2 min read

Why IVR and chatbots are disappointing

Man holding his head in hands

Gartner just released their latest hype cycle for AI.

Right there in the trough of disillusionment are chatbots.

What went wrong? Everyone was so excited about the possibilities!

I think it’s a general issue with AI. Or at least, our perception of AI.

Humans evolved to create and maintain highly complex social groups. To do this, our brains try to understand what other humans are thinking, so we can anticipate and provide for each other’s needs. Or anticipate and avoid an attack.

But we over-generalize. We fall in love with cats, that probably don’t love us. We complain that a dog is naughty when they’re just responding to the stimuli we introduce into their environment.

We over-generalize with pets that have surprisingly similar DNA, biology, and brains to us.

Imagine just how easy it is for us to over-generalize with AI that appears to do things like we do.

Like chatbots, that ask and respond to questions.

But chatbots share almost none of the underlying biology (infrastructure), DNA (programming) nor experience (data) that makes us who we are.

And that’s the issue. We can’t use our intuition to understand what AI is capable of. When Google shows off an AI chatbot that pretends to be an airplane and appears to chat convincingly with their human creators (I wrote about it here) it’s easy to imagine those capabilities will extend to the chatbot we deploy in our contact center.

But Google’s chatbot isn’t intelligent like us.

It’s not flexible, helpful, and resourceful, like us.

It’s just a computer program that’s harnessing billions of examples of conversation to say something plausible. It might be good at chatting about folding paper and flying. But it doesn’t know your business needs. Nor your legacy processes. Nor to whom it should turn for help if it gets stuck. Unless you provide very detailed instructions to it.

And that’s the issue. IVR, voice or chatbot platform plus data does not equal the capabilities of a human agent.

Nowhere near it.

You have to provide the instructions. That’s what Conversation Designers do. They teach robots to talk.

The latest AI algorithms make this easier. You don’t have to teach the bots everything. Conversational AI platforms have general models of language built in to help IVR and chatbots understand what a customer says. But only at the surface level. You have to provide them with lots of examples to fill in the gaps.

You also have to provide very precise instructions on how to behave based on what they think a customer said. And meant.

The platforms try to make that easier with nice-looking graphical interfaces to build your bots with. But they provide an illusion of simplicity. Just because you can quickly build a bot, doesn’t mean you can actually build a bot to do what your business needs. There are lots of gaps, and corner cases that can catch you out.

Conversation Designers, and the teams that support them, need to understand what Conversational AI platforms are capable of, and work around those constraints to build a bot that customers will engage with, and understand. And that will engage with and understand them. But only in certain, very narrow, situations.

3 min read

Own your Bot Strategy. You can do this!

A medium rare steak on a wooden board

I love a good steak. But I was always scared of cooking one myself. I tried a couple of times and overcooked it. $50 of prime rib. Ruined. So I gave up.

Then about 10 years ago, Gordon Ramsay, the famous chef from Hell’s Kitchen, did a ‘cook along live’ show. It was a brilliant idea. He told you what to buy the week before, then you set up the television in the kitchen and literally cooked along with him. Live. He told you when to put the pan on, how to season the meat. He guided us through every step.

An hour later me and my future wife finished our desserts. 3 delightful dishes, and the best steak I’d ever had. Anywhere.

We’re all capable of more than we think. We just need the confidence to do it. The right ingredients and the right guide can make all the difference.

In the last email in this series, I laid out the 8 steps to delivering a brilliant IVR, voice, and chatbot strategy. It’s not a quick fix. It takes about 6-8 weeks, and a bit of effort, but the results can be incredible.

We took a large US retailer through this process a couple of years back, and I recently spoke to their senior product manager, Bindi, who was in charge of the IVR project, to see how things were going. She said this:

“The Bot Strategy process was a cornerstone of our ability to progress so quickly”

Within 18 months they had transformed their IVR, and they’re now looking at rolling out a chatbot too.

But not everyone wants or can afford to pay us to do this for them. That’s why we decided to launch the Bot Strategy Bootcamp. Well, that and my experience with Gordon Ramsay!

Bot Strategy Bootcamp takes this same process and guides you through it. It’s not your usual corporate training event where you learn some stuff you could have got from Google, get back to the office after a couple of days and forget what you learned as you dig your way out of a mountain of emails.

