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Will Old Internal Systems Destroy your Conversational AI Dream?

By Mandy Reed, Global Head of Marketing

Microsoft announced this week that they will stop supporting Windows 10 in 2025, with no new updates or security fixes being released after 14 October. This news comes as the company plans to reveal a new Windows operating system later this month. Screenshots of the new Windows 11 have been leaked online ahead of that virtual event – you can check them out here.

Whether you’re a Windows user or not, this type of announcement can highlight the need for wider discussions about the technology and systems being used internally at your organisation. Are you one of the many companies that relies on old or out-dated solutions? These legacy systems can have a knock-on effect, sometimes creating issues when the restrictions they create aren’t acknowledged at the start of a digital project or even keeping organisations from embarking on new projects at all.

For example, this can be the case when deploying an internal conversational AI solution for employee support. As virtual agent and chatbot expert, Peter Studd explains in a conversational AI guide:

“It’s very important to be aware of your users’ technology when you’re implementing a virtual agent to ensure it will be compatible. For example, it’s not uncommon for large companies to have very old systems and browsers that are still being used companywide. This can cause issues if not taken into consideration when developing an internal virtual agent.”

Constraints created by old systems and browsers don’t necessarily mean you need to abandon your plans for an internal virtual agent. However, they should be identified and discussed at the beginning of your project to avoid any unwanted surprises. If not, you could find that you’ve invested time and money into a solution that can’t be properly integrated with an important legacy system or isn’t user friendly for employees using older browsers.

This is just one of the downsides of taking a DIY approach to building and deploying a chatbot or virtual agent. If you don’t have people with the right experience on this team, it will be easy to miss or overlook older systems that could create project roadblocks. You end up with a case of ‘we didn’t know what we didn’t know’ and a tool that doesn’t meet expectations.

An experienced conversational AI provider will know the right questions to ask to help you pinpoint any potential compatibility issues upfront. They’ll provide guidance on any changes or accommodations you may need to make to your plan. They’ll also be able to offer suggestions for ways to work with potential constraints based on a deep knowledge of their technology and prior experience with similar challenges.

In an ideal world, all of the systems and technologies being used by your organisation would be up-to-date and easy to incorporate into new conversational AI projects. Since that’s not likely to become a reality any day soon, the best course of action is to work with a provider that can not only help you identify potential challenges but also provide the guidance on how to overcome them. Old internal systems don’t need to destroy your conversational AI dream.

Is Your Inexperienced Approach to Self-Service Driving Customers Away?

By Mandy Reed, Global Head of Marketing

As many people around the world reflect on more than a year of pandemic-related lockdowns, restrictions, and public health measures, it’s impossible not to marvel at how we all adapted to our current reality. This has involved a lot of trial-and-error as we learned new skills and created new routines in both our personal and professional lives.

Trial-and-error is important to our individual growth and life in general. However, when it comes to areas like customer support, using a trial-and-error approach can have a devastating effect on your customer experience. And it is no secret that poor experiences can lead directly to customer churn and lost revenue.

Perhaps in the early days of limited in-person interactions and surges in calls to contact centres, customers were more understanding about long wait times or out-of-date self-help content. The attitude of ‘we’re all in this together’ extended to giving companies a little space to try some trial-and-error to get their support experience right. If that grace period did exist, it is now long over!

During the past year, more customers have turned to digital channels and automated self-service for support. Usage of virtual agents and chatbots exploded with record-breaking levels of traffic. Customers expect these conversational AI tools to be easy-to-use, convenient, accurate, and reliable. When built and maintained properly, they are all those things.

Unfortunately, not all companies tackle the implementation of conversational AI solutions with a realistic understanding of what it takes to make them successful. Instead, they take a DIY approach with limited internal knowledge and experience. This requires a lot of trial-and-error which creates poor performing tools and frustrated, unhappy customers.

As Claudio Chico, Development & Support Technician at Creative Virtual, explained in a recent conversational AI guide:

“A proper business virtual agent has many parts and building one involves knowledge in many areas. If any part is new to you or you aren’t extremely familiar with the tools you are using, you’re stuck applying the principles of ‘hoping this works’ and ‘changing stuff and seeing what happens’. When you outsource this to an experienced provider, you get a whole team of people who not only know what they are doing but have done it thousands of times. They have a deep understanding of how to use their tools and how they work, so nothing is a mystery anymore.”

Part of the underestimation of the importance experience plays in successful conversational AI projects stems from a misconception that chatbots and virtual agents are new self-service solutions that burst onto the scene several years ago. If this is new technology, then surely everyone is inexperienced and utilising a trial-and-error methodology, right? The truth is this technology has been used in areas such as website self-service for over two decades.

