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Why Customer Support Today is all about Self-Service

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Why Customer Support Today is all about Self-Service

Technology simplifies life.

Everything from the moment we wake up to when we sleep, we use different technologies that uncomplicate tasks for us. Things we used to do manually can now be automated using artificial intelligence.

For example, companies usually need high investment, training, and bandwidth to offer stellar customer support. Handling support tickets seamlessly typically needs more agents to answer queries. However, companies can now rely on conversational AI self-service chatbots to automate support resolutions and enhance CX. 

In fact, 81% of customers would first attempt to get solutions through a self-service portal before they reach out to a live agent. Self-service is convenient for both, companies and users alike. 

In our recent webinar titled “Why Customer Support Today is all about Self-Service”, we had Ankit Goenka, Head of Customer Experience at Bajaj Allianz General Insurance and Saransh Bhatnagar, Marketing Automation Lead at Noise share their views and takeaways on self-service with conversational AI.

You can watch the complete webinar here: Why Customer Support Today is all about Self-Service

We’ll now dive into the key takeaways from our discussion below.

How prevalent is conversational AI today?

Consumers of today are aware of the potential conversational AI holds in refining interactions they have with brands. It has enabled them to solve queries without connecting with a live support team.

Whether we are ordering food online or paying our credit card bills, self-service chatbots are streamlining these journeys everywhere. “People don’t have the time to go through an IVR or scavenge through a website to contact a company anymore”, notes Saransh.

Increasing online traffic has boosted self-service with conversational AI during the pandemic.

“80% of our total customer footprint is through digital assets.”, Ankit says while emphasising the wide-scale utility of self-service chatbots as we progress into a new decade. 

This brings us to our next question.

Why are consumers switching to self-service with conversational AI to get customer support?

What is the “convenience” factor that we mentioned earlier? Saransh cites three main reasons why people are inching towards self-service chatbots: Accessibility, Accuracy, Privacy.

While chatbots make customer support accessible and accurate, data privacy is the defining element for their uprise. Consumers are not always comfortable sharing their personal details over a call to a person. However, a customer self-service chatbot can collect and store information in a secure database. 

Moreover, customers don’t need to dial up a call centre or queue up in the waiting line to receive solutions. This makes self-service chatbots a popular alternative to traditional customer support.

Conversational AI offers a company the flexibility to build their customer self-service chatbot according to their use case. This way customers can receive support designed to solve their specific problems.

Self-service with conversational AI and agent productivity

Artificial intelligence has relieved customer support teams from dealing with a constant flurry of support tickets at any time. So, it’s impractical to expect all support agents to deliver the same level of service to every user. 

However, self-service chatbots are equipped to uphold consistent service quality across channels every single time. This way, AI can handle most of the common and elementary support tickets.

Now, customer support agents have to intervene only when there’s an absolute need. They can focus their attention and time on high-priority queries. This way, self-service chatbots can shoot up agent productivity. 

“Previously, handling 100 incoming calls at one time required 100 agents. 80 of those queries now can be handled by the self-service chatbot. The remaining 20 queries only need 4-5 agents to resolve.”, Ankit quantifies the impact customer self-service with conversational AI has had at Bajaj Allianz General Insurance. 

Measuring conversational AI metrics and ROI

Machine learning and artificial intelligence are evolving concepts. Their dynamic nature helps them to process data and refine their approach to queries. 

Some of the KPIs you should consider when deploying a conversational self-service chatbot are:

  • Bot-to-human percentage: This is a metric that shows the capability of a chatbot to handle x number of queries from the overall traffic. In other words, it’s the First-time resolution percentage that tells you how many queries your chatbot can handle end-to-end to offer a resolution in the first go.
  • CSAT: With this metric, you can gauge the satisfaction level of your customers with your service.
  • Onboarded users: A smart customer self-service chatbot will boost the number of converted users on your platform.

