4 min read

Why and How You Need to Build a Conversational AI Business Case

People looking at a business case

Lower costs and a better customer experience. That’s what most business managers are looking to get out of their conversational AI systems. But to achieve these goals, you need to look beyond high-level metrics.

You need a detailed business case as part of your overall bot strategy. In essence, a business case provides you and your stakeholders with:

  • A detailed, data-driven analysis of how to achieve lower costs and better CX
  • The direct and measurable financial benefits you tie to your efforts
  • An overview of your costs and timeline to achieve your vision

A business case helps focus conversational AI systems — voice, IVR, and chatbots — in the right areas. It will also guide your design and delivery decisions. In the long term, a detailed business case provides you with a basis for ongoing performance monitoring and improvement.

Build Your Business Case by Focusing on Direct Financial Benefits

Lowering costs and improving your customers’ experience with your conversational AI systems are both worthwhile goals. But the financial benefits of great customer experiences are difficult to measure and especially hard to attribute to particular changes.

That’s why the bedrock of your business case needs to be financial.

Most business managers I speak to want a better customer experience, but very few have a budget line item for it. Typically, they need to pay for it through measurable cost savings.

A well-crafted business case can help you do just that. If you go to a budget holder in your organization and say, “We’ll get a million dollars more in sales if we invest a million dollars in a better customer experience,” they’ll inevitably ask you to prove it. If you explain that a recent survey shows a better customer experience creates more loyal customers, they’ll ask how much more loyalty. And how much more those loyal customers will spend. The truth is, it’s very difficult to forecast the impact of specific customer experience improvements. But you don’t have to.

Instead, get the budget you need to improve the customer experience by assuring stakeholders you’re not just going to improve the customer experience. Tell them how you’re going to reduce costs, too. Explain how the project will pay for itself based on the cost reduction alone. Then, you use your business case to back up that claim. You have to show how the directly measurable impacts of the project — reduced call volume, handling time and internal transfers — far exceed the cost. Then the customer experience benefits can be seen as a bonus.

Look Beyond High-Level Metrics When Building a Business Case

Solely focusing on high-level metrics is a sure fire way to tank your business case. If you’re only looking at containment metrics, you’re taking too simplistic an approach. That’s because many calls and chat sessions can’t be fully automated, but there are significant benefits to be gained through partial automation. If you’re forecasting financial benefits in your business case around fully automated tasks alone, you’re working against yourself.

What you really need to focus on is the customer journey. Think about the tasks your users are trying to accomplish through automation. Then, evaluate how much time automating those tasks will save your human agents.

When you build your business case with that customer journey in mind, you’re going beyond those broad, misleading metrics like containment. You’re looking at the journey, but not exclusively through the lens of CX improvements. Forecasting the financial impact of changes to the customer journey creates a much more compelling and insightful business case.

Why Detailed Business Cases Matter: A Real-World Example

Years ago, a client came to us with a business case another company had prepared for them. Our job was to deliver the system as outlined in their business requirements. We did the job as requested and completed a great conversational AI design around their specifications.

However, when the project went live, our client was upset to see that performance in one specific area of their business went down.

We traced this decline in performance back to their business requirements. It specified adding an additional step: customers calling to make a payment had to be both identified and verified. This additional verification step had the unintended consequence of causing some callers to drop off.

Remember, every question you ask customers in their interactions with your conversational AI system comes with some risk. The system may not understand what they say. They might not have the information required. Whatever the case, they may drop off, try another route, and negatively affect your bottom line as a result.

Had we built that business case, we’d have taken all of this into account — just as we’re encouraging you to do. Even though that additional verification step came with some benefits — everyone going through the contact center was already verified — the business case didn’t consider how that step would affect this particular group of users. The result was costly. The system required changes that could have been avoided had the business requirements taken that segment of users into consideration.

Four Steps for Building Your Conversational AI Business Case

You understand the need for a detailed business case. You know it’s a key step in getting the funding you’re after, and that it can protect your project from missteps caused by unintended consequences. But how do you actually build a business case?

