Support bots are the present and future of first contact for customers who need help with our product or service. These AI-driven tools streamline the process of customer support such that you can immediately assist those in need of help and more reliably route them to those that can answer their questions and solve their problems.
Why you would need a support bot is quite easy to explain: You can automate certain aspects of support, increase conversion rates, offer a much-improved level of assistance, gain better customer engagement, more easily and reliably collect information from your customers, and lower your support costs.
So that decision has been made. You want or need a support bot. What’s next? That’s where things can get a bit tricky. Yes, you can always hire a third-party company to develop your bot and integrate it into your site, but that could get costly. The other option would be to develop it in-house. Thanks to open-source technology, creating your own support bot is a viable route for any business.
If you do go the in-house route, what will you need to make it happen? Let’s take a look at what you’ll need for a successful support bot deployment.
Well-defined purpose
The very first thing you must do is define the purpose of your chatbot. Will this be a multi-use chatbot or specific only to product or service support? This is a crucial step because it will help you decide what platform you choose how your bot conversation will flow. You should ask yourself (or your team) questions like “Why are we building this chatbot?,” “What are the most frequent problems customers have?,” and “What features do we want for our chatbot?”
You need to have a solid plan for your chatbot, well before going into the development stages. If you fail to create a well-defined purpose for your chatbot, you’ll wind up trying to do too much with it, which will only end in a failed experiment. You’ll want to know what the purpose of the chatbot is, who the chatbot will serve, and to what extent it will assist your customers.
Choose a chatbot platform
You also need to choose a chatbot platform. This doesn’t necessarily mean you must go with a third-party hosted chatbot. There are plenty of open-source chatbot solutions that you can use (such as Botkit, Botpress, Rasa, Wit.ai, and OpenDialog). Just know that if you go the open-source route, you’ll need developers on your team that can integrate it with your current website.
Many proprietary chatbot platforms make it much easier to integrate into your site, but they might be costlier and more limiting in what you can do with them.
Developers
If you opt to go the open-source route, you’ll need developers skilled in one or more of the popular languages used for chatbots. At the moment, the most popular languages for chatbots include Python, Clojure, Ruby, Lisp, and Java.
Many open-source chatbots come in the form of a framework, so your developers will need to understand how to effectively use those tools.
A conversation flow
This is where the rubber meets the road. Once you’ve gathered all the developers and software together, you must design the chatbot conversation. No chatbot has reached the point where it can simply jump into the conversation without first having a script designed. This is done by creating triggers, decision nodes, and action blocks.
For example, a user launches the chatbot, which triggers the initial interaction. The customer will then ask a question that requires a decision node (for example, Customer A wants help with Product X). Once the decision node arrives at a conclusion and an action block (such as entering an email or serial number for a product).
These conversations can take considerable time to create and you have to create numerous conversations to all the possible use-cases the chatbot much handle.
Time to train the bot
Once you’ve created the conversation flow, you then need to train the chatbot. This is only necessary if your chatbot uses artificial intelligence. If your chatbot is a simpler, rules-based bot, you can skip this step.
For those AI-powered bots, this will be a crucial step in creating an effective support chatbot. During the training period, you’ll use existing data sets (emails, support tickets, and other conversation threads) or purpose data sets from a third party to run against the bot so it can learn how to correctly respond to interactions.
Effective bot training is all about predicting what users will say and getting the correct response. For this, you need to know three key elements: Utterances (something a user might say), intent (what a user’s utterance means), and entity (parts of a user’s utterance that make it more clear such as “today’s” and “weather” in the utterance “What is today’s weather?”.
In the training process, you must make sure your:
- intents are distinct and contain numerous utterances.
- entities are purposeful.
- chatbot has a personality.
- chatbot doesn’t rely only on text.
Time to test the bot
Finally, you must take plenty of time to test your chatbot. One of the most important aspects of the testing process (besides taking the necessary time to effectively test it) is to make use of a diverse testing group.
You don’t want to only use those who are close to the project (such as the developers) to test your bot. Recruit people from other departments, so you’re getting completely different verbiage thrown into the testing process. The more diverse your testing team is, the more accurate your results will be. If you’ve trained your bot to only succeed with input from specific user types, and you only test with those same types, you won’t know how and if it will fail when other personalities, nationalities, or skillsets use the tool.
Conclusion
Adding a support chatbot is a great way to effectively handle first contact with customers. Not only that, but support chatbots are means to a cost-effective end that can pay off in ways you might not be able to see at first. Customer engagement and satisfaction will dramatically increase, which will have a direct impact on your bottom line.
The process of adding a support chatbot might be time-consuming, but the end result will pay off and your company and your customers will flourish.
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