Ever feel like your world is moving at warp speed? Consumer purchasing habits and modes of communication are evolving almost as quickly as the digital platforms on which they buy goods and communicate with businesses. Online interactions have transformed from the days of simple digital sales to today’s need to offer the full digital experience, with customers now expecting more than ever.
Savvy companies are adapting to this changing landscape to keep customers satisfied. They are transforming their business models to take advantage of the digital world. In the sphere of customer experience, artificial intelligence and chatbots offer unparalleled services when it comes to creating a friction-free digital experience for customers.
Companies have no choice but to become fundamentally digital and harness the power of today’s technology. Businesses need to think about leveraging newer forms of technology and intelligence to drive the next level of customer experience or risk falling behind their competitors at an accelerated pace.
Chatbots have been around for decades. But today they’re more necessary than ever because the way consumers communicate is creating a shift in how companies provide self-service and customer experience. It’s no longer about simply accessing data, it’s about how quickly customers can get their tasks done and how seamless and frictionless that experience can be.
Consumers are increasingly becoming conversational through the use of client applications, websites, apps, messaging services, and myriad devices. This means modern communications should be less about a single conversation through a single channel, and more about having a multi-channel conversation, leveraging interest, and leveraging data to drive the next level of interaction. Today’s customers are looking for speed and convenience in each and every transaction. It’s up to you to provide them with a personalized experience that anticipates their needs. It’s time to stop asking, “How can I help you?” And it’s time to let chatbots change the conversation by taking the guesswork out of the process and knowing how to help.
Artificial intelligence and chatbots can help you by figuring out who the customer is, what their tendencies are, and providing an avenue for more personalized transactions. Leveraging data for problem solving, decision-making, learning, and speech recognition can all take customer engagement to the next level.
With every self-service technology, we look at how to reduce costs through increased automation. Since virtually every answer is possible through a self-service bot, it is counterintuitive to transfer these types of interactions to a voice agent. Therefore, in-channel agent escalation allows bots to save money by handling multiple sessions at one time — something a voice channel simply cannot do.
In the digital world, you gather a huge amount of data that you can use to better understand critical data points and gain competitive insights. This data makes it easier to identify friction points within the customer journey and figure out how to help customers complete their interactions with as little hassle as possible.
Making sure agents are well positioned in the new digital world and ensuring they can work alongside this new technology is important. Chatbots can take on the task of handling lower- value interactions, allowing agents to focus on high-value jobs and increasing employee satisfaction. Additionally, being able to escalate customer issues along with the entire context of the interaction to an agent when needed can help increase both customer and agent satisfaction.
It’s important to figure out how chatbots fit into your company’s customer engagement environment, why chatbots are the future of market research, and how they’ll best be used. What level of engagement do you need?
If your company needs basic information provisioning, or a solution for a single question-and-answer session, you can use a bot that offers natural language in order to provide a simple, straightforward response. Example: What’s the shutter speed on this particular DSLR camera?
The second level of chatbots helps companies leverage data about the customer in order to provide more complex responses. If a response is dependent on a customer’s profile or other back-end information, this type of bot will gather the information before providing a reply. If someone is logged into a customer portal, for example, the bot will be able to use their data to determine the correct response. Example: What’s my overdraft limit?
This advanced level of chatbots is more about helping customers complete their journey than providing basic answers. These chatbots can help execute transactions on behalf of the user when there is complex intent with particular topics and goals. This is best for non-linear, conversation-based transactions. Even if the interaction must be escalated to a web agent, that agent will have the entire context of the conversation and will be able to complete the customer’s journey with minimal friction.
Example: What’s the best credit card for me?
Can you help me apply for the credit card and answer questions along the way?
How to put everything together and deploy chatbots in line with the customer engagement framework:
Thinking ahead helps businesses derive intent from data, context, and natural language. Understanding customer intent can help you decide how to interact with them, and can help chatbots figure out how to engage with customers based on those intentions and needs. Rather than interrupting customers with a bot as soon as they access your website, you’ll be able to use analytics such as profile, interaction, and relationship to better understand what the customer is looking for and act accordingly.
Once you understand what the customer intent is, it’s important to figure out how to engage customers with the best experience possible. By using the same data points, including profile, interaction, and relationship, you can figure out when to prompt the customer in order to resolve the interaction. Should you interrupt the customer while they’re shopping, engage them on the existing channel, or perhaps continue the process later on a different channel?
Essentially, chatbots should be able to provide the best channel treatment and offer an easy escalation path to chat with an agent, when appropriate. Bots should be made for multi- channel engagement and should be able to follow customers across time and channel with context.
It’s important to consider how you can use machine learning, analytics, and crowdsourcing to help your business in the future. Thanks to their self-learning capabilities, bots can identify new trends and intents based on today’s trends and those of the future. A particular pattern of interactions, for example, provides self-learning mechanisms that improve intelligence, as well as offer the customer the next level of experience in the future.
Chances are you’re thinking about implementing a chatbot, or have already done so. If not, your competitors likely are. Even if you’ve already started down a path, it’s important to know where bumps can arise. [24]7.ai can help you work out what the best chatbot strategy is for your business.
