AI can be used to completely automate certain customer engagements through a virtual agent, which can be used to reduce service costs.
Artificial Intelligence (AI) opens new avenues for enterprises to automate customer engagements. These AI-fueled experiences offer inherent benefits for customers, notably 24/7 access to services, hyper-personalized information, resolutions executed at machine speed and an added dimension of privacy. Of course, like any major undertaking, a company can’t merely purchase an AI system and be done with it. Some planning, preparation and experimentation will be necessary to build the ideal experience for your customers.
Attend this year’s Digital Workforce Summit (DWS) on Wednesday, May 8 in New York City to hear stories from enterprises that have already made this journey. In the meantime, let’s review a few points for building optimal customer experiences with AI.
Identify Pain Points
When attempting to transform the customer experience (CX), the first step should be identifying the exact customer pain points your company wishes to address. This will help you choose the most effective form of AI-powered automation for your organization. Are the most pressing concerns weighing down your Net Promoter Score (NPS)? Are customers experiencing long resolution times on basic issues? Are there extended wait times before a customer can connect with a service agent? Inconvenient business hours? Something else entirely?
AI can be used to completely automate certain customer engagements through a virtual agent (VA), which can open access to a company’s digital systems and accelerate resolution times. VAs also can free experienced service agents from high-volume tasks so they can have more time to address unique or complex customer needs.
Alternatively, AI can also be partnered with your human-powered service infrastructure to make support more productive overall. For example, when a major insurance provider hired the industry-leading VA Amelia as a whisper agent, human service agents were relieved from the cognitive load, so they could utilize their uniquely human soft skills in customer interactions. By augmenting the customer service function with Amelia, the insurer was able to reduce average call times and increase the percentage of calls resolved in one session.
Get Your Data Ready
Now that you’ve made the decision to reinvent your CX using AI, you’re going to need data. Lots of it. With Machine Learning (ML) functionality, AI systems can process unstructured data to independently discern patterns that can, in conjunction with human developers, hasten the maturation of an AI-powered UX.
Take Advantage of New Functionality
Unlike static digital interfaces, AI allows for new personalization capabilities or even in some cases hyper-personalization. For example, it wouldn’t necessarily be in a bank’s best interest to engage with a recent college graduate the same way that it would with a retiree. A VA could recognize that these customers have different banking needs and therefore offer them different banking products. It also could converse with them differently as well.
These personalized experiences can take place in the user interface (UI) or at any point in the lifespan of the customer journey. For example, one of Japan’s largest telcos utilized Amelia’s technology to automate customer engagements on social media. The company not only increased sales, but the solution’s auto-segmentation functionality allowed the company to increase cost-effectiveness of its targeted marketing campaigns dramatically.
As with any undertaking involving your company, it is important to listen to customer feedback. This can be done through traditional analog methods such as focus groups or surveys. However, AI-fueled automation allows for granular analysis, delivered in real time which can be used to continually improve the CX.
For example, analytics are useful for letting you know that your customers (or even a certain segment of customers) are abandoning sessions early. If you choose a specific remedy at some point along the journey, AI can provide real-time results to see if the fix actually addressed the issue. AI can even be used to run A/B experiments with different tweaks to the CX to determine their effectiveness.