Bot Strategy Bootcamp is a 3-day online course with 12 hours of interactive sessions. We don’t just teach you the process, we give you the tools and templates we use to identify opportunities, create a vision, build a business case, and define a phased program of work that delivers measurable impact and solid ROI for your business.

During the course, you’ll practice using these tools. By the end of the course, you’ll have everything you need to go build a brilliant bot strategy.

Bootcamp costs $2k. Discounts are available for multiple attendees from the same organization.

That’s less than 5% of the cost of getting in external consultants.

It’s nothing compared to the cost of false starts and delays in this critical area of business transformation.

Participants in the first round of Bootcamp said:

“The training was amazing. I come from an IT background, and I learned a lot.”
 
“Before it was like the wild west. This gives us the structure for prioritizing, planning and implementing”
 
“Do it! I loved the interactive sessions. Enjoyed every minute”

You can do this. But you need to take action now.

Check out the Bot Strategy Bootcamp brochure for more details.

If you’ve already got an IVR, voice, or chatbot deployed, or you’ve got plans to build one, Bootcamp will make sure you too are able to progress as quickly as Bindi and her team.

In the meantime, suffice to say that with the confidence that Gordon gave me, I’ve gone on to cook bigger and better steaks.

Here’s a favorite of mine:

Bone-in ribeye, also known as Cote de Boeuf. And don’t worry, I’m not blowing up the environment to enjoy a good steak like this. It comes from a local farm just down the road.

This is the last in a 6-part series on the Bot Management System, and Bot Strategy. Check out the earlier blogs here:

Why a new strategy is more important than a new platform

Why you should think of your IVR, voice and chatbots as a bot workforce, not just a piece of tech

How to apply the principles of HR to your bot workforce

Why you can’t leave your strategy up to your platform or tech provider. You need to own it

8 steps to delivering a brilliant IVR, voice, and chatbot strategy

4 min read

8 steps to a brilliant Bot Strategy

8 steps to a brilliant Bot Strategy

It’s time to build a Bot Strategy. Are you ready?

So far in this blog series we’ve talked about:

  1. Why a new strategy is more important than a new platform
  2. Why you should think of your IVR, Voice & chatbots as a workforce
  3. How to apply the principles of HR to your bot workforce
  4. Why you can’t leave your strategy to your tech vendor

Now I’m going to cover how to do that. How to build a bot strategy that suits you, and your business.

Like I said before. This is not trial and error, nor a 1-day workshop delivered by a tech partner to convince you to buy their stuff. This is a 6-8 week process. There are 8 steps.

Step 1 – Understand the strategic backdrop

What are you and your business trying to achieve? Think about these four areas: cost reduction, revenue enhancement, customer experience, and brand. Usually, everyone wants all of these, but go deeper. Will you invest money to improve the customer experience? Or does that investment need to be offset by cost savings? Do you want to differentiate your brand with Conversational AI, or just match the competition?

Step 2 – Review your experience, and your competitors’

You need to understand your starting point. Do a review of your current IVR, voice or chatbot experience. You don’t need to be an expert to do this. Designing conversational AI is not something everyone can do. But most humans know what good conversation is, so while you may not be able to design it, you can review it. Use our Customer Experience Checklist to guide you. Do the same for a couple of your closest competitors.

Step 3 – Get Context

Your bot workforce is part of a wider team. Now you understand what your bots are doing, you need to understand what your human agents are doing too. That means doing side-by-side call listening with agents and reviewing recordings or chat transcripts. Talk to a group of agents about the different requests they get and how they handle them. Review contact center reports to get a feel for the volumes of different tasks, and if you can, the approximate handling time for each of them.

Step 4 – Identify candidates for automation

Bots can’t do everything, so use the information in the previous step to highlight those tasks that occur frequently – at least 5% of total contact volume – and have a simple, repeatable process. These are candidates for automation. They don’t have to be whole calls or chats. They can just be the repeatable part of a longer process: identifying the customer, providing an account balance, or giving order status information.

Step 5 – Build the business case

Identifying direct financial benefits from customer experience and brand enhancements is very hard. There are strong correlations between customer experience and business value, but proving causation is very difficult. Attributing the benefits to a specific experience change is even harder. If you need to demonstrate ROI to get funding for your project, the best approach is to build a business case based on direct financial cost savings. So what’s the value of the tasks your bots perform in comparison to the alternative, which is usually having a human do it? Estimate the number of tasks your bots will perform and multiply by the average handling time for agents to do the same thing and the cost per minute of your agents. Then look at the size and complexity of each task, to get a feel for the cost. You don’t need decimal points here.  A t-shirt size is OK: small, medium, large.

