Why Self-Service Needs a Human Touch


Why Self-Service Needs a Human Touch

How to make self-service live up to its promise.

Self-service has emerged as a key contact center strategy, both in terms of improving the customer experience (CX) and reducing cost in the contact center. Yet the delivery of self-service still hasn’t lived up to the promise.

In today’s digitally centered world, a consumer can order the day’s groceries online before their workday begins, run to pick them during a lunch break, and make a bank transfer or a healthcare claim on their phone while they wait for the groceries to be put in their car.

More and more, digital touchpoints are central to the CX, and the demand for 24/7 self-service channels is soaring.

More than 80% of customers will try self-service first, which explains why 80% of enterprises have some self-service offering, according to Forrester. Yet Gartner estimates that only 9% of inquiries are resolved in self-service, which means that 91% end up in live service, which costs 100x more than self-service.

“While there will always be live service, that type of service should be treated like a precious resource,” notes Gartner, rightly. The percentage of successful resolution in self-service represent only the most basic inquiries: the rest use precious live resources.

As the number of channels for customer service proliferate and customers use them all, maintaining happy customers across the channels gets even more difficult: and expensive. The need for an effective customer service channel strategy is key: and self-service plays a vital role.

What’s Been Holding Self-Service Back?

Traditional self-service models are manually created by using a narrative approach, meaning humans guess which phrases customers might use to express intents (i.e., the assumptions made about what a customer is intending to accomplish).

But the narrative approach is reactive, time-consuming, and inaccurate. The results are not only poor outcomes and decreased customer satisfaction, but a huge spend going to outside resources and management consultants in efforts to improve containment.

And by continuing to analyze failed self-service interactions—focusing on where it went wrong instead of mining the intelligence around where it went right—companies are doomed to repeat their mistakes.

What if companies pursued a data-driven approach that took the insights from employee-assisted interactions to learn where self-service channels can improve?

If instead of guesswork, we used customers’ experiences with humans—the Voice of the Customer (VoC)—to understand their needs and adapted self-service to fit their intents? This is what’s possible with Enlighten XO from NICE.

Mine Your Most Valuable Data Source

To drive improvement in self-service, it’s important to include the most valuable data source you have in the contact center, namely human conversations. By leveraging artificial intelligence (AI) and analytics, contact center leaders can use data from employee-assisted interactions to drive intelligent self-service.

Enlighten XO builds smarter self-service channels by automatically generating insights from human conversations on any channel. The insights transform self-service channels with a data-driven, empirical approach that continuously updates with every interaction.

Enlighten XO discovers customer intents from human conversations, uncovering thousands of training phrases that pinpoint each customer’s needs on every touchpoint. The data-driven approach means more precision, new insights, and no more narrative guesswork.

Enlighten XO identifies and prescribes the best self-service opportunities. Its AI-driven automation scores identify customer intents with the greatest return on investment (ROI) for self-service, making it easy to know where to focus. Further, Enlighten XO automatically understands the detailed conversational flows that model the ideal resolution paths.

Customers and businesses constantly change. What if your self-service could keep up with the rapid changes in your business? Enlighten XO continuously updates so you can adapt self-service to match your changing business needs.

For example, if there is a new campaign driving an increase in live customer service, with Enlighten XO you can easily identify the newest customer intents, quickly update self-service for greater coverage, and improve resolution through digital channels.

Serving Up Success with Smarter Self-Service

Leading healthcare company improves csat in digital, while keeping up with changing benefits

THE CHALLENGE. Traditionally, healthcare insurance choices were relatively straightforward: medical, dental, and vision plus individual or family, and finally HMO or PPO.

Nowadays, choices have exploded. There are insurance markets, premium or high-deductible plans, HSAs and FSAs…you can even insure your pet! If humans can barely grasp the complexity, how are chatbots supposed to comprehend?

A Fortune 100 healthcare company needed to keep up with this complexity in its self-service channels, making it easier to answer benefit questions 24/7, while reducing the operational load on the call center. But where to start building automation and keep up with the changing benefit landscape in the self-service channel?

