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Why are chatbots needed in a call center?

May 17, 202314 MIN READ

Most of us are aware of the big benefits of using chatbots in call centers, which include their 24/7 availability and quick response rate. But did you know that AI bots are poised to drive 3400% growth in operational savings in 2023?

How? The biggest cost component in customer service operations is voice call interactions, which is why smart brands have started encouraging customers to look for instant resolutions through digital and self-serve channels.

As per the Juniper Research cited earlier, chatbots have the potential to lower operational costs substantially by offering a robust self-service channel for customers, and this is one of the reasons why chatbots are essential for call centers.

The second reason is that modern customers prefer to use multiple channels. If you want to craft seamless experiences and serve them throughout, your agents will need the help of chatbots.

Now, what exactly are chatbots? How can they benefit call centers and enhance their operations? Will they be an alternative to human agents? What are their features, and what challenges could a call center face in implementing chatbots? Let’s answer all these questions one by one.

What is a chatbot in a call center?

A call center chatbot understands and responds to real-time customer queries, providing relevant resolutions under minimal agent intervention. Chatbots could be programmed according to your business use cases, whether collecting data or agent feedback. However, there are many more applications of AI chatbots in call centers. Let’s discuss them.

Common use cases for chatbots in call centers

Organizations can leverage chatbots to engage with customers by deploying them to answer Frequently Asked Questions (FAQs) and speeding up response times. You craft better customer experiences as well as save costs on operations. Here are three primary use cases of chatbots in a call center.

1. Automate website support

Your website is one of the first points of contact between you and your customers. They will have a lot of questions about your products and services like:

  • How can your product help me?
  • What is the cost of your product?
  • Will I get any warranty?
  • What should I do in case I need any technical help?
  • Would there be any shipping charges?

Chatbots are efficient in resolving commonly-asked queries. Deploying them on your website helps in delivering instant responses, without overwhelming your agents. Even when agents are busy or unavailable, chatbots can continue resolving queries 24/7, shooting up your response rates and reducing customer churn.

Bots can function like a bridge between your customers and agents, making it easy to optimize your service process at every stage of the buyer’s journey. When agents are unavailable, bots can continue collecting customer data and hand it to agents on a platter, enabling faster resolutions.

2. Become a support system inside the app

Companies are implementing chatbots in their mobile apps and leveraging them as a customer support system. Using conversational AI, chatbots have become a primary force of in-app support as you can easily provide these three things to your customers.

  • Timely notifications and updates
  • Real-time query resolutions
  • Personalized product recommendations

It helps increase user engagement, making the customer feel more satisfied with getting assistance within the app, without jumping through multiple channels.

3. Gather instant feedback and increase your net promoter score

Chatbots can be leveraged heavily to get customer feedback across different stages of the buyer journey. Post a sale, you can use a chatbot to send a pop-up survey to your customer and gather feedback on their purchase experience.

Similarly, chatbots can share NPS surveys with customers during their interactions to gather authentic testimonials for promotion on different customer-facing platforms. In short, using chatbots is a win-win. They help you increase customer satisfaction and detect loyal customers and advocates through NPS scoring, enabling you to build a better brand.

How can chatbots benefit call centers?

As said, chatbots don’t just help you lower your operational costs, but they also help you craft better customer experiences. They allow you to manage customers who overload your helpline by deflecting them to cost-effective channels like web chat, SMS, email and WhatsApp. Let’s elaborate on the main benefits of using chatbots in contact centers.

1. Low service costs

Self-service tools like chatbots provide organizations an excellent opportunity to reduce overall support costs as they cost way less than live channels. For B2B and B2C companies, live channel interactions cost $7 and $13, respectively, as opposed to $3.64 in chatbots.

If organizations could deploy enough chatbots, customer support agents would spend more time-solving complex queries, leaving the basic issues to self-serve tools and reducing the cost per contact.

2. Faster response time

Today, customers suffer from the paradox of choice. If you give delayed responses to their queries, the probability of them choosing your competitor over you becomes high. For an average customer, how fast you get back to them matters; faster responses can increase your conversion rate by 21x.

With chatbots, you can engage with your customers 24/7, which helps brands improve their sales by 67%.

