Cast your mind back to the first time you interacted with an AI chatbot – you probably thought it was pretty high-tech right?
But times change! Chatbots are now the fastest-growing brand communication channel out there.
In fact, 67% of global consumers had an interaction with a chatbot over the last 12 months.
You don’t have to be running the Starship Enterprise to have one, and to be totally honest, if you want to keep up with your competitors and your customers’ expectations, you kinda need one, like… yesterday.
In this article, we’ll tell you everything you need to know about AI chatbot development and how it can take your business into the future.
You can trust us – we were named one of Australia’s top chatbot companies.
What Is an AI Chatbot?
You know when you’re on a website and a little bubble appears in the corner asking if you want to chat?
Well, unless it’s coming from a dodgy pop-up advertising “sexy singles in your area”, that’s more than likely a chatbot: software designed to help customers resolve issues immediately, no matter the time, and with the ease of talking to a real person.
There are loads of ways chatbot functionality can be applied, for example:
- eCommerce bots can act as virtual personal shoppers, notifying users of real-time offers.
- Personal finance bots can carry out banking tasks like payment verification.
- Hospitality chatbots can help users book rooms, notify them of flight changes, and more.
What is the difference between AI and chatbot?
Historically, chatbots worked a bit like those old choose-your-own-adventure games. Remember them?
“You meet a troll under a bridge, do you:
a) fight it
b) walk away
c) say ‘Hi, Mum’?”
There are certain responses that simple chatbots are programmed to respond to with set scripts, and if all goes as planned, the customer is moved through the conversation easy-peasy.
However, if a customer’s query is too complex, they could get stuck in a frustrating loop of repeating themselves.
There are loads of chatbots out there like this – just look at this example:
That’s pretty unforgivable stuff, especially when you consider that 33% of customers say the most frustrating customer service issue is having to repeat themselves.
Artificial intelligence chatbots – also known as conversational AI – are the solution.
They use AI and machine learning to create a more natural, useful conversation and avoid a lot of the issues you get with traditional chatbots.
|Potential issues with simple chatbots||AI chatbot solution|
|They don’t retain information||Machine learning allows the chatbot to remember what you’ve told it so you don’t have to repeat yourself|
|Only specific words or phrases can trigger a useful response||Natural language processing allows the chatbot to understand a broader range of input|
|Only programmed for a limited number of recommendations||Intelligent analysis allows the chatbot to make more complex recommendations based on your history|
No wonder AI chatbots are taking over from simple ones: experts predict that AI will power 95% of customer interactions by 2025.
Example of an artificial intelligence chatbot in action
One of our favourite artificial intelligence chatbots to implement for clients is IBM Watson.
This artificial intelligence chatbot software was created by tech giant IBM and has been deployed across a multitude of industries. There are huge advantages to using the IBM Watson software, including:
- It can identify and replicate your brand tone based on just a few sentences you provide as training data
- Its irrelevance detection models know when to pass the customer to a human agent
- It is unfazed by natural language errors like poor spelling
- Machine learning retains information so customers don’t have to repeat themselves
Take a look:
Good, right? A Forrester study found that the software paid for itself within 6 months of installation and offered a whopping 337% ROI.
But what does it look like to actually implement an AI chatbot like this?
What Does AI Chatbot Development Look Like Today?
There are five basic stages to go through when you’re implementing a chatbot.
Wait a second.
Nope, that’s wrong. The REAL first stage of AI chatbot development is…
1. Defining your goals
What problems are you bringing your AI chatbot on board to solve?
It’s important to think strategically here. The answer will depend on your current team, your product, and your industry. Some industries’ customers are more open to chatbots than others’:
Some clues that your business is ripe for AI chatbot problem-solving are:
- Your teams are currently doing a lot of manual tasks
- Many of your leads come through landing pages or social media
- Your customer service reps spend a lot of time answering the same queries over and over
2. Choose your languages and channels
There’s no point spending loads of money on a multilingual chatbot if 99% of your customers are in your immediate area, and you have no other plans to expand your reach.
Likewise, if you’re a B2C company that gets most of its leads from Facebook, chances are you don’t need a heavy-duty LinkedIn chatbot.
Direct your resources where they’ll make the most impact.
