How data-driven chatbots are going to ensure success
The hype regarding chatbots can no longer be ignored. They have been on the rise for years, however, 2019 is thus far the flourishing chatbot era. It will come as no surprise that we can use the technology well for sales, marketing and service and therefore technology contributes to the achievement of our business objectives. Yet too often we see organisations starting chatbots to join the hype, without keeping the clear KPIs in mind.
Data from online conversations and knowledge hubs, for example, is broadly available. However, these data remain often unused in the process of developing a chatbot. This while data can help your organisation to get the most out of your chatbot. I have spoken to Software Engineer Gerben van der Huizen and Data Analyst Koen Hallmann about the added value of data for chatbots. This because the combination of insights and technology is the magic combination to ensure the best results.
To bot or not to bot; data has the answer!
‘Not because it’s necessary, but because it’s possible’ is the starting point for many organisations to start with chatbot technology. After all, it is interesting to keep pace, innovate, to see what technology can do and where opportunities lie. Still, it would help if our thoughts would flow from the goal point of view, rather than from the means point of view.
For example, when you use your chatbots for service, what is the purpose? Faster service and better response times? Accessibility outside opening hours? Or create efficiency for service employees by having chatbots prepare the work? The solution lies in data. Use the numbers available to predict whether a particular task would be cost effective if a chatbot would run it. Assess in advance if the chatbot can start to pay for itself and avoid incurring costs to develop a chatbot that does not meet your business goals.
Data analysis as a basis
Software Engineer Gerben van der Huizen and Data Analyst Koen Hallmann develop data analyses to predict the performance of a chatbot. A Chatbot Feasibility Report provides you with the necessary insights to consider developing a chatbot for your own organisation. Koen explains:
“By doing an analysis, you can choose a chatbot based on hard figures, instead of relying on intuition or fascination with the technology. By looking at a sample of online customer service conversations with a real linguistic view, you can also find out in advance where a chatbot wouldn’t work properly. That saves you a lot of irritation with your customers afterwards. This is often overlooked”.
The underlying idea comes from pragmatics, the task of linguistics, which is concerned with verbalizing and interpreting language.
“You have to find out what language act there is. A customer asks a question, but if the conversation is a complaint, does a chatbot have any added value? Is the answer that a chatbot provides to the customer a complete answer to the question? After you plunge into the depths in this way, you eventually make an overview of the figures. This total picture gives you the insight into whether and what a chatbot can do for you,” says Koen.
Data visualisation & ROI
Through an analysis of the data and a subsequent calculation, you are able to calculate the expected result of a chatbot for a specific task. By making this visual in a report, you’ll be able to prove to management why a chatbot would be appropriate.
“Don’t just start with chatbots, but look for where the real challenge lies. Have a realistic estimate made of the expected outcome in advance before committing yourself. But even after the launch of the chatbot, data is of added value. An analysis shows exactly what the performance of the chatbot is and whether it pays to expand it further. The effect is really made visible by this analysis and with this the management of organisations can also be included in the importance and development of chatbots,” says Gerben.
Creating a realistic view
When you start using data as a predictor of the success of your chatbot, it is important to ensure quality. Do not assume that a chatbot can be used anywhere. Technology is not a solution for every task. If an analysis shows that a chatbot is not suitable for a particular task, do not continue. So far, showing sympathy and empathy is really only for the human agent. Therefore, let them answer complaints or other negative experiences instead of having them answered by a chatbot.
“Bots can’t do anything with empathy. A chatbot can help you very quickly, but if you’re looking for reassurance, you can’t get it from a bot. A real person is an important backup that the bot can always rely on,” says Gerben.
Data-driven chatbots: 4 tips
- Develop your chatbot based on data-driven research and make sure your chatbot is problem-oriented.
- Make a problem or opportunity demonstrable in advance by insights from data instead of your own intuition.
- Stay realistic: does a chatbot most likely not deliver what you want? Then stop early or send the process to another, better application of technology.
- Always keep in mind that a chatbot must contribute to the customer experience. Avoid irritation and make sure that a chatbot connects seamlessly with your customer, but also that your chatbot does not get in the way of the customer and pass the baton on to the employee if that is good for the conversation.