When we think of artificial intelligence (AI) or analytics, a lot of the time we’re met with the idea of robots processing massive sets of data in the blink of an eye. While the image isn’t too far off what the latest advancements in AI are producing, the key point here is understanding what data, out of the many, is useful. And what can be leveraged to improve certain key performance areas (KPAs) for an organisation.
In this blog, we focus on one KPA that is of growing interest for organisations wanting to maintain a competitive advantage: customer experience (CX). How can implementing artificial intelligence and analytics allow us to understand how to empower our CX agents and in turn, harness the power of a satisfied customer?
The relationship between artificial intelligence and data collection
In short, artificial intelligence is powered by data. AI-powered services require data to be able to accurately interpret their ‘next best action’. Say for example a conversational CX agent like a chatbot is implemented to reduce average handling times in your contact centre. Why do chatbots need data? To know what customers are asking of them and to know how to answer back correctly.
The data could be simple, like a list of possibly asked questions and the answers to those, or, could be ingestible data like a book, manual or set of web pages. That is, a chatbot that uses artificial intelligence uses data to familiarise itself with customer language, learns how to efficiently map these to correct customer intent.
Features like ongoing supervised learning are a great way for automated CX agents to learn how to best match intents with the language used by customers. Understanding how a human administrator responds to a question the automated CX agent couldn’t answer means the next time a similar question is asked, there is a higher chance that it might.
Think of it this way, the more data an AI-powered system, program or software is provided with, the more capabilities it can develop. You don’t even need to have your CX agent fully optimised in data collection or AI-powered learning protocols to start. The development from your side can continue post-deployment.
You cannot have one without the other. AI empowers data analytics just as much as data analytics empowers AI capabilities. The success of both relies on the other and in terms of customer experience success, Servion Global Solutions predicts AI will power 95% of all customer interactions by 2025.
What is a customer experience agent?
Customer experience agent and customer service agent go hand-in-hand: they mean the same thing. Their job is to provide support to customers who have queries, concerns, questions or problems associated with a product or service offered by an organisation. You can hire human CX agents who work in your contact centres or even implement automated CX agents like voicebots or chatbots that take care of queries.
How artificial intelligence can improve customer experiences
So how can organisations use artificial intelligence and the data analytics that come from it to deliver a better customer experience? It all starts with implementing artificial intelligence that collects the right data for your CX goals.
Businesses that combine their operations and CX through a data-driven approach are more likely to reap their desired benefits according to a study by Capgemini. Investing in AI-powered automation solutions like Oration, can provide features that are already embedded in the software to extract data and further help the AI-powered CX agent improve.
An example feature is advanced speech recognition which enables natural spoken language to be interpreted and converted into text by the CX agent, so it can be used to apply caller intents and extract information. Another key feature for CX improvement includes automatic KYC verification which has your CX agent automatically asking and confirming identification questions without agent involvement and can integrate voice verification technology to match callers with their stored voiceprint.
AI can help your CX agents save valuable handle time in contact centres by performing the identification and verification of callers. Along with using typical verification questions, optional voice biometrics allow callers to be validated simply by saying their identity numbers, adding an extra layer of security and improving caller experience.
Leveraging analytics to create powerful customer connections
Designing the customer journey comes down to data. Data that has stemmed from an analysis of surveys, social media, ratings, payments, website visits, the list goes on. The customer journey is the path or places of interaction your target consumer has with your organisation. So you’ll want to extract data from every single one of these touchpoints and create an informed conclusion on how to improve the CX at each one.
Let’s take a point of your customer journey, your contact centres, and delve into how AI could assist in enhancing CX here using Oration as an example. Oration is driven by the most advanced AI-powered speech recognition technology. It can create useful graphical user interface dashboards that intuitively build and manage different customer journeys and generate insightful reports on call routing solutions for your contact centre. Not only that but thanks to AI, it can generate reporting insights that allow contact centre professionals to analyse call statistics and gain a deeper understanding of top caller intents and AHT. This, in turn, can be used to influence changes to the customer experience.
Artificial intelligence and improving contact centre performance
Be it data-driven CX agents or intelligent reporting, artificial intelligence can do more for your overall customer experience by having positive effects on the efficiencies of your contact centre as a whole. AI features like intelligent call routing can ensure huge volumes of calls received by contact centres are quickly matched to the right outcome every time. This can be a valuable benefit in times of increased call volumes.
During peak times, having AI that can see what a caller has said before they pick up a call, like with Oration’s contact centre agent view, means they’re well prepared to quickly resolve queries without asking callers to repeat information.
What are the benefits of AI-powered customer experiences?
Now that you understand how AI can help customers and help contact centre agents, what about the benefits received by the organisations that implement these systems?
AI-powered chatbots can be made to ‘work around the clock’. That is, online and available to answer queries 24/7 and if the customer needs to be referred to a live agent, AI can be used to program these online agents to store customer details so a human agent can assist in the future. With 90% of customers rating an immediate response as essential or very important when they have a customer service question, this can be a game-changer.
Get more bang for your buck
Organisations are also on the lookout for ways to minimise costs and maximise revenue. AI has the ability to automate workflows and attend to more customers in less time than it would for one human CX agent to do. This can allow your live agents more time to look after the customer queries that go beyond the scope of your AI-powered chatbots and voicebots.
Bots will never be overloaded. It means that their functionality can be scaled to meet the needs of a growing customer base as well as learning how to deal with more complex queries… all at the same time thanks to AI. For organisations, this can mean reduced recruitment and hiring costs as the need to hire extra staff for increased enquiry volumes is no more. Overall staffing costs go down as the bot becomes more efficient, reducing the need to hire more employees. Tier 1 queries can be handled by AI-powered chatbots that filter the majority of customer problems while becoming more intelligent the more interactions it filters.
Data delivers the ultimate customer experience
Having AI-powered CX agents or a contact centre run on efficient data collection and analytical insight translates to a smoother and more efficient customer experience. The data extrapolated can help personalise customer interactions and make them more convenient for consumers.
It saves time for the customer having to not answer as many questions as artificial intelligence can predict their issues from past interactions or similar consumer queries. On the other side, it saves time for contact centre employees to get access to the right information to service consumers based on AI analytics and can then move on to the next customer more efficiently.
Without this data, without this implementation of effective AI systems, organisations will be left behind in the race to satisfy customer demands for customer service.