Call Center Bots: Top 10 Tips on How to Successfully Deploy a Bot [2023 Checklist]

Call center bots are becoming increasingly important in optimizing a caller’s experience.

No matter how hard you try to plan for disaster there is always the unexpected. For call centers the impact of the coronavirus has just raised implementing a bot to the top of the we need it now” list.

Indeed, for some clients who have approached us over the last week, they’ve experienced a 10-fold increase in call volumes to their call center. But how can you ensure a bot will solve your issues, not create more confusion at a time when customers are looking for clarity?

All call centers have contingency plans. They normally involve switching the calls to another location, but with the world in the grip of the Covid-19 global epidemic, that’s not a viable solution. Deflecting as many inbounds as possible from the call center is the next best strategy.

The obvious solution is to deploy a bot that interacts with customers 24/7. But the chances are, if your customers are contacting you at this time, they have complex issues to solve. Situations that need information held on different systems, or technical guidance, or data from a back-end process.

However, many bots are built on simple frameworks. While they’re fine for everyday FAQ style queries, they don’t have the capability to deliver the humanlike experience customers demand. Nor are they able to interact with the backend operations of a business, assimilate the information and provide an intelligent response.

This is where conversational AI dovetails into the call center mix and takes bots to the next level. Delivering more than just an answer, conversational AI can carry out complex tasks, fill out forms, make recommendations, talk users through processes, set up new accounts and so much more.

But to be successful in bot development, call center businesses need to keep in mind 10 critical points.

1. Ensure Speed of Development of your Contact Center Bot

With an urgency to solve issues now, not in six months time, it’s important to look at how quickly you can develop a contact center bot. But speed of development shouldn’t be the only consideration. Be aware that not all development platforms are equal. A few days might give you a shiny new bot, but if all it does is little more than an animated FAQ, then save your money. Time to market needs always to be tempered by the functionality of the final product.

At the same time, some development platforms might look as if they fulfil the capability you require but a closer look reveals long development cycles, a steep learning curve or vast amounts of curated data needed just to get a proof of concept working. All of which will delay the implementation of the final application.

2. Guarantee Ease of Bot Development

Development time is also heavily influenced by the ease with which an application can be developed and maintained.

Not too long ago, building conversational call center bot was a lengthy and complex process, only undertaken by computational linguistic specialists and technical experts. For some development tools that’s still the case. This introduces delays in waiting for highly specialized developers to carry out specific tasks and frequently adds significantly to the overall cost and ongoing maintenance of the conversational system.

The answer is a hybrid conversational AI development platform that delivers the balance between intelligent automation of complex processes in building the system and enabling trained developers and business users to work together to develop the functionality of the bot.

call center bots linguistics and machine learning

3. Start with a Smaller Project

Consider the end goal of what you want your contact center bot to achieve but start with a smaller project in order to see the results and measure the success before deciding on the next phase.

Ideally look for an area or topic that has a smaller initial audience, while offering potentially high gains to the business. This will provide you with an opportunity to monitor and assess each stage against pre-determined success criteria and enable for enhancements to be made quickly before expanding the application.

But remember, in order to achieve the next phase and capitalize on your initial investment you need a scalable platform.

4. But Plan your Call Center Bot to Scale

Choosing a scalable platform is essential to maximize your initial investment, expand knowledge to cover new areas of the business, provide regional support in native languages and allow customers to access the application across multiple channels.

How easy is it to take the investment you’ve already made in dialogue flows and integration, including the tone of voice and branding, and reuse it? Can you apply your own data and vocabulary into the conversational flows, and how quickly and easy is it to do that? As well as using dialogue components within multiple conversations, can you reuse them and the conversational logic across different channels? In other words, how easy is it to take an application built for a website and use it across Google Home, Alexa or Facebook Messenger?

How many intents can the platform handle? A pilot or proof of concept may have only 10 or 20, making it easy for the application to learn those intents with machine learning. What happens when it’s hundreds of intents over multiple business divisions, languages, and regions?

Think about what you would like to achieve now and in the near future, and make sure the technology is able to take your conversational AI journey forward.

5. Deliver an Intelligent Bot Experience to your Customers

Digital channels are fraught with points of irritation at the best of times. But when your customer is already stressed, worried about family, their income and the future, even a minor hiccup in trying to find information or solve a problem is likely to have a significant negative impact on customer experience.

A bot that doesn’t understand their request or is incapable of doing more than spouting out company FAQs is likely to have abuse hurled at it on social media. Not the kind of publicity any company wants.

