As we read in the first part of this blog post, the chatbot space is relatively new. Not all bots are equal, and not many are configured around Artificial Intelligence (AI) yet. But that’s gonna change real quick. Know more about chatbots and customer analytics.
Remember, bots are built with a purpose. For now, there are two types of chatbots out there – one built with limited programming for a limited purpose, and the other with AI, where the bot learns on the go. The latter is still rare.
But as your bot starts to get traction, you are suddenly staring at an abyss, one you never thought existed. That hole is analytics. Analyzing data left behind by your customers is something your business will need to consider if it does deploy chatbots. In fact, the two go hand in hand. Bot analytics provides brands with an opportunity to go even deeper into their data analysis.
After all, every company needs a set of tools to gain insights from its customer interactions and analyze them correctly. Chatbots are one more addition to the toolkit. By using analytics generated by bots, brands can make strategic as well as tactical decisions about customer service.
Another business area where bots can help Enterprises is to augment the importance of Big Data through their automated data collection. AI bots can automatically add to a customer profile by progressively seeking additional information during customer interactions.
In customer analytics, chatbots enjoy one advantage over traditional data collection tools – it’s their very nature. Chatbots network directly with customers, in real-time, not via a 3rd party, such as a social network. This means that, rather than a brand having to collect data for analysis from scattered sources, all it needs to do is extract the data made available by the bot. After all, analyzing the various actions a potential lead or customer takes across multiple touchpoints in their journey is crucial for taking follow-up action.
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A bot analytics platform allows Enterprises to primarily do two things: increase user engagement and acquire new customers. Such a platform can deliver high value from an extensive data set within a short period of time, something that would take a human analyst longer to process.
Analytics dashboards targeted explicitly at the customer, such as those provided by Express Analytics, can easily be configured to incorporate bot-centric inputs to bolster industry-standard metrics such as engagement and retention.
But do remember that chatbots are still young. They are coming to terms with the collection and treatment of large quantities of data that will only grow exponentially over time. 1st gen bots, believe it or not, may not be as accurate or as a fail-safe as many of us believe them to be. Some experts think that human biases are bound to creep in during their development. This could affect the analysis of the data the bots have collected. For now, periodic human intervention to analyze the analytics is necessary if an Enterprise wants to ensure that its strategic plans are based on accurate facts.