3. Decide on integrations
An AI chatbot is useless to you unless it’s plugged into the other areas of your business. This means not just seamless integration into your website (that goes without saying), but also your:
- CRM contact centre
- CRM contact management system
- Payment systems
- Cloud storage tools
Once you’ve made this decision, it’s time for the next step.
4. Build your bot
We know how this looks. It looks like if we’d said “There are 5 stages to building a boat! Stage four… build the boat.”
Hear us out: if we broke down all the steps you’d need to follow to build an amazing AI chatbot, this article would be longer than War and Peace.
You can build an AI chatbot by yourself – Zoho One, for example, offers this option. Alternatively, you can use a chatbot platform like MobileMonkey.
But to get the best results, you want an expert like Human Pixel on board.
We can help you think creatively about how your chatbot can not just help customers, but help you, building your brand voice and gathering key information from interactions.
We’ll build a state-of-the-art AI chatbot using IBM Watson or Google Dialogflow, and we can also handle broader tasks like
- Business process automation
- CRM and tech stack integration
- Conversation flow
Not convinced? Just wait – you’ll definitely want an expert on hand for step 5…
5. Scale alllll the way up
Remember how we said there’s no point in a multilingual chatbot if you’re only operating in your own region?
Let’s say your company (with the help of your chatbot) extends its reach; your marketing efforts ramp up; in a few years, you’re opening an office abroad.
You’ll need your chatbot to be able to cope with these changes, and you’ll have your work cut out for you doing it alone. A development partner can help you do it right.
Why Are So Many Companies Investing in AI Chatbot Development?
It’s not just your imagination: chatbots are literally everywhere these days, and they’re only getting more widespread.
The global conversational AI market is set to grow from $6.8 billion in 2021 to $18.4 billion by 2026.
There are lots of reasons for this growth spurt, but these are the ones we think you should know about.
1. They boost efficiency
They might seem space-age, but artificial intelligence chatbots are, at their heart, an automation tool like any in your Customer Relationship Management system.
They work, too. Consumers and businesses are predicted to save over 2.5 billion customer service hours by 2023 through the use of conversational AI, because of how many common customer service tasks they can replace:
|Business area||Tasks AI Chatbot development can automate|
|Sales & marketing||Lead distribution Data collection|
In eCommerce, basket management and notifications of deals
|Customer service||Routine or repetitive enquiries|
Directing enquiries to relevant reps
By cutting down the time spent on repetitive manual tasks like data entry, you’re freeing up your team to work on higher-value tasks like
- Dealing with complex customer queries
- Creating new strategies for retention
- Improving customer UX
You’re doing what we love: using technology to make more room for the stuff that only humans can do.
It’s not just good for your employees, but your customers too…
2. They help you keep up with consumer expectations
Look, we all know that customers want fast responses. Nearly half of all customers expect companies to respond to their queries in under 4 hours, while 12% expect a response within 15 minutes or less.
Can you imagine if you tried to have a sales rep available for online chat 24/7?
Recipe. For. Disaster.
A chatbot, on the other hand, can do all of this easily, while also adding the benefits we’ve described above.
What’s more, customers love it! The average satisfaction rate of bot-only chats is 87.58%, which is not too shabby – especially compared to the alternative. Do we need to show you that GIF again?
When two thirds of companies compete on customer experience, you’d be a right idiot to neglect this advantage, just saying.
3. They cut costs and boost revenue
This should be obvious. Really, think about it.
With an artificial intelligence chatbot, you’re cutting down the time your reps are spending on boring tasks that they hate, and which distract them from the stuff that really adds value to your business. That alone lowers your overhead.
You’re also getting back to customers more quickly, with natural language. Their simple queries get cleared up straightaway, and when they’ve got a really gnarly one, they get directed to the right rep on the first try. Up goes your retention.
But it’s not just that chatbots save you time and customers: they also boost sales.
This is what’s called, in the biz, “a buttload more money”.
The benefits of AI chatbot development (the short version)
Didn’t get all that? No worries, here are the highlights:
|Benefit of AI chatbot development||Examples|
|Boosting efficiency||Automating repetitive queries|
Taking over basic data entry
Automatic lead distribution
Directing queries automatically to the correct rep
|Keeping up with consumer demand||24/7 on-demand service|
Machine learning means no more repeating your query
|Cutting costs and boosting revenue||Lower overhead due to the increased efficiency of your teams|
Higher revenue thanks to increased customer satisfaction
The Future of AI Chatbot Development
It looks like the only way is up for AI chatbot development in the next few years.