3. Higher agent productivity

Chatbots can easily handle basic queries, leaving agents with more time to focus on complex issues. They also help in pre-qualifying customer issues by asking questions and gathering relevant information before transferring it to an agent.

While the agent deals with a complex issue, chatbots can provide real-time assistance, sharing relevant customer information and help articles to guide them through the troubleshooting process. This way, agents are able to resolve more cases in less time and boost their productivity at individual and team levels.

4. Better CSAT and NPS

If your NPS and CSAT scores are below industry benchmarks, step up your customer service game by deploying chatbots. They can drive net promoter scores (NPS) as businesses can use them to implement AI-driven customer surveys.

Getting a good NPS score is not the only objective here, it’s also about understanding why customers gave a particular score.

These surveys go beyond asking monotonous questions and focus on understanding the customer expectations from a brand. Thereafter, the decision-makers can implement customer insights to improve the overall customer experience, product and pricing strategy, leading to happier customers.

How do chatbots enhance call center operations?

If you deploy chatbots, it’s like putting call center operations on steroids. If a customer service chatbot is not deployed, this is how a customer journey looks like if they try to get details of a particular product on an e-commerce website.

Without a chatbot to assist, this is how the customer journey would look:

  1. The customer visits the website
  2. They enter the category and name of the product
  3. Scroll through the search suggestions
  4. Skim through the details till they find the right product

With a chatbot deployed, it becomes a two-step process:

  1. The customer visits the website
  2. The customer interacts with a chatbot, “Hey, please find me this product.”

Steps

Without chatbot assistance

With chatbot assistance

1

The customer visits the website

The customer visits the website.

2

They enter the category and name of the product.

The customer interacts with a chatbot, “Hey, please find me this product.”

3

Scroll through the search suggestions

-

4

Skim through the details till they find the right product.

-

Boom, that’s it! One request, and the job is done. With chatbots, you provide a virtual assistant to your customers during their buying journey.

Natural language processing (NLP) and natural language understanding (NLU) helps chatbots understand human speech better. The more the customer interacts with the bot, the more efficient the bot gets in understanding the intent behind conversations and responding accordingly.

NLP and NLU help AI chatbots to provide automated responses with a human touch reflecting the conversation, making conversational AI a cost-effective alternative to agent-assisted support.

Gartner agrees with the above statement and predicts conversational AI will reduce contact center agent costs by $80 billion in 2026.

Chatbots vs. human agents

Comparison attributes

Chatbots

Human agents

Availability

Chatbots are available 24/7

Human agents are not available 24/7

Scalability

Chatbots can handle surge in traffic with ease

Scaling human agents requires hiring, training and managing costs

Personalization

With sentiment analysis, chatbots can provide personalization to an extent

A well-trained human agent can always empathize with a fellow human’s problem better

Efficiency

Chatbots can handle large volumes of basic queries at once but not when queries become complex

Handling multiple queries for a human agent is difficult but when it comes to complex queries, they resolve it better

Complexity of queries

Chatbots are well suited for straight forward basic queries

Humans have a wide range when it comes to handling the complexity of queries, from simple to difficult, they can handle everything based on their expertise

Cost

Deploying chatbots entails a one-time cost of production amounting to ~ $3000 but scaling chatbots is cost-effective

Hiring a human agent cost around $4000 but it’s a recurring cost that happens whenever an agent churns or your needs expand

Essential features of chatbots for call centers

There's no end to the features you can have in a call center chatbot, but some are non-negotiable. To begin with, you should look out for these five main features when developing your chatbot.

Unsupervised AI Learning (NLP/NLU)

The best call center chatbots are developed through unsupervised AI learning. It involves discovering hidden patterns and insights from the given data. Compare it with how a human brain learns new things, that’s how unsupervised learning works. It will help your bot personalize conversations based on user profiles and, as per their understanding, offer them solutions and recommendations to make informed decisions.

Knowledge base

Knowledge is power, and your chatbot is robust if it can integrate seamlessly with a knowledge base. It helps them deliver the right answers and updates. And as long as the knowledge base keeps getting updated, the bot only gets better and better with the delivery of resolutions.

Omnichannel messaging

If your company wants to give an omnichannel customer experience, you need omnichannel bots.