Building a conversational AI business case boils down to a four-step process. Our video goes into each of these steps in much greater detail, and we recommend watching it after you’ve finished this article, but here’s a quick overview:

  1. Identify Automation Opportunities – Which calls or contacts are both frequent enough and simple enough for you to automate?
  2. Estimate the Number of Customers Experiencing Each Different Customer Journey – What percentage of each contact type contributes to a potential automation opportunity?
  3. Forecast the Financial Impact of Each Customer Journey – What is the value of each customer journey, and what is the likelihood of a customer taking each of these journeys?
  4. Evaluate Costs and ROI – How do the benefits of the system offset the costs of its implementation?

Build a Business Case That Works for Your Organization

Building a solid business case takes a lot of work, but it’s work worth doing. Once you have your business case, you can leverage it time and time again as a forecasting model.

Use it to guide every conversational design, technical, and strategic decision you make. Your business case enables you to evaluate the positive, or negative, impact those decisions might have on the financial benefits of your IVR or chatbot. Keep it updated as you move through delivery sprints, compare results to what was forecasted, and measure success in dollars and cents — not perceived CX benefits that may or may not get you the returns you’re after.

If you have any questions about building your business case, or if you’re interested in developing a deeper bot strategy and you need some help, let’s chat.

 

4 min read

Want Your IVR to Perform Like Alexa or Google Assistant? Here’s How You Do It.

Hands holding a Google Home mini

Consumer expectations are being set by voice assistants like Siri, Google Assistant, and Alexa. We interact with this technology every day. So do business leaders. We often hear clients complain that their own voice channels pale in comparison to the voice assistants offered by tech giants. Frequently, they assume the solution is investing in new technology.

If you want your IVR (interactive voice response) system to function at a higher level, or if you’re thinking about how VA (voice assistants) might play into your customer experience, throwing money at new technology isn’t necessarily the answer.

The platform is the foundation. It’s what you do with it that counts. Putting the right Bot Management System in place will get the most out of whatever platform you choose.

Why Just Switching Up Your Platform Won’t Solve Your IVR or Chatbot Problem

Business leaders often think “better” technology platforms will create better experiences for their customers. We know this is a myth, though. How?

Because the same platforms Alexa and Google use — Lex and Dialogflow, respectively — are available for you to build your own IVR and chatbots with. But moving to the same platforms as big tech companies doesn’t mean the problems with your IVR and chatbots will disappear. A recent study of Alexa Skills, for example, found that of the 30,000 skills analyzed, only around 37% have any reviews, and of those, only 19% had positive reviews. Poor reviews are not in short supply.

If Amazon’s Alexa Skills can vary so greatly in quality, it’s obviously not the platform itself that makes for a great experience. For all of its usefulness, Google Assistant has a lot of room for improvement when it comes to user experience, too.

We’re not saying these platforms are no good. Alexa and Google Assistant both sound great and can be used effectively. That’s not all thanks to the platform, though. It’s thanks to the fact that Amazon and Google have put in the time and effort to build great things on top of those platforms.

Google and Amazon haven’t just sunk countless hours into building these platforms, with “as many as 10,000 of Amazon’s employees” working on Alexa Smart Assistant and Echo products. They’ve invested in building the experience you love on top of them. So you can’t just “use the platform” in the hopes of duplicating their customer experience or success without also mirroring the investments they make in conversation design, speech science, programming, and analytics that deliver a great customer experience.

What you can do is what we teach — use a bot management system to get the most out of the platform you have, and only switch platforms if and when your bot strategy demands it.

What Happens When You Rely on the Platform to Do the Work?

Take some time to scroll through a few pages of Alexa Skills, and you’ll see. Those one and two-star ratings aren’t the results of a bad platform — no more than those four and five-star ratings are. You can create great experiences in IVR or voice assistants, but you’ve got to go about it the right way. Google and Amazon have been running their own bot management systems for years to create the experience that you love on top of Alexa and Google Assistant.

The developers and designers of those poorly-rated apps probably have not.