The Natural Language Processing (NLP) market alone is expected to have more than doubled by 2024 compared to 2019:
But despite the widespread use of voice-activated conversational AI like Alexa and Google Home, written AI Chatbots look set to have a much more stable growth period.
This is due to disillusionment around the complexity of voice technology and concerns around data security put off consumers.
The challenges we still need to overcome
AI chatbots aren’t quite ready to rule the world just yet. Which, in some ways, is a bit of a relief.
There are still some key challenges to using AI chatbot software that haven’t been resolved:
1. They’re not yet applicable to all areas of business
We mentioned above that not all industries have customer bases that are ready for extensive AI chatbot development.
Well, not all business areas are, either. Customers are still only willing to use chatbots for certain functions:
As you can see, customers are much more willing to turn to chatbots as a shortcut, or as an alternative to something they can already do online, like finding the relevant rep or paying a bill.
They’re less likely to use a chatbot for prospecting purposes. For instance, in real estate, this might be discussing what they’re looking for from their first home, or even putting down the deposit on a property.
But, before you put on your disappointed face…
… remember that this is what experts like Human Pixel are here for!
The challenge is finding the areas of your business where chatbots can make a big impact, and this kind of business process improvement is our speciality.
2. They can’t understand emotions
Look, there’s a reason why we use our phones to call our friends and not to be our friends.
Computers, no matter how far they’ve come, still have trouble discerning emotion or context from text.
For example, a computer could not have written such a helpful and funny article about AI chatbot development. Right???
NLP is helping chatbots discern emotion in messages. For example, Google Dialogflow uses Sentiment Analysis to gauge when an unhappy user should be passed to a live agent to handle. But the fact remains, the live agent is still necessary.
You’ll probably always need your flesh-and-blood team to provide that real human connection with your customers, as nearly two thirds of consumers still prefer humans to chatbots for important queries.
But, like we said before – why ask your technology to replace your people when it can just help them do their jobs better?
At Human Pixel we think that tech like AI chatbots should be used to push all the boring, formulaic tasks into the background so that your human team can really shine, and we can help you build a chatbot to do this.
3. Making decisions isn’t their strong suit
Are you sensing a theme here?
The Harvard Business Review reckon we are moving closer to AI-powered decision making that looks something like this:
But we’re not there yet.
Simple decisions based on set rules are great for AI chatbots to deal with, such as
- Lead distribution
- Resolving web errors
- Recommending eCommerce deals
But more complex, qualitative questions require a human to answer them.
To use the real estate example again, an AI bot might be able to tell you what’s available in your area of choice and budget, and perhaps even calculate potential mortgage payments based on the factors you input.
However, only an experienced agent would be able to:
- Tell you their own perspective on how the local area is developing
- Give you empathetic advice based on your plans for a family
- Give you a hug when you close on your first home
The fact is that there are still some things that only humans can do well. Computers might be better than us at “maths”, but we’re still sticking it to the robots when it comes to thinking out of the box, creativity, and emotional intelligence.
The challenges of AI chatbot development (the short version)
|Challenge of AI Chatbot development||Examples|
|Not yet applicable to all areas of business||Only 13% of consumers would use a chatbot to buy an expensive item|
Not all industries have customers who are fully amenable to AI chatbots
|Can’t understand emotion||NLP can gauge tone but it can’t create an emotional connection|
|Only capable of simple decision-making||Decisions based on a finite set of specific rules are fair game|
But more complex decisions that take in qualitative experience and emotions can’t be automated (yet!)
Conclusion: Choose Human Pixel for Your AI Chatbot Development
Business moves fast; to keep up, you need a chatbot to help you keep juggling all those priorities.
As one of the world’s top chatbot companies, Human Pixel can help you combine the incredible power of AI chatbots with the equally incredible potential of your human team.
We’ve managed tech transformation for countless businesses. We know how to help you avoid the pitfalls of a poorly-implemented AI chatbot, from choosing where it will have the most impact, to integrating it into your techstack.
We’ll also be here for you as the technology develops in the future, so you stay at the cutting edge. Get in touch today to arrange your business development workshop, or check out the 12 AI and Machine Learning Applications for 2022 and Beyond to find out more ways AI is transforming business practices.