The digital world is creating enormous amounts of data on a daily basis. Social listening and social media analytics have made it significantly easy for us to analyze and understand this data. Marketers have been using this data to gain insights into the minds of potential customers to inform their audience targeting efforts and their marketing strategy.
There’s nothing more effective than social listening to support these efforts to delve deep into the oceans of data on social media. Big companies are slowly coming to rely upon chatbots, backed by artificial intelligence and machine learning, to help them respond in real-time to the grouses voiced online taking their brand’s name. These chatbots are primarily programmed to engage with such messages based on the presence of certain keywords. They can be programmed to respond the same way each time or respond differently too. Respondents to a survey by Drift have said they would find chatbots to be of good use:
- When seeking a quick answer in an emergency
- To resolve a compliant
- To get detailed answers and explanations to specific questions etc.
Can Chatbots function without Human Intervention?
The answer, for now, is just ‘maybe’. This insight has been recently illustrated by a funny conversation that unfolded on Twitter recently. Not only did Amazon’s chatbot get confused over a sarcastic comment meant to mock the political crisis occurring in Maharashtra, India, it actually apologized to the person who made the comment and offered reparations. The incident involved four regional political parties in the state of Maharashtra in India namely, the BJP, the Shiv Sena, the NCP, and the Congress party. The parties were looking for alliances to build a sufficient majority to prove their eligibility to form the government, with a lot of party-hopping and horse-trading being involved.
As one Twitter user questions the need for the BJP to buy time to prove that it has the strength needed to prove its majority on the floor, another user offered a sarcastically phrased explanation, comparing the situation to how one needs to wait for orders placed on Amazon to be delivered.
Any (human) employee of Amazon would have laughed and moved on when the social listening tool pulled it up from the data ocean for review. But the bot, probably reading the mentions of ‘Amazon’ and ‘Delivery’ in the same sentence – even without any other negative expression – promptly responded with “Apologies for any unpleasant experience you had with regard to the delivery of your orders. Could you please elaborate on your concern? We would be glad to assist you.” Oh, really!?
Credit goes to Amazon’s team to review and delete the tweet quickly, but they weren’t quick enough to stop the Twitterati from saving the screenshot and sharing it onwards.
Social Listening for Customer Engagement
Social listening tools track brand mentions to draw relevant insights and help a brand engage with its audience base. Chatbots fulfill the need to provide instant, real-time responses which are so important when they want to make an unhappy customer happy.
Like all good things, it comes with a caveat. Using chatbots to provide automated responses could work but not without some amount of human intervention. At least, not until machine learning helps these bots evolve, making them really adept at sensing more from the words used and their context and tone better. For now, let’s just say that marketers and consultants should continue using social listening and chatbots to save precious time and wow their customer-base, but let’em also be hands-on when doing so.