Apart from these, you can factor in the number of chat sessions initiated, engaged users, bounce rate, to name a few.

While these metrics can give you a fair idea of how well you are harnessing conversational AI, ROI is something that grows over time.

“Companies go wrong expecting immediate ROI when they first deploy artificial intelligence”, Saransh asserts. “A new chatbot needs training, iterations, and learning to be able to generate ROI”, he adds. 

“You’d probably had to wait for 2 years to see ROI from your AI chatbot. But with AI adoption skyrocketing, you can now see results just after 6 months.” He continues.

Self-service with conversational AI: Scaling and boosting customer adoption

When we talk about scaling with AI, a company needs to get to the grassroots with hyper-automation.

Hyper-automation is an efficiency-driven business approach with which a company explores, identifies, and implements automation across departments. Every single core business process that can benefit from AI is optimised by hyper-automation. 

Scalability is easier when your internal processes are automated. 

How can you drive AI adoption among users?

Expanding your chatbot’s reach can sometimes be tricky. For some people, artificial intelligence as a concept is still intimidating. “They think it’s like the movie Matrix – Keanu Reeves with zeroes and ones running in a green backdrop.”, Saransh laughs while showing how people can misconceive AI. With careful inspection and iterations, AI can be implemented and scaled in a company easily.

On the other hand, Ankit credits the WhatsApp chatbot for the level of reach his company was able to achieve.

“Implementing a WhatsApp chatbot was a game-changer for us. You don’t need to advertise or over-communicate on the platform, because everyone uses it.”, he adds.

WhatsApp makes accessing customer support easier because it is the most widely used chat platform.

“To reach out to more people, we need to align our campaigns in a contextual way which can boost conversions or pull them further down the sales funnel”, Saransh notes as a way to increase AI adoption. 

Besides the metropolitans, the rest of the country is a goldmine to scale with conversational AI-driven self-service. 

“I think one universal truth would be that we should never underestimate the potential that tier 2 and tier 3 cities have.”, he continues.

Bajaj Allianz General Insurance has been able to tap further deeper into the country’s demographic with their app “Farmitra”. Farmers can now view and claim their policies with the help of the app’s inbuilt chatbot.

“We have 3.5 lakh people using Farmitra as a self-service portal to check policy details and raise claims”, Ankit talks about the app’s success.

Besides this discussion, the webinar was an open forum for the audience to ponder over and ask any questions. We also touched on –

AI and the cost of human touch – This depends on the type of experience a company is looking to provide. Whether you want to connect with your users with natural conversations or provide integrated CXs, the cost depends on the company’s vision.

The efficiency of self-service – The key metric to measure is the end-to-end handling of support tickets by chatbots. If your chatbot itself can initiate a conversation, and direct the user to the right solution, then that’s a key metric to look into.

Customer’s willingness to use self-service chatbots – This is subjective to your product or service, opportunity costs, and the business’s own efforts to bridge the gap.

Don’t forget to check out the full-length webinar in which we dive much deeper into these questions and the potential self-service with conversational AI holds!

Quick recap:

  • Self-service with conversational AI makes customer support quick and accessible.
  • It can significantly improve a company’s support processes – it saves time and reduces costs through automation.
  • Hyper-automation is necessary to scale with AI.
  • Contextual marketing plays well to drive adoption by customers.
  • Boost adoption by giving power to users to get solutions faster users with self-service

To wrap it up

Self-service chatbots are becoming the face of customer support for an increasing number of brands. Today’s tech-savvy users want convenience at their fingertips and don’t mind finding solutions on their own. 

Unsurprisingly, a study shows that a whopping 79% of the majority expect brands to offer customer self-service tools to get faster resolution. AI truly holds the power to condense days long tasks into minutes.

Verloop.io uses conversational AI to build a customer self-service chatbot that handles support tickets so your team can focus on what’s important. Wondering how? 

Schedule a demo with us to live the complete Verloop.io experience today!

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