Step 6 – Prioritize and plan

Some things that seem appealing early on, look less so when you’ve checked the value and cost. You can drop them. But you should still have a bunch of things that are worth doing. Don’t try and do it all in one go. First, identify the quick wins: decent volume, no IT dependencies, small t-shirt size. Next up, phase 1 should include bigger tasks, still with good volume, and manageable IT requirements… as in, the API is available now or it’s already on the IT roadmap. Phase 1 should also include foundational elements: things that you’ll need to build out your vision. Phase 2 and beyond includes everything else: tasks that will need new APIs built, or that rely on foundational elements from Phase 1. Make sure each phase has demonstrable ROI: the costs for delivering that phase need to be outweighed by the benefits calculated in the business case step.

Step 7 – Articulate the vision

Don’t skip this part! You’re deep into the weeds, and you know this project is worthwhile. But other stakeholders don’t have that detail, nor the time to consume it. You need to build a compelling story around the outcomes of the first 6 steps. There are many different approaches, but a simple framework to use is the hero’s journey:

Set the scene: the strategic backdrop, the review you did of your current experience.

Show the challenge and opportunity: what your competitors have (from your review), what you could have (candidates for automation).

Define the objective of the quest: It really helps if you can bring the vision to life with recorded audio samples or chatbot storyboards… but you’ll need a conversation designer for that.  If you don’t have access to one, take audio or screen recordings of examples you found in you competitor review and use those.

Then show the path to get there: your plan, and the ROI for each phase.

Step 8 – Deliver it!

Got buy-in? Got budget? Great, let’s do this! But remember this isn’t just a tech project. You’re building a bot workforce here, so you need to put a bot management system in place. Check out our Bot Management System e-book to get a feel for what that entails.

Phew. That’s a lot, right? And that’s why you can’t leave it to your tech vendor, nor do this in a couple of meetings or whiteboard sessions. This process really works, but you’ve got to put the time in.

You can do this, but this blog isn’t enough. Nor is reading a couple more blog articles. If it was, you’d have done it before, wouldn’t you? In my next blog article I’ll be showing you some options that will help you get this done.

In the meantime, let me know what you think of this approach. Have you done any of this already? Did it work for you? What problems did you encounter?

3 min read

Hair Cuts and Strategy

Hair Cuts and Strategy

I used to hate having a haircut. That dreaded question: so, what are we doing today?

What I really wanted was to look so awesome that I’d attract my perfect life partner. But at that time I hadn’t found her, so I clearly hadn’t been asking for the right haircut! I tended to leave the decision up to the hairdresser. “Whatever you think” I’d say.

The results were different every time, and never quite the outcome I’d hoped for.

One hairdresser made me look like I was in a boy band. Another cut my hair like the lead singer from Snow Patrol. Neither worked. They just weren’t right for me.

Eventually, I found my perfect partner and a haircut we’re both happy with. But it was trial and error. Partner and hair cut!

What getting a good haircut teaches us about Bot strategy

I see the same situation playing out in the field of IVR, voice and chatbots all the time. 

Companies are letting their tech vendor dictate their strategy:

“You need a chatbot”
“Deploy Natural Language”
“You need voice biometrics”

And my favorite nonsense requirement: “You need real AI”!

They’ll show great case studies and do an awesome demo. But it’s like the boy band haircut, it works in some situations, but maybe not yours.

A bot strategy that suits you

Like me and my haircut, most companies know what outcome they want from their conversational AI: it’s got to delight customers, enhance profits, and differentiate the brand. In essence, deliver amazing ROI. Otherwise, why bother?

But what does that actually look like? For you and your business? What haircut… I mean bot strategy is right for your business?

One thing’s for sure. It’s not the same as Amazon, Apple, or your competitors. Your customers are different. Your business processes are different. Your contact volumes are different. Your capability is different.

You need a bot strategy that suits you. One that will attract, delight, and retain perfect customers, just like I’d hoped my haircut would help me attract the perfect partner.

What a bot strategy looks like

Getting there is a process. But it’s not trial and error.

A brilliant bot strategy aligns 3 things: customer needs, business needs, and technical realities. And it articulates a vision for what bots can do in your business. Now. In 6 months’ time. Next year, and beyond.

