operations. Here’s why:
- Long hold times: If there’s one thing every customer hates, it’s waiting on hold. Automating your call center with an AI agent and built-in Contact Center as a Service (CCaaS) tools like automatic call distribution enables customers to get answers quickly on any channel, allowing you to provide a cohesive customer experience.
- Clunky IVR: Interactive voice response (IVR) systems can be frustrating — press 1 for this, press 2 for that. It’s an annoying game of “guess what button to push” that makes your customers yell, “Get me an agent!” assuming they don’t hang up out of frustration. Replace your IVR with an AI agent so customers can start asking questions without having to make it through a phone tree maze first.
- Data silos: Agents spend considerable time piecing together information when systems aren’t integrated and automated. Suppose your customer Jim calls about a billing issue. The agent wants to view customer history and the billing system, but they’re not integrated. While the support agent frantically tries to pull data from disparate systems, Jim is running out of patience. See the problem?
- Customer dissatisfaction: The sum of all the previous points is customer dissatisfaction. Long hold times and inefficient processes that lead to agents struggling to keep up make them feel like they’re talking to a wall and waiting forever without getting anywhere.
Let’s look at how automating your call center can help you achieve goals, not just prevent problems. Call center automation can:
- Increase efficiency: Automation takes repetitive, mind-numbing tasks off agents’ plates. Your agents will save a ton of time that they spent on data entry and copy-pasting across systems. And with voice AI, your agents will save time on resolving repetitive customer queries and have the freedom to focus on strategic parts of work.
- Reduce costs: You can save big with automation. Here’s why:
- Fewer human hours spent on repetitive tasks translates to lower labor costs.
- An AI agent fields customer inquiries and reduces support desk traffic. This means fewer agents are tied to the phone, lowering the overhead costs of handling a massive influx of customer calls.
- Automated systems don’t make human mistakes. Fewer errors translate to less time spent fixing mistakes and fewer refunds due to slip-ups.
- Automated systems are easy to scale up during peak season without panic-hiring or stretching your financial resources.
- Improve customer and employee satisfaction: Automation improves customer satisfaction by offering quick resolutions and a personalized experience. And it improves employee satisfaction by taking repetitive tasks off their plate, allowing them to focus on more complex issues.
- Make informed decisions: Automated systems can collect, organize, and analyze data at lightning speed. They offer a comprehensive view of customer interactions to help you identify trends and track performance metrics. This real-time data is key to making informed decisions and making small but impactful adjustments to your customer service strategy.
Which tasks does call center software automate?
AI-powered call center software can automate internal as well as customer-facing tasks, like:
- Handling customer inquiries: An AI agent becomes your first line of defense. When customers call, call center software solutions use conversational AI to understand the customer’s question and respond using natural language.
- Call routing: If the customer requests to speak to an agent, the automated call distribution (ACD) system connects them to the right agent based on availability and other pre-defined criteria. For example, a customer calling for help modifying code is connected to an agent with expertise in programming.
- Internal tasks: Integrations enable call center software to exchange information with the tools in your tech stack. Integrations are vital to automating your workflow — it’s what enables agents to view customer details in the CRM during a call, view a customer’s previous support tickets, and automate repetitive tasks like data entry using apps like Zapier and IFTTT.
- Reporting: Call center software collects data and converts it into insightful reports. The reports include various metrics that help assess agent performance, identify trends and customer preferences, and gauge customer satisfaction.
- Feedback: You can configure call center software to automatically collect feedback after a call or send satisfaction surveys.
- Proactive issue resolution: Call center software with built-in predictive analytics can be your problem-solving wingman. It analyzes historical data using machine learning algorithms to predict potential problems before they occur, and suggests solutions based on similar issues from the past.
Key features to look for in call center software
On-premise solutions are obsolete. The best call center solutions today are cloud-based CCaaS. Here are some common features of a CCaaS solution:
- Call recording and monitoring
- Predictive dialer
- Call whisper and barge-in
- Multichannel support
All the top CCaaS providers offer these essential features. But these aren’t enough to stay ahead of the curve. Let’s talk about CCaaS features that can help you become future-ready.
Your customers want to self-serve. In fact, 67% of respondents said they prefer self-service over speaking to an agent. Imagine calling customer service, interacting with an AI agent, and getting your query resolved effectively — no need to hold or explain yourself multiple times to agents. That’s the dream isn’t it? It’s the experience your customers want (and deserve) and the most compelling reason for why you need voice AI for call center automation.
The problem? Only a few CCaaS solutions currently offer built-in voice-based AI because they have poor intent recognition capabilities. Voice AI should understand whether a customer needs more information, has a service query, or needs help troubleshooting to effectively address their needs.
Here’s some good news: You can integrate CCaaS with a third-party voice-based AI solution that’s accurate — solutions that can use existing resources like FAQs and your customer service knowledge base to help customers.
