7 Steps to Deploying AI-powered Self-service during the New Normal


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TechSee describes how to successfully introduce AI-powered self service
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It’s no surprise that AI-powered self-service is gaining traction with customers. Even before the pandemic created a New Normal, 73% of consumers said they wanted to solve their issues on their own without having to engage with a human customer service agent. Now, with social distancing on everyone’s minds, more customers than ever are prepared to use self-service tools to avoid technician visits. According to a recent survey, 51% of consumers claim that they tend to resolve more issues by themselves during the pandemic.

Beyond consumer preference, companies are increasingly relying on AI-powered self-service to drive operational efficiencies. COVID-19 has forced many companies to transition their contact centers to a WFH model, and self-service goes a long way toward alleviating pressure on a scaled-down workforce. If your organization is contemplating whether now is the time to implement self-service for your customers, consider Gartner’s data showing that by 2025, customer service organizations that embed AI in their customer engagement center platforms will increase their operational efficiency by 25%. The time to act is now.

Here’s how to move forward with AI-powered self-service during the New Normal

1. Determine the strategy

Every good solution starts with a plan. Decide what business problem the conversational AI assistant is being built to solve, and be clear about the desired results and the relevant KPIs. Some organizations may want to reduce inbound calls to human agents, others may wish to increase outbound calls to head off product returns, while still others may want the conversational AI assistant to make it effortless for customers to access information about the company. Whatever the reason, make sure your organization does not lose sight of its goal as development gets underway.

2. Find low-hanging use cases

Choose the right use cases by looking at which business processes can be automated with the AI assistant and consider each one in terms of volume and complexity, such as whether the task is informational only or whether it is transactional and requires interaction with other company systems. It is also essential to assess the level of engagement needed with a customer, such as whether a back-and -forth dialogue will be required to find the resolution. Most organizations are advised to start simple by keeping the task informational only and limiting the level of engagement. Ongoing analysis will help fine-tune the self-service AI use cases and uncover any gaps.

3. Design the AI assistant’s personality

When designing the conversational AI assistant’s responses, don’t go for dry or boring. Aim for high-quality dialogue with character. Whether witty or even slightly cynical, having an AI assistant that can engage the customer will bring them back repeatedly, furthering the adoption of your organization’s offering.

4. Train for accuracy

When training the algorithms, make sure that the activities are centralized and not developed in a silo. Key staff should be involved in the training to make sure all the important points are covered. Keep in mind that your AI assistant is meant to enhance your human customer service agents, and not to replace them. Use the manpower you have to best position your AI assistants to help scale your customer support capacity by automating routine inquiries and tasks.

5. Analyzing performance regularly

Once the AI assistant is deployed, the organization cannot rest on its laurels. It is critical to measure its performance to drive improvements. It’s not enough to analyze whether the original business case is being met; rather, it is important to integrate performance metrics with other customer care center KPIs, such as call deflection rates, total cost per contact, fulfillment speed, customer satisfaction and, of course, success rate.

6. Enhance your virtual assistant’s capabilities

Once the basics are covered, your customers are using the AI assistant and you’re seeing ROI, it is time to expand and enhance the capabilities of your AI in offering. Consider enabling the AI assistant to answer a text message, suggest a product for purchase or find the customer the best rate available. Implementing Computer Vision AI gives your chatbots the power of sight so they can handle more use cases. If brands can use Computer Vision to see issues and understand customers on an individual level, they can deliver more personalized marketing, sales, and service.

7. Drive adoption through targeted marketing

Aside from bot’s service performance, another area to measure is the growth of customer uptake. To achieve optimal adoption, your company must get the word out. An ongoing marketing campaign should stress the availability of the AI assistant and the benefits of using it. Agents themselves can be the chatbot’s ambassadors by letting their customers know that they could have accomplished the task at hand in self-service.

Benefits you can expect from deploying AI-powered self-service

With the fear and uncertainty caused by the pandemic, contactless self-service that addresses customer safety concerns is fast becoming more of a must- have than a nice-to-have. With 68% of customers reporting that they would be more loyal and give preference to companies that go further to ensure safety in technical support, enterprises that provide self-service options will achieve the service resilience – and cost optimizations – necessary to shrug off the effects of COVID-19 and emerge even stronger than before.

This post was first published on the TechSee blog.

Liad Churchill
Passionate about turning complex technologies into compelling stories that deliver business value, I’m a multi-discipline product marketer with over 15 years’ experience at B2B tech companies. I bring a strategic analytical perspective, creativity, execution skills, and rich global customer-facing track record. With deep knowledge of data analytics, cyber and AI, I’m a copywriter at heart, specializing in presentations and keynote speaking. I lead marketing at TechSee, a growing startup that’s shaping technical support with a game-changing solution based on AR and Computer Vision AI.


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