It details where your bots add the most value, what they can do well, and what you still need humans to handle. It details the investment it’ll take, the organizational capabilities you’ll need, and the metrics that will ensure you’re on track to deliver the benefits.

Bot Strategy Discovery and Development

Over the last 20 years, me and my team have developed a process for this that we call Discovery. It’s not about sitting around a boardroom table or in front of a whiteboard and dreaming something up. And it’s not the 1-day session that tech vendors do to sell you their stuff. It’s a methodical, practical sequence of steps that takes 6-8 weeks and creates not just alignment, but excitement, and an orientation towards action.

Look out for my next blog where I take you through those steps to creating a brilliant bot strategy.

And don’t worry if you’re not sure if this is your job or your responsibility. I truly believe that every member of a team should contribute to the vision, and strategy of their organization. You can do this. You just need to follow the steps.

In the meantime, I’ll leave you with one question to think about:

What do you really want from your investments in IVR, voice, and/or chatbots?

Write down three items. Be as specific as you can. If you want some ideas, think about these three key areas: customer experience, brand communication, and profit (meaning revenue enhancement or cost reduction).

If you want some feedback or just some extra accountability, please email and send me what you write down. I’ll treat it completely confidentially, of course. The answers to this question will really help as you start to develop your strategy.

This is the fourth blog in a series, so if you haven’t already seen them, check out the earlier blogs in the series:

Part 1 – What’s the best Conversational AI platform

Part 2 – Why your IVR, voice & chat bot need HR for AI

Part 3 – Super agent or Nightmare agent?

4 min read

IVR and chatbots: Super-agent or nightmare-agent?

IVR and chatbots: Super-agent or nightmare-agent?

Humans can be just as frustrating as a badly designed IVR, voice or chatbot.

When I recently called to sort out a problem with my broadband, I knew the person I was speaking with couldn’t help me, but he insisted on going through the troubleshooting process he’d been taught. Eventually, I got escalated to the tech team and we got it sorted, but it illustrated the problem with bots, and why you need a Bot Management System to keep them in check.

In the last blog in this series I explained the fundamental differences between web, mobile, and conversational AI. We established that customers expect bots to speak and listen like humans, and be smart, helpful and resourceful like humans are too.

But even the best AI doesn’t have the flexibility and robustness of human intelligence.

Human vs Bot

That doesn’t mean bots are useless, they’re just narrow. Like a rookie customer service agent who has only been trained on a single process, say processing the return of an unwanted item. Outside of that, they’re not going to be very helpful. If the rookie returns agent receives calls or chats about making a return all day, they’ll do a great job. But if someone starts asking about doing an exchange instead of a return. Or wants to know if there’s a larger jacket size in stock because the one they’re returning was too small, the rookie returns agent is going to struggle.

Now, a human rookie returns agent will use their general human intelligence to fix the problem. They’ll ask a manager for help or transfer the customer to a more experienced agent. But a returns bot won’t do that, they only know about returns. They don’t know how to tell their manager there’s a problem. And they only know how and when to get another agent to help if they’ve been given explicit instructions on how to identify when they need to get help, and they’re taught how and where to transfer a call or chat.

It’s actually even harder for bots. Imagine if our rookie returns agent isn’t a native speaker of the language most of the customers use. What if they only learned enough English to handle the returns process. They’re listening out for the word ‘return’, and they know if they hear it they need to say: “what’s the order number”. They don’t really know what the question means, but they know that most people respond with an 8-digit number that they can put into the system to process a return. If someone doesn’t respond with an 8-digit number, things will get awkward quickly.

Nightmare-agent

This is the bot’s predicament. They know just enough language and just enough of the business process to do very specific things. If well designed, they can do those specific things just as well as a human agent. Sometimes even better. Because they can use a voice that your customers respond best to, and that matches your brand. They can access data faster than a human agent. And they can help customers 24×7.

But outside of that narrow envelope of expertise, they quickly change from super-agent to ignorant, annoying, relationship-killing, brand-destroying nightmare-agent. Worse than that, they’re an ignorant, annoying, relationship-killing, brand-destroying nightmare agent who won’t complain to their manager, won’t ask for help, and won’t ever leave. They’ll just keep having thousands of terrible conversations. Your nightmare agent. The worst possible employee. Talking to your customers, at scale!