With omnichannel bots, you can be omnipresent and offer a seamless, consistent experience to your customers everywhere. Plus, these bots adapt accordingly when customers switch between channels and never lose conversation context.

Customization

Deploying chatbots is a great idea, but you can confuse your users if your chatbots don’t reflect your brand identity. Your chatbots should be similar in physical attributes across all touchpoints to give users a unified experience.

And for this very reason, customization is a much-needed feature in chatbots. Infuse your brand’s personality into your bot and make it stand out. In fact, you can train your bot to speak in any human voice of your choice and lend a human touch to your bot conversations.

Sentiment analysis

Sentiment analysis enhances chatbots' ability to interpret a query's intent through context, tone of voice and words used by the user. It comes in handy when a chatbot is dealing with an angry and frustrated customer. Moreover, you get to know what a customer feels about your products and services. Analyze their sentiments over a period and figure out which products, services and teams are doing well, and which have scope for improvement.

It also helps the bot classify words as positive, neutral or negative, helping it to understand the mood of a conversation and suggest the next steps to the agent in the queue.

Chatbots learn fast, and with every interaction, they become more insightful in their support, leveraging sentiment analysis.

Challenges in chatbot implementation for call centers

Yes, the benefits of a chatbot are plenty, but building and deploying chatbots comes with its own set of problems, which can be classified into three main buckets.

Privacy and security hazards

Chatbots should comply with privacy regulations like GDPR and CCPA. Call centers should be careful about how they manage their data.

When discussing delicate issues like finance, people don’t really trust chatbots. They may appear to them as unsecured, and avoid them altogether. As an organization, it’s a good practice to be transparent and let your customers know when they are talking to a chatbot. That way, they won’t mistake them for actual people and divulge sensitive information.

Apart from investing in the functionality of chatbots, do look into their security features. Ensure it’s end-to-end encrypted and built on HTTP protocol in order to secure user information.

Incompatibility with human agents

In 2019, Forrester raised concerns that customers would rebel against chatbot support because 60% of chatbots don't have escalation options. If a customer is talking to a chatbot, there should be an inbuilt option to get in touch with a customer agent to maintain a seamless experience.

More than a replacement for human agents, chatbots are like reliable assistants that can recognize when a query requires human intervention and seamlessly transfer the conversation to a human agent.

Difficulty in measuring value

Many businesses build chatbots to be in sync with the trends. Investing in a chatbot without understanding how, where and why to use it can result in a waste of resources. To measure the value of chatbots, take into account these three factors.

1. Activity volume

One of the factors that determine the value of a chatbot is activity volume. Activity volume is the number of interactions it has with its users, and whether the interactions increase or decrease over a given period of time determines how valuable the chatbot is or will be over a given period of time.

2. User feedback

Another way to measure the value of a chatbot is getting user feedback. You can ask these two questions to the user after each bot interaction.

  1. Did the chatbot resolve your issue?
  2. Will you use this chat service again?

If these questions get a favorable response, the chatbot is doing well, and your investment is worth it.

3. Customer support savings

Finally, the amount of time and money you are saving is a major point in evaluating the value of chatbots. How does a bot help save money? Are the agents getting more work done because of the chatbots, or has the working process become more time-consuming? Finding answers to these questions, and adding up all of the above factors will help you measure the value of a chatbot.

Understanding why you are deploying a chatbot and how you will measure its value are two important things you need to determine. Asking these kinds of questions before developing a chatbot will inform your bot strategy.

  1. What kind of queries will it address?
  2. How much improvement do you look for in your CSAT score?
  3. Will it reduce the workload of your agents?

Once you have clear answers, you understand why you are implementing chatbots and how it’s an important step to make the life of your customers and agents easier.

You need a chatbot in a call center because they remove the initial hiccups of a conversation between a customer and an agent. If ever your phone line gets jammed with pending complaints, your agents will find chatbots pretty handy. Let chatbots take the call and engage the customer before your agent comes in and resolves their query without wasting any time. Customer experience at its best!

Wrapping up

Deliver peak customer experience with Sprinklr’s Conversational AI, as it offers everything you need in a contact center solution. Enhance your chatbot functionalities with contact center intelligence and live chat, and add the final touches to build a seamless agent and customer experience by deploying an agent assist option in the conversation.

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