Collaboration tools allow your agents to assemble like Avengers to tackle customer issues. Agents can team up to share their superpowers with one goal: to help customers. Collaborative features like shared dashboards, screen sharing, and built-in chat go a long way in providing quick resolutions.
Suppose John, a support agent, gets a complex tech query. He needs help from Amanda from tech to help this customer. With collaborative tools, John can ping the in-house tech wizard, share his screen, draw diagrams, or even tag-team to resolve the customer’s problem together.
33% of customers have screamed or sworn at customer agents. 5% of customers admit to having threatened an agent’s job and 3% admit to having threatened to physically assault an agent. Yikes. You can avoid all of these problems with sentiment analysis.
Sentiment analysis is like teaching software emotional intelligence. The feature uses NLP and machine learning to scan call transcripts to decipher a customer’s mood and tone. It picks up on subtle cues to understand if a customer is being sarcastic or getting angry. Itcan even pick up on irony or cultural nuances.
Let’s say one of your customers calls support and it sounds like he had a rough day. Adam might not start the conversation with “Hey, I’m frustrated!” but his tone and choice of words might drop hints. Adam might say, “I’ve been waiting on hold for 10 minutes and I’m not getting anywhere!” — sentiment analysis knows that’s a red flag waving.
Sentiment analysis looks at the intensity of these words, voice pitch, and pace of speech. It alerts your agent that the customer isn’t in a great mood so they can be patient with him.
Predictive analytics is your crystal ball. It tells you what customers might do based on historical data. With intel from predictive analytics, you’re not just reacting to customers raising the flag, you’re putting out fires before they start.
Say you’re planning to raise the price of your SaaS. Past data shows a certain percentage of customers don’t renew their subscriptions after a hike. At this point, predictive analytics jumps in, sips on its digital coffee, and gets to work. Here’s what follows:
- Segmentation: Predictive analytics segments customers based on usage patterns, behaviors, and demographics. It identifies the group most likely to cancel their subscription. Suppose this group is the heavy data users on the mid-tier plans.
- Outreach: Agents — or better yet, your AI agent — reach out to this group with discount offers and loyalty perks before the price change hits. Armed with insights about customers’ preferences, agents offer tailored deals, such as an extra data bonus, to sweeten the deal for customers who are a flight risk.
- Feedback: Predictive analytics keeps monitoring cancellation inquiries and complaints for any upticks. It flags these upticks as soon as they occur so support agents can swoop in and take corrective action. This is also a great way to gauge the effectiveness of your strategy during outreach.
How do you automate a call center?
You can’t buy call center automation software and call it a day. You need a strategy to implement software and ensure all agents know how to use it effectively. Here’s a step-by-step guide you can follow to automate your call center:
- Evaluate workflows: Evaluate existing workflows to find repetitive tasks and bottlenecks in customer interactions. Seek input from the support team and analyze call center metrics to find room for improvement.
- Set goals: Once you have a list of tasks to automate, bottlenecks to address, and metrics to improve, set goals for how you plan to get from point A to point B. For example, your goals could be to reduce call wait times by 30%, increase containment rate by 50%, or improve CSAT scores by 25%.
- Find CCaaS: Find a CCaaS that offers features that can augment your customer service and fits your budget. Remember, even if the CCaaS you choose doesn’t have all the features built-in, you can always integrate it with third-party apps.
- Create an implementation plan: Create a detailed implementation plan that outlines phases and responsibilities. Don’t jump directly to full-scale deployment — create a pilot group to test the software so you can make adjustments and implement feedback.
- Configure and integrate the systems: Design IVR menus. Train and set up the voice AI agent. Integrate your CRM, ticketing system, and databases into your call center software so agents have access to holistic customer information.
- Train the team: Train agents to use the call center software, especially features that legacy systems lack, such as sentiment analysis.
- Monitor, measure, optimize: Establish KPIs and monitor them using built-in analytics. Collect agent and customer feedback on ways to improve and optimize the use of call center software. Most importantly, stay updated on new features and technologies to become the company that offers the best customer service in your industry.
Maximize ROI with a powerful AI agent
To maximize your ROI, you need cost-efficient call center automation solutions that deliver exceptional performance and help you become the customer service peck leader in your industry.
That’s where an AI agent comes in. A voice AI agent, like Ada’s, integrates into your CCaaS and answers customers using natural language. In fact, our aim is to reduce the number of calls that reach your support desk to zero.
Sarah Fox is a scuba-diving, animal-loving journalist turned content marketer. In her career, she’s covered stories on development, written profiles on notable philanthropists, and interviewed celebrities with a passion for giving back. When she’s not producing content for Ada, Sarah’s likely fawning over her dog somewhere in the woods.