Chatbot QA, done right, deliver next-level customer experience. They’re convenient, personalized and make it easy for customers to get answers. There’s a reason you see them popping up on the websites you’re visiting. People would much rather converse with a bot and get a quick answer than wait on hold for the next available representative.
Using automation to save people time is exactly why chatbots are on the rise. Customer service is just one example of the many industries chatbots are being deployed in to make both customers’ and employees’ lives easier. But before chatbots can evolve to that level of complexity, there’s a key component that needs to be addressed: quality.
If you’re beginning to visualize how a chatbot could streamline operations for your company, don’t skip reading this article on quality assurance (QA). It’s the key to making sure every dollar you invest in this technology pays you back in productivity, customer experience, and sales/savings.
When Chatbot QA Isn’t the Focus, Customers Bail
Chatbots are efficient and customers love to interact with them; that is, until they don’t…
In fact, 40% of chatbot users disengage after just one interaction. The reason for this departure: Bad chatbots didn’t undergo appropriate chatbot QA (quality assurance) before being released into the wild.
Amazing customer experience is key and chatbots can deliver that, but when the solution goes sour, news travels fast. We’re more likely to read headlines about terrible (or even scary) chatbots than we are to read about the marvellous examples businesses are creating.
So, it’s imperative when you are executing a chatbot solution for your business, you get it right, the first time. Customers will be impressed, stick around for longer, and that has a direct positive impact on your bottom line.
What QA to Look for When Selecting a Chatbot Solution
No matter the budget or scale of your chatbot solution, you need to ensure it incorporates appropriate QA throughout the entire development process. Whether you develop the bot in-house or outsource the project management to a Chatbot consultant, make sure your solution includes the following chatbot QA feedback loops:
1. Define Specific Use Cases
The first step to ensuring a quality chatbot deployment is to define, very specifically, your use cases. Brainstorm with your team a shortlist of the possible use cases and for each of those, define the expected business result.
From that list, select one use case and define, in as much detail as possible, the exact business application. Document what the chatbot will do, what KPIs will indicate success or failure, and how exactly the chatbot will contribute to company-wide goals.
Don’t be afraid to narrow in. Being very clear about your use case, and simplifying it further than you might think necessary, will help with the QA process. If you and your team know where you are headed and have clear guideposts along the way, the simpler the use case, and the easier it will be to know you’re on the right track.
2. Develop a Proof of Concept
Now it’s time to kick-off the chatbot development team. But rather than jumping right into creating the final chatbot solution, agile processes should be used and a proof of concept should be the first step. This ensures the minimum possible development spent before the first quality feedback loop.
Agile Chatbot Consultants will advocate for small development steps to ensure all parties are happy with the result. If you happen to be spearheading the project with an internal development team, make sure to rein them in so the first prototype is simple, and has just enough detail to allow for testing and QA.
Before the chatbot solution reaches the eager fingers of customers or employees, gather a small team of users to test the product out and provide honest feedback. Let the solution work for a couple of weeks and gather as much data as you can to detect any issues early on.
3. Deploy a Minimum Viable Product
The minimum viable product (or MVP) is yet another feedback loop, but one that incorporates a larger pool of test users. The MVP will also be detailed and polished enough it could be launched onto your public platforms. But it’s also not over-developed in the sense that you haven’t wasted development dollars on a product that requires some more improvements.
Feedback loop #2 can now commence. You’ll be able to receive feedback from a larger user group and you’ll continue to collect data from the chatbot itself. As soon as issues are flagged, they can be addressed and corrected. Real data now inform the final development process, making sure your bot is on track to do what you intended without any surprises.
4. Commit to Continuous Chatbot Improvement
One of the greatest characteristics of chatbots is they inherently improve. Conversational AI gets better and better at anticipating the user’s intent and providing the correct solution.
So even without additional development or updates, the chatbot will improve, making the most of your investment.
However, human QA is still required to ensure the chatbot is continuing to deliver value to the end-user. A team member will need to check-in periodically and make sure the improvements the AI is delivering are, in fact, improvements.
This is yet another feedback loop to ensure a quality product customers/employees are happy to use. And this step doesn’t take much additional time, because chatbot dashboards and backend systems should already be set-up to collect and display important data for humans to decipher and use to drive business decisions.
Chatbot QA: Test, Test, and Test Again
While these many stages of testing and ensuring quality may seem like overkill, it’s this attention to detail and planning that will ensure you don’t have a chatbot blunder on your hands. The logical, agile approach to development will ensure bugs are found early, mitigating the cost of course correction.
Your chatbot solution needs to be extensively and continuously tested before and during its launch to make sure customers are delighted, and not turned-off, by your chatbot. This way, you’ll preserve your company’s brand and its dedication to deploying useful, quality solutions for its customers and employees.
Have you wondered what a typical agile chatbot development process looked like? Check out our process flow chart here.