Even though these self-service tools may be new to your company and team, vendors like Creative Virtual have years and years of experience with delivering successful solutions. This means that forward-thinking companies – perhaps even some of your competitors – have years and years of experience with offering successful solutions. It also means that customers have used those successful solutions when engaging with other businesses and will use your chatbot or virtual agent expecting the same level of reliable and accurate self-service.

When it comes to creating positive customer experiences and getting the most from conversational AI technology, there is no substitute for having hands-on experience with building, integrating, installing, maintaining, and expanding virtual agents and chatbots. An inexperienced, trial-and-error approach doesn’t drive success. It drives your customers away.

Download the Guide to Selecting a Virtual Agent or Chatbot Vendor: Forget the Technology & Focus on Experience whitepaper for more tips from industry experts.

Also check out the ISG Provider Lens™ Intelligent Automation – Solutions & Services report for the analyst group’s independent evaluation of the conversational AI market and vendors.

Bottom line: Work with an experienced team to deliver your company’s self-service solutions and leave the trial-and-error for finding the most flattering lighting for your next Zoom meeting or testing the best ways to trick your kids into eating their vegetables.

How Much Does it Cost to Make a Chatbot that Actually Works?

By Paulo Barrett, Chief Operating Officer

Ask any seller of a highly complex and customizable chatbot or virtual agent system about cost and you’re likely to get an evasive answer. ‘There’s no one-size fits all.’ ‘I’d need to talk to you on the phone to give you an accurate quote.’ Increasingly, in this ever-saturating market, it’s easy to find elements of chatbot pricing (i.e., API request fees) or flat monthly subscription costs for low-end systems, but who is giving the educated bot buyer a clear, top to bottom view of what it costs to build a system that will really work?

By ‘really work,’ I mean one that will materially contribute to cost savings, improve customer satisfaction, and maybe even generate new revenue. In other words, how much is it realistically going to cost to build a bot your customers will actually want to use.

The truth is, building a successful chatbot is not purely a question of technology. Whether you are buying a platform to BYOB, getting something cheap and cheerful off the shelf, or looking for a bot consultancy to support your internal efforts, your work is really just beginning once you have the system configured and deployed. The ongoing work to improve the chatbot’s performance and to get the best out of self-service in your unique deployment is what makes the difference.

It can be difficult to predict exactly what actions your customers will want to take in the beginning. That means being able to take an informational system and swiftly evolve it as desired customer outcomes become clear is key for success. This is enhanced by using great technology, of course, but ultimately, you need the right experts (internal or external) to separate your deployment from the crowd of others (often failures) which are flooding the support world.

Think of it like buying an instrument. No matter how expensive or special it is, either you learn to play it, or you get someone else to play it for you (alternatively, it ends up gathering dust and doing absolutely nothing for anyone). One way or another, this expert training costs time and money. You have to weigh this investment against the return.

Now to the million-dollar question … pun intended. What will a chatbot that your customers actually want to use cost for a large enterprise? While it’s true that most deployments are unique to every client and require some customization, there are some standard pricing building blocks you can expect to see.

The first cost to nail down is the pilot fee. How much am I gonna spend to test this thing out and see if it works for me? The financial risk associated with a pilot should be shared by the customer and the vendor and typically runs around $50,000 (USD). While the client assumes some risk via the initial cost, you should expect this to be credited against the cost of the full production-level deployment if you choose to move forward. This fee will cover all hosting, software deployment, content development, technical consultancy, and transactional fees for the agreed period. Typical pilots run 30-60 days from go live to give you enough time to see material results and make a decision about the ongoing plan.

Once you convert from pilot to full system (we pride ourselves on a +90% conversion rate!), you have some choices to make about how you pay for the tools and ongoing consultancy. Some customers wish to be purely pay-for-performance. Often, they go with a tiered model based on volume with session costs starting at a dollar (i.e., a single interaction with a user, with unlimited question/integration calls in that session). This per session cost may fall based on meeting certain volume thresholds. With any variable pricing model there are pros and risks for both the customer and the vendor.

If you prefer not to have a variable rate in your forecasting, you can purchase a more traditional software/services package. A standard production system should include integration with a live chat platform as well as your CRM. This will ensure your customers get personalized answers to their questions and are able to complete transactions with the bot online, rather than just receiving flat, informational content. The cost to provide the software and ongoing consultancy, along with an adequate knowledgebase of 100-200 solutions, will generally cost somewhere between $150,000 and $250,000 (USD) per annum, depending on the number of sessions.

While this may seem like quite the investment, you have to ask yourself: What is the cost of deploying a support tool that my customers don’t want to use and delivers a negative, frustrating experience?

Ready to learn more? Our team is always on hand to arrange a personalized demo with you and answer any questions you may have about getting started with your pilot.