Posts

Integrate Your Way to a Better Self-Service Experience

By Mandy Reed, Global Head of Marketing

If you give visitors to your website the option to self-serve with a chatbot or virtual agent, kudos to you for recognising the importance of easily accessible digital support! Both current and potential customers appreciate being able to engage with automated self-service anytime, anywhere. However, what they don’t appreciate is thinking they are going to have an easy self-serve experience only to discover your chatbot is ill-equipped to handle anything beyond a simple question and answer pair.

I’ve been in the chatbot and virtual agent field for over 13 years and have the privilege of working with many colleagues who have over two decades of experience with the technology. Back in the early days, all chatbots were very simple question and answer tools. Rachel Freeman, Operations Director at Creative Virtual, has talked about starting in the industry in 2000 “when the focus was marketing and the novelty of the service was almost as important as the aim to increase ‘website stickiness’.” Major advancements in the technology have propelled the capabilities of today’s chatbots far ahead of those early deployments.

Unfortunately, there are still many chatbot platforms on the market that operate as simple question and answer tools with very limited conversational capabilities and integration options.  While there are specific use cases for these types of bots, quality customer self-service is no longer one of them. You will never be able to deliver the experience customers are looking for if you don’t have a tool built with an advanced conversational AI technology and the ability to be integrated with other systems.

Why is the ability to integrate your chatbot or virtual agent with other backend systems so important? Without those integrations, you are unable to deliver personalised responses for authenticated users. You can’t seamlessly escalate users from the virtual agent to a live chat agent. You don’t even have the option to deliver updates in real-time from external information feeds. All these pieces of functionality are now part of users’ expectations when they engage with your chatbot.

Given those expectations, what sort of systems should you consider integrating with your conversational AI tool? The integrations you select will depend on your self-service use cases and customer needs. Think about integrating with live chat, CRMs, voice technologies, knowledge management platforms, digital payment systems, community forums, ticketing systems, user survey tools, and contact centre platforms. Your goal should be to implement integrations that enable both you and your users to fully take advantage of the benefits of today’s conversational AI capabilities.

The big question then is: how should you go about upgrading your simple Q&A bot to an effective and integrated conversational AI tool? An obvious first step is to determine if your current chatbot platform supports the integrations you want. If not, find a more advanced platform that will allow you to create those connections. Jumpstart your upgraded tool by repurposing what you already have with your current project.

Once you have a chatbot management platform that gives you the integration and customisation options you need, don’t feel pressured to do everything at once. Take a staged approach, starting with the integrations that will have the biggest impact on improving your self-service experience. Then gradually add additional functionality to create a tool that is built for your specific needs and goals. Don’t forget to periodically review your conversational AI plan and make adjustments as your business and customer needs evolve.

We all know from our own personal experiences as customers how influential the support engagements we have with a company can be in our purchasing decisions. Take a few minutes to test your organisation’s digital self-service from that perspective. Are you delivering a seamless and personalised experience with your chatbot or virtual agent? If not, then it’s time to revisit your conversational AI strategy and identify what integrations could improve your self-service.

Gone are the days of siloed, disconnected customer service chatbots. To deliver the conversational AI engagement customers want, expect, and appreciate, you must integrate your way to a better self-service experience.

Solving Common Conversational AI Project Issues

This post was originally published on AI Time Journal.

By Chris Ezekiel, Founder & CEO, Creative Virtual

Back in 2019, I wrote an article on reasons why chatbot projects were failing or being abandoned before they even reached the testing stage. At the time, the conversational AI industry had been saturated with both false promises about the capabilities of the technology and a plethora of new start-ups with misleading claims about having AI-powered customer service bots. That left the chatbot and virtual agent landscape littered with poor-performing and failed projects along with negative press about the technology.

Fast forward to 2022, and much has changed in the world of conversational AI. One important change is the widespread acceptance that pure AI is not the right answer for automated customer service and employee support. Industry experts, analysts, and vendors (including those that previously claimed otherwise) now agree that a combination of humans and AI is the best approach to these chatbot and virtual agent solutions. This is coupled with important advancements in conversational AI technology that allow for the right balance of human and machine to create positive support experiences.

Conversational AI is now widely recognised as an important technology in digital customer experience and employee support strategies. During the pandemic, chatbots and virtual agents were a crucial tool for some organisations to meet the challenges of serving customers quickly and efficiently during a time when contact centres were overwhelmed and information was changing rapidly. These success stories demonstrate just how essential conversational AI technology is for successful digital strategies.

Yet despite all those success stories, some organisations are still struggling with a chatbot that’s not performing as expected, can’t be scaled as their business grows, or doesn’t properly reflect their brand. Over the past couple of years, I’ve heard a variety of reasons from business leaders on why their company is unhappy with their conversational AI tools. Here are the six most common issues they cite:

  • I can’t expand my solution to support my growing business and customer base.
  • I have limited integration options to create a seamless and personalised experience.
  • I started my project with an inexperienced start-up that isn’t able to provide the technology updates and support I need from my vendor.
  • I am struggling to manage multiple chatbots across different business divisions or departments.
  • I am unable to staff my chatbot project with internal resources with the necessary knowledge and experience.
  • I don’t own the user interface or training data with my current chatbot provider.

In those situations, it can be easy to mistakenly dismiss the technology as ineffective. Don’t fall into that trap! Instead of abandoning your investment and writing conversational AI off as a poor fit for your strategy, you need to engage with a vendor that has the tools and experience to get your project back on track.

My first recommendation for transforming a tool with any of these issues is to find a vendor that can leverage what you already have from your existing project or projects. You want to rescue your investment, not start over from scratch. If a vendor doesn’t have technology sophisticated enough to do this, then most likely their solution isn’t going to work for you in the long run anyway.

My second recommendation is to be very clear – both internally and with the vendor – about both your short-term and long-term goals for your chatbot. This is what is going to drive your conversational AI strategy and technology requirements. If you don’t know what you want to accomplish with your chatbot, then you can’t properly identify the functionality, integrations, reporting, etc. you need from a vendor.

And my third recommendation is to ensure you’re selecting a vendor with the right experience and expertise. You want to collaborate with a provider that has solved your issue before, understands the specific needs of your industry and/or use case, and has the references to back them up. Ask to talk to their current clients so you can hear first-hand from them what it’s like to work with the vendor.

If you’re interested in learning more, Creative Virtual has put together an eBook – Conversational AI Issues & Solutions – that talks about each of the common issues I listed above in more detail.

My overarching advice is: Don’t let any of these issues signal the end of your conversational AI project. Leverage what you already have to transform that project into the successful and valuable digital support solution your organisation needs.