Some app developers see a great conversational AI platform and just assume that whatever they build for it will be on par with Alexa or Google Assistant because they’re using the same foundation. That’s where the rubbish skills with consistently low user ratings comes from.

These developers haven’t been paying attention to the industry for the last 20 years to see previous failures up close the way we have. It’s no coincidence that early iterations of IVR annoyed users so much. Technical limitations play a role — and frankly, voice assistant technology isn’t really where it needs to be to excel in the broad range of customer service tasks that agents handle every day — but the lack of user-centered design is just as much to blame for IVR’s early failings. It’s improved over the years, but rushing out of the gate certainly didn’t do it any favors.

Great Conversational AI Requires a Thorough Discovery Process

Let’s stop to think about what Alexa does for users. The system gives users general reminders, right? It answers general knowledge questions, and it tells you when your deliveries are due to arrive. These features aren’t something Amazon randomly decided to do with Alexa. It’s what their discovery process revealed about what their users wanted while they were hanging out in the kitchen with Alexa listening on the countertop.

Amazon came up with the bot strategy, and then they brought on a team of designers to handle the next stage of the bot management system. They’re designing great experiences, developing them, and implementing them on the platform. Then, they’re constantly looking at data to figure out where the next opportunities lie.

Using this data and doing this discovery work allows Amazon to show up for their users in the way that those users want. That’s what creates a great user experience. What is it that your users are asking for? What are multiple users looking for that your bots currently can’t deliver? Is the technology capable of automating these tasks effectively? Is the required investment justified by the expected business benefits? Answering these questions will help you discover where to focus your efforts next.

Start with the Strategy, Manage Your Bots, and Prepare for the Future

Our research shows that 51% of consumers would be likely or very likely to use their voice assistants for sales and customer service purposes if the organization they were engaged with provided that option. With conversational AI playing a bigger role in our daily lives than ever before, that’s an opportunity that shouldn’t be missed.

There’s a lot of work you can do now to lay your foundation. That way, you’ll be ready to apply your process to new channels, including VA, when the time is right.

It doesn’t matter if you’re talking about IVR, VA, or chatbots. They’re all channels that allow humans to interact with systems using conversation. And because we learn language and conversation at such a young age, we can’t unlearn it. So IVR, VA, and chatbots need to leverage the norms of human-human conversation. They need to create a comfortable, easy-to-use experience.

Start by putting the right bot management system in place, and apply this to existing platforms and channels. Because the system itself is platform-agnostic, the same system can be used to roll out capability across new platforms and other channels — once your bot strategy or conversation design demands it.

That’s how you’ll offer an experience that can go toe-to-toe with the industry leaders of today.

4 min read

How Do I Get More ROI Out of My IVR, Voice, or Chatbot Platform?

Getting more out of your IVR and chatbots

You’re expected to meet escalating customer experience expectations and manage costs at the same time. Conversational AI systems like IVR, voice, and chatbots are supposed to help, but often the outcomes don’t live up to the promise. So how can you maximize the ROI from your Conversational AI?

It’s tempting to turn to your tech team or vendor and demand better results, or look for a new platform that will solve the problem. But the platform is just that: it’s the foundation you build on. It’s what you do with that platform that nets your return.

In this article, I’ll show you how to spot the problems that might be affecting your bot workforce, and some simple techniques to coach and help them improve. Just like you would with your own team.

How Problems With Your Bots Affect Your ROI

Everybody says they want a better customer experience and lower costs. But how do you get that? The answer is to get the right team members, bots and humans, doing the right things and working together seamlessly.

The goal of your contact center is to get customers to a skilled agent who knows how to help, or a bot that can do the job just as well. Your bot workforce and your human workforce need to work together to achieve that goal. For your human agents, you’ll routinely spend time listening to their conversations with customers, watching their performance metrics, and coaching and training them to do better. You need to do the same for your bots.

What’s Causing Problems With My Bots to Begin With?

