As with other aspects of customer-technology, first there was the task, then came the data and then the need to manage and use it properly. Customer spreadsheets and databases became CRM tools, point of sales records became data for recommendation engines and marketing, and so on. The same is true with chatbots, as businesses look to leverage the data they provide to add value.
Chatbots are rapidly changing the way that businesses interact with their clients, and how data is provided to their systems. It isn’t a massive change from previous generations, when a sales database became a tool for the whole organization to use, but still represents a change in how companies will work.
Naturally, all of this assumes that the data is being stored in a suitable manner, following GDPR and other suitable legislation, and that the users have given explicit permission for you to use the data. If your chatbot doesn’t ask or your terms and conditions aren’t crystal clear, and accessible, then you can’t use their data however you see fit.
It also depends on your chatbot’s pedigree, early bots didn’t save any information, some now keep records in the cloud, while advanced examples, perhaps as part of a business suite or framework, tag the information to customer service or sales records to build up the knowledge of the customer. (We will now sing the IT hymn, “Everybody hates a data silo.”)
To ensure you can make the best use of data, the chatbot needs to provide it in a suitable format, with useful feedback, an audit trail and ensuring that only legitimate users can access it for proper uses. Failure to do so not only leaves a fresh source of valuable information untapped, but if you do go about it in an ad hoc manner, could leave the business in legal peril.
Having established all that, where is the value, and what can it be used for? The value lives in the huge number of chatbot interactions that businesses see on a daily basis. Consider an airline or customer service chatbot helping thousands of users on a daily basis.
Chatbot-interactions provide the business with data to predict trends, for example:
- Why are lots of people suddenly typing “staycation” in a tourist chatbot?
- Why has demand for a company’s 2018 model dropped off a cliff?
- Why are there more support queries for this updated product over the older version?
All simple questions, that could be answered over time using other systems, but through chatbots become a live source of data, providing instant information. Chatbots, either by text, voice or emoji, through quick survey rating questions can also provide feedback on the quality of products and services. That can help speed up problem resolution and other issues, while highlighting how businesses can update their chatbots to feed more information into the pipe and use it across a wider range of services.
All about the data
For a first chatbot, the data can help improve its own service and help customers with better answers, but as a company gets used to operating bots, more options become available. Chatbots can provide data for marketing, revenue-generating services, bill payments. That data through analysis can improve future services and guide the business to better AI services and smarter chatbots as they move from discrete services to a joined-up part of the business.
For any business looking to get better value from their chatbot, the link to analytics tools is the key feature, and then a joined-up approach to asking the right questions and getting metric-based feedback or having the right automated analysis in place will provide winning results.
Much of this will all be done by AI in the very near future, with alerts and updates informing executives or decision makers about changes or thresholds being passed. Those alerts can inform decisions in customer support for any business, product ordering for retailers, choice in ranges and styles for fashion houses or increases/decreases in services for transportation.
When planning or launching a chatbot, there is no excuse for ignoring the results it produces and gaining the maximum value from them to help the business improve its service.
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