Conversational AI allows you to deliver a far more intelligent and intuitive online experience. Instead of having command driven conversations, customers can ask for exactly what they want using their own words and terminology. Advanced capabilities allow call center bots to carry out a multitude of tasks on behalf of your customer, allowing them to resolve problems fast at their own convenience.

But don’t forget not to waste your customers time. Make sure you explain beforehand what the bot can or can’t do if it only covers certain sectors of your business.

Contact center bot infograpic

6. Build a Contact Center Bot that is Conversational

Customers want to be able to talk with technology as if it was a human, even though conversely, they’d prefer to know it was a machine. Your contact center bot needs to have personality and be able to understand multiple intents within a single sentence, while also being intelligent enough to ask for more information if required.

A memory is essential to personalize the conversation, understand the context as it evolves and to deliver the right response to a complex query that might have more than one part. The bot also needs to be capable of task switching and to bring the customer back on topic.

Conversational AI platforms such as our own Teneo, allow enterprises to build sophisticated natural language systems that are capable of providing brand differentiation while delivering the ultimate customer service.

7. Make your Call Center Bot Available on Multiple Channels & in Different Languages

Customers want to communicate over a channel of their choice. While in these difficult times they may be prepared to use the channels that you dictate, it’s worth considering at this point how you will expand your offering in the future. Even so, for global enterprises because of regional variations the chances are you’ll need to offer your bot over two or more different channels.

Teneo, our conversational AI platform -for instance, runs over any platform or channel through a series of handy connectors that integrate directly into messaging and speech applications or into CPaaS (Communication Platform as a Service) technologies.

Be aware that while many call center bots may offer multiple languages it normally involves a complete rebuild of the bot. Look for technologies such as that from Teneo that allow for it be built in one language and easily ported to another typically reusing 80% of the original build and requiring only minor adjustment to local customs or regulations.

8. Allow Easy Collaboration among Teams

Many enterprises have teams in disparate locations working on projects, but with many people now restricted to working from home collaboration functionality such as user control is essential in a conversational AI development platform.

In addition, it’s important that teams have visibility into the actual application including the ability to annotate. Platforms such as Teneo have been developed with this in mind to easily allow developers and business users to work alongside each other to identify points that may need adapting to bring in line with business processes.

However, in the current coronavirus epidemic this feature is even more important to ensure that other staff can take over a project at short notice should a team member be sick or absent looking after family members.

9. Integrate into the Call Center’s Back End Systems for Greater Capability

Integration into backend systems and processes allows conversational AI applications to deliver a much more relevant and personalized response to customers. From retrieving details of past orders, to calling on an RPA (Robotic Process Automation) to run a specific task, enterprises can deliver a sophisticated customer experience by taking advantage of existing systems.

It also enables organizations to pick-up where the limitations of their current online offerings fail by enabling additional functionality. Already one our customers has reduced the time it takes to deliver essential legal documentation to customers from 7 days to one hour, simply by connecting its Teneo based bot into an RPA workflow.

10. Enable Control over Data Ownership and Privacy

The last point to consider, but by no means the least, is data ownership and privacy regulations. Conversational AI applications encourage people to talk more about what they are looking for than simpler bots. This creates vast amounts of data that platforms such as Teneo are able to use to personalize the conversation further and deliver actionable insights back the business.

However, not all platforms allow the enterprise to own the data. Some don’t even provide all of it, just the “final pizza order” for you to deliver. This can impact of the RoI of the conversational system, because you’re not able to derive the full value. It can also make it more difficult to ensure compliance with privacy and security requirements.

Teneo allows enterprises to own the data generated and provides the functionality needed to make maximize its value and still comply with privacy regulations such as GDPR. It can also be run on premises, instead of in the cloud affording those businesses with stricter security measures full control.

Moving Forward

Using conversational AI for contingency planning in call centers is nothing new. Our bots have been used in the past by call centers that need to close because of whole range of unexpected events such as severe bad weather. But rushing in without considering first what your main goals are and how the bot technology you’re planning to use will solve those is likely to end up frustrating both customers and contact center staff.

As one UK insurance company famously used to say — don’t make a drama out of a crisis. Taking just a little more time right now to ensure that your bot is capable of delivering a consistent, relevant, intelligent response will be key to its success. Further, by selecting the right partner and technology, you can quickly deliver conversational AI solutions that meet both your immediate need to handle massively more capacity and at the same time, meet the expectations of your customers.


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