THE SOLUTION. The healthcare company deployed Enlighten XO to the largest contact center handling member inquiries on both chat and voice channels. They used Enlighten XO to:

  • Listen in on the human conversations to identify the best place to start automation
  • Identify the questions members had about the new benefits and how they asked those questions
  • Understand what responses were making customers most happy and ensure that’s how the chatbot was programmed to answer questions
  • Apply the insights from Enlighten XO to streamline the development of new intents

THE RESULTS. With a data-driven approach, the insurer brought their self-service to the next level. The highlights include:

  • Improved member satisfaction on the digital channel
  • Reduced volume on HSA and FSA benefit calls, which were top priorities for automation
  • Faster cycle time to release a new intent, saving hundreds of hours per month

Household media company adapts to reduce friction, maintain competitive edge in a hot market

THE CHALLENGE. Today, consumers have more media options than ever before. Not only are there more products and providers, but consumers can change who they do business with, often with the click of a button.

In an effort to keep up in this fiercely competitive market, a major media company was running various promotions at once to win customers.

Yet handle time on sales calls was going up. And the self-service channel wasn’t carrying enough of the load.

THE SOLUTION. The media company turned to NICE for help, rolling out Enlighten XO to the 500 sales professionals on the voice channel. The goal was to understand the customers’ questions about the promotional offers that were driving up handle time before the sales.

The professionals could learn from the best agents how to effectively communicate the fine print behind the promotional offers.

For example, it was unclear whether there was a commitment period with one of the promotions, which drove up call volumes. The company was able to not only identify the issue but communicate to Marketing to clarify the offer in future ads.

Additionally, the company could train product-specific chatbots with new intents focusing on the promotional terms, along with the ideal resolution paths.

THE RESULTS. The media company was able to identify points of friction and improve across all channels:

  • Handle time started to decrease shortly after each chatbot was updated with new intents
  • Conversion rates slightly improved or remained steady
  • Expanding solution to service channels

Large bank improves self-service using omnichannel insights

THE CHALLENGE. As interest rates hit record lows, this bank saw an increase in refinance applications: and an increase in handle time and customer frustration as their existing self-service systems could not keep up.

The team responsible for the CX evaluated previous self-service interactions but found no clear improvements to make. To improve self-service, they needed to understand what customers were asking, the best resolution path, and the changes needed in the self-service system to get there.

But if not within the self-service system itself, where are the insights for improvement?

THE SOLUTION. To learn from the VoC across all interactions, the bank’s CX team partnered with NICE to gain new self-service insights from Enlighten XO.

With data-driven insights, the bank’s self-service development team know exactly where to focus their efforts to improve their customers’ digital experiences. They quickly learned the highest priority questions from customers and the specific training phrases to include in the self-service channels.

With AI, Enlighten XO identifies specific insights from every interaction for every customer need, task, and conversational turn. Using the VoC the bank gained a new understanding for the driver of each customer’s outreach on the refinance application process.

THE RESULTS. By streamlining refinance applications in self-service, the bank realized:

  • Faster development time via data-driven approach: no more guesswork
  • Improved self-service containment with better digital resources for customers
  • Increased CSAT by improving customers’ experiences in the self-service channels

Power Digital Transformation with AI

The heart of Enlighten XO is powered by Enlighten AI, the first comprehensive framework for the CX. It is a set of purpose-built AI technologies that make every CX application and process smarter in real-time.

Developed from more than 30 years of industry expertise and using the largest syndicated interaction dataset, an array of self-learning AI solutions are embedded across the NICE product portfolio and delivered out-of-the-box.

Learn more at www.nice.com/EnlightenXO

Andy Traba

Andy Traba is a Director of Product Marketing at NICE. As an innovator in the field of behavioral analytics, Andy has been instrumental in the creation, go-to-market strategy, and evolution of personality-based products that decode the chemistry of conversations.