Super-agent

Hiring an employee is the final step in a process that started with a business strategy, departmental objectives, resource forecasting, job spec creation, advertising, interviewing, and objective testing. Once hired there will be a probation period, and the new employee will be set clear goals with measurable targets and outcomes. Training will be put in place, and the employee will meet with their line manager regularly. Before and during their 1-2-1 meetings the line manager will measure the employee’s performance and assess progress against the targets. They will discuss areas for improvement, and if targets are being met or exceeded, look for opportunities to help the employee develop their skills and deliver even more value in the business. This is line-management 101. You wouldn’t hire an employee without doing these things.

The Bot Management System

Now, as we saw above, from the perspective of the business, bots are very similar to a rookie human agent. With the right training and support, bots can do a human-like or even super-human-like job in a very narrowly defined area.

And they can do it at a lower cost. That’s ideal. A superhuman job for less than the cost of a human.

But outside of that narrow area, our super-agent becomes a nightmare agent. You can stop that happening with a Bot management system that ensures you hire the right bots for the right job and that you train them to do it brilliantly and measure their performance. A Bot management system lets you identify problems with your bot workforce and fix them. And find opportunities to enhance the impact your bots are having.

The real problem with bots today is not a tech issue, or a design issue. That’s not to say that better tech and better design aren’t really important. They are. They expand the capabilities of bots and the value they can deliver. But without a Bot Management System you can’t expect a decent return on your investments in IVR, voice and chatbot applications.

I’ll be continuing this series with a look at how to build a Bot Strategy  That’s the first step in creating a bot management system. If you missed them, check out my previous blogs in this series: What’s the best Conversational AI platform and Why your IVR, voice & chat bot need HR for AI.

Did you have a super-agent or a nightmare-agent experience recently?

2 min read

Why your IVR, voice and chatbots need HR for AI

HR style management of a BOT workforce

There are two fundamental differences between conversational experiences, like IVR, voice and chatbots, and graphical user interfaces, like web and mobile experiences. These differences demand a different approach.

Learned vs Instinct

Web and mobile are learned experiences. They use physical metaphors like inertial scrolling, desktops and filing cabinets. But the interaction we have with them is learned.

We learn to use a touchscreen or mouse. We discover how to navigate the user interface. We adapt to the technology. And we can do that because we have big flexible brains that can adapt our behaviour to our environment. That’s what helped us populate every corner of the globe and imagine, build, and use digital devices.

But language is different. Conversation is different. We learn language at such a young age that we can’t unlearn it. Harvard Professor Steven Pinker describes language as an instinct. Just as babies instinctively attach to their parents for food and protection, they instinctively develop language. And we can’t un-learn it.

Expectations

The other big difference is that most of the channels we use to interact with bots started as ways to interact with humans: the telephone, text messaging, web chat, WhatsApp and Facebook Messenger. These were all originally used for talking with other humans. Bots joined the party later. So customers interacting on these channels don’t just need bots to speak and listen like humans do. They also expect them to be smart, helpful and resourceful in solving problems, just like humans are.

Web and mobile experiences don’t have that human expectation problem. Most web and mobile customer service experiences are like forms and documents, in-store adverts or shopping catalogs. We expect those things to be useful and easy to understand. But we don’t expect them to be smart, helpful and resourceful.

These two differences set a really high bar when it comes to building bots.

We adapt to use web and mobile experiences, and we expect them to be useful. But we won’t, in fact we can’t adapt to the way bots talk, and we do expect them to be smart, helpful and resourceful.

They need to speak and listen like a human, then understand and act like a human would too.

A different approach

The best Artificial Intelligence (AI) algorithms today can match or exceed human performance in specific, narrow areas. We don’t have a generalized form of AI with anything like human levels of flexibility and robustness. But there is a fix for this.

You need to treat your bots like a workforce, that needs leading and managing, just like humans do. You need clear job descriptions for your bots, so they can excel in their narrow areas of expertise. And you need to review their performance and coach them to improve, just like you would do in regular 1-2-1s with your staff. We call it HR for AI.

It’s a big mindset shift, but once you look at your bots from that perspective, getting maximum ROI from your investments in conversational AI becomes as simple (and difficult) as applying management best practice to your bots.

In the next blog in this series, I’ll be looking at How to apply the principles of HR to your bot workforce.

If you missed the first one, check out what’s the best Conversational AI platform?