But with the sudden popularity of ChatGPT and similar programs bringing AI to the masses, companies are (or should be) taking a fresh look at how they’re implementing AI and where they can better use it to improve customer experience. The contact center houses some exciting opportunities.
Contact centers generate so many data points around customers’ behaviors, preferences, histories, and more. With AI, you can structure all of that unstructured data and draw insights to help you make better decisions and drive better outcomes.
1. Get more data and better perspective with NLPOne newer AI technology that holds a lot of promise for contact centers is natural language processing (NLP), which gives machines the ability to understand text and speech similarly to how humans can.
NLP tools can listen to conversations happening in the contact center – both the customer and the associate sides – in real time and help interpret them in a way that gives you useful insights. It works on voice calls, chatbot interactions, and other conversations. Previous tools have had similar abilities to listen in on a small sample size of interactions, but NLP can listen to a much larger aggregate pool of interactions. This gives a clearer and more objective view of interactions.
NLP uses technology to interpret what is happening and how people are feeling during interactions, so it’s less subjective and more reliable than having people interpret those things.
That said, humans are still key to ensuring you get the most out of NLP. People need to tell NLP what it should be looking for. For instance, if you want to make sure associates are giving a necessary financial disclaimer during every interaction, people must direct the technology to look for that.
And bot tuners play a valuable role by taking the trends, patterns, and other insights NLP uncovers and putting them to practical use by passing them on to the people designing chatbots. This ensures improvements are continually made and customer experience keeps improving.
2. Upgrade associate trainingAI’s ability to quickly make sense of mountains of data can improve associate experience and productivity, too.
Brands should be integrating AI into associate training. As you’re onboarding new employees, AI tools can help you make data-driven decisions, adjust trainings accordingly, shorten training timelines, and optimize associates’ speed to proficiency.
AI-powered training tools, like TTEC’s RealPlay, let associates participate in gamified, self-paced training that teaches through role playing real-life customer scenarios. They also deliver real-time feedback and coaching. And when AI takes on some of the responsibility for training associates, it frees up the people on your team to focus on more-complex training needs and issues.
By integrating RealPlay into its training, a major telecommunications firm improved its associate attrition rate by 58% while also improving efficiency by 6% and first call resolution rate by 5%.
At the same time, you’ll gain access to valuable insights. An AI training tool can tell you, for instance, if customers keep getting frustrated at a certain point in interactions or if associates continually struggle to find a certain piece of information they need. With that intel, you can fine-tune your workflows and knowledge base to improve experiences for associates and customer alike.
3. Proactively detect and fight fraudAs the world we live in becomes increasingly digital, cybersecurity attacks are on the rise and fraud is a growing concern for companies. AI can help.
AI can comb through huge amounts of data and pick up any anomalies as they occur. This gives you the ability to flag suspicious activity or potential fraud at its earliest point, so you’ll be much more successful at combatting it. Instead of learning that fraud has happened after the fact, you can detect it at the outset and stop it in its tracks.
For this to work, your AI needs to be tuned properly, which is where humans again play an important role. People need to inform AI models by setting standard deviations. Then, whenever AI detects data that falls outside those standard deviations it will sound an immediate alarm, in real time, that can trigger human fraud investigators to take immediate action.
Detecting fraud early, or preventing it before it starts, can save you valuable time and money. Having the right, secure verification and reporting processes in place, for instance, helped a large U.S. bank cut its instances of fraud by 75%.
4. Achieve smarter AI with data annotationAI’s only as powerful as the quality and quantity of data informing it, so it’s crucial to have the right datasets feeding your AI models and algorithms. Data annotation, the human-led process of labeling and categorizing data before it is fed into AI, is paramount to AI’s success.
Traditionally, brands have hired data annotators through crowdsourcing and paid them per annotation. But this outdated approach just incentivizes annotators to work quickly, which can compromise the quality of your annotations. It’s time for a new approach.
Focus on finding high-quality annotators who will perform the job with a high accuracy rate, and be sure to seek out annotators who have vertical-specific expertise that’s relevant to your business. This strategy produces results, including 98% model accuracy for one of the world’s largest online e-commerce marketplaces.
Data quality is vital to AI’s success, so it’s worth investing in data annotation.
Work with an expert partnerAI has huge potential to improve the way contact centers operate but taking the necessary steps to harness its power may seem daunting. The good news is you don’t need to do it alone.
A customer experience outsourcing partner with AI expertise like TTEC can help you identify where and how to use AI to improve customer experience, boost associate productivity, and streamline processes. The right partner will bring together the strategy, people, and technology you need to evolve your contact center with AI.