Machine learning, Natural language processing, Instant messaging, Artificial intelligence all these wonderful ideas, frameworks, and technologies come together to create a next gen tech called chatbots. In recent developments chatbots have been surprisingly quick and cost-effective in helping organizations realize exciting business-use cases.
That said, it's equally easy to get things wrong. Even though the cost of failure isn't a huge deterrent for enterprises looking to experiment with chatbots, it's obviously more desirable to learn from others' mistakes.
That's where this guide will help. Here are six key secrets that organizations should strive to understand to make their chatbot implementations better.
Find the right business-use case for your chatbots
The most critical question with far-reaching consequences that any business needs to ask is - what's my use case for chatbots?
The unique selling proposition (USP) of a chatbot is its immediacy of response, and the use of natural language that makes communication unobtrusive and organic. The right use case - chatbot fit is crucial for the project team to deliver fulfilling use cases.
The most successful chatbots are those that have been built around expected customer usage.
Not only does this help you determine whether a chatbot is a right option, but also helps with key insights on the most value-adding features to build into the chatbot. Consider, for example, "Lucy and Bruce," the deployed by the University of Canberra to answer student queries about student services and class schedules.
This is just one example of universities and colleges using chatbots to reduce the load on their support personnel which helps save money and enhances the student experience.
The point is, organizations need to find opportunities where the immediacy, natural language, and learning abilities of a chatbot make it the most suitable approach to solving a customer service problem. The ability of a chatbot to provide valuable information is crucial for the user - that's the secret sauce you need to focus on.
Choose the right platform
Once you've zeroed in on the ideal use case, you will need to decide the platform for the chatbot.
Wherever your users find it easiest to connect, your chatbot must be available there. Whether it's via a website, through speech, or by typing, users have too many options, each with their own advantages. This means that your chatbot projects also need to consider all these forms and formats.
Remember, what's best for your team might not be the best for end users. Consider the example of NASA, where developers are used to utilizing Slack for most of their testing projects. However, since that's not what other NASA scientists are used to, they've also built a website where users can simply log in and use all kinds of bots.
Voice assistant app builder, text-based instant messaging app builders, social media messenger based chatbots, Alexa apps - there are several ways to build apps.
The choice of platform should be such that doesn't require end users to change anything about their information search process. It's for the chatbot to sneak in, and make the potion its own.
Know how to prove success
Receiving the funds for your company's first chatbot implementation might not be a challenge; getting the next ones financed could certainly be much more arduous. Unless, of course, you know how to prove whether or not something is a success or not.
It's not often that a chatbot will contribute directly to revenue. So ROI is not always feasible to calculate. Instead, the metrics you should strive to measure and track are:
1. Numbers of end users of the chatbot.
2. The average duration of a session (too short is as alarming as too long).
3. Number of sessions per chatbot user (stagnant or slow growth implies that users aren't getting answers to their queries).
4. Confusion triggers (the kind of inputs that cause the chatbot to fail in their response times).
Establish an escalation mechanism
It's been observed that user perception about chatbot effectiveness is positively influenced as far as the transaction (info search, purchase, ticket logging) is successful.
The most successful chatbots are the ones where a sophisticated escalation mechanism has been built right into the bot's workflows. Chatbots need human oversight to resolve complex situations. The two key methodologies to focus on are:
1. Make sure the chatbot documents and showcases the information gathered until the time it triggers the escalation workflow.
2. Make sure that the human agent is able to feed in structured data related to the resolution so that the bot can be improved with time.
Keep security considerations paramount
There just can't be such a thing as an unsecured chatbot, that's how well entrenched the notion of chatbot security is. The deeper the functionality of the app (example, a bank's chatbot that gives informative answers versus one that allows users to check account balances), the bigger the security challenges.
No wonder, enterprises prefer keeping chatbot capabilities to a minimum viable level, balancing off its security demands.
It's a real risk - your chatbot provides customer info to an unauthorized entity, and your business reputation could end up being like Facebook's and Twitter's business reputation after all those scandals in 2017 and 2018. The key security aspects of a successful chatbot strategy are authentication, data security, and end-user training. Of course, the more sensitive the industry, the more challenging the security aspects become.
The idea of perpetual chatbot development
Just like a human assistant becomes better with time, so do your business chatbots. Customer service is a type of domain where regional, cultural, and social differences of the customers massively influence the nature, quality, and course of their interaction with the chatbot.
The development team, hence, needs to step up and work closely with the human agents to make the chatbot scripts better over time.
This approach makes sure that regular users always feel that the same chatbot keeps on satisfying them over time, rather than merely being constrained within short boundaries of interaction limits.
Pick up any visionary list of technologies that are shaping the present and future for businesses. Chatbots are present in all these lists. The strategies we've shared in this guide will help businesses make their chatbots better than they were before.