Bots can do exceptional work in the specific areas they’re designed to operate. But four organizational issues can make things really difficult for your bot:

  1. Lack of maintenance and updating. Just like your human workforce, you need to keep your bots up to date. Let them know when a new product launches, or a process changes. Your bots won’t figure these things out on their own!
  2. Uncontrolled changes. Conflicting instructions will undermine the confidence and capability of your agents. Same with bots. You wouldn’t let anyone and everyone from across the business tell your agents what to say. You need to apply the same standard to your bots. Uncontrolled changes have unintended consequences.
  3. Technology problems. Sometimes, your agents can work around problems in the CRM. Bots can’t. So watch out for changes in the backend APIs that will have Bots spouting garbage to your callers.
  4. Poor conversation design. You need to bring in an experienced conversation designer to address this issue.

Chances are that some or all of these problems are already undermining the performance of your bot workforce, so how do you figure out what needs fixing?

Apply Your Existing Management Skills to Your Bot Workforce

Among your skills as a contact center or business manager is the ability to listen to and work with your human agents to uncover problems and cultivate your team’s skills. You know how to hold effective one-to-ones to identify areas of improvement as well as growth opportunities.

Just as you work closely with your human agents to optimize their performance, you can work closely with your voice, IVR, and chatbots to do the same—with a few tweaks. Your bots can’t tell you what problems they’re having. So how do you apply your existing skills to effectively manage your bots?

  1. Listen to call recordings and read chat transcripts. With a human agent, you’d probably just do side-by-side call listening or chat monitoring. With your IVR, voice, and chatbots, listening to their interactions with customers and reading chat transcripts serves the same function. Get your tech team to pull a selection of whole call recordings, or chat transcripts, so you can review the interactions your bots are having with your customers. You’ll learn a lot.
  2. Mystery shop your bots. Mystery shopping is a great way to put yourself in the shoes of your customer and experience what they experience. You can do the same with your IVR or chatbots. Just call up and pretend to be a real customer. To really get a feel for things you’ll need to have an end customer account or actually go buy and return an item to see how your bots handle things.
  3. Dig into data. Your bots can’t tell you what they’re struggling with, but you can learn a lot from digging into the data. Are you getting a lot of internal transfers? That could mean there’s a routing problem. Or are people dropping off the call or closing the chat session mid-task? Could mean the bot is getting stuck. When you see these problems, go back to the call recordings, chat transcripts, and mystery shopping to understand what’s really going on.

You’ve Identified the Issues with Your Conversational AI. Now What?

You don’t need to be a techie or a conversation design expert to spot problems in your bot workforce. Just treat them like you would a human workforce. You know what good performance looks like. You know the kind of experience your customers expect and you want to deliver. And hopefully this article will help you see where your bots are falling short. But how do you fix the problems you find?

If your bots are basically doing the right things, but not understanding the customer or being understood themselves, the answer could be to update your bots with a better conversation design. But often the problems are deeper. You wouldn’t hire a bunch more agents without a strategy for what they’ll do, what skills they’ll need, and how you’ll measure and manage their performance. Same goes for bots. If the problems run deeper, you probably need to build a better Bot Strategy.

3 min read

Optimize IVR with Tactical Channel Integrations

Optimize IVR with Tactical Channel Integrations

‘Omni-channel’ can be a daunting prospect.

And connecting all your channels isn’t just a huge logistical challenge, it can also be extremely expensive.

4 min read

6 Tips for Integrating Outbound Text Messaging

6 Tips for Integrating Outbound Text Messaging

In our last post ‘How outbound text messaging can improve the customer experience’, we outlined some of the benefits of integrating outbound text messaging in your contact strategy. As with any channel, the success of those interactions will be dependent on an understanding of who will be using the service, how the text messaging fits with the wider journey and designing great SMS content. So what should you consider if you’re thinking about offering your customers outbound text messages?

3 min read

Stop IVR Rot

Stop IVR Rot

Over time, customer demands and language change. For a contact centre agent, adapting to these changes is a natural process, but what about your IVR? Is it frequently updated in line with new expectations, or has it simply been left to rot?