The Impact of AI on Customer Interactions
When you think of using artificial intelligence (AI) to improve customer experience, what comes to mind?
Some people might (mistakenly) think of it as trying to replace human beings with Siri or Alexa, or reducing individual customer needs to a faceless demographic. In reality, AI and machine learning are starting to have some surprisingly practical applications for improving customer experience. Let’s look at a few that people are starting to talk about nowadays.
1. Building a better chatbot with artificial intelligence
Years ago, so-called virtual assistants were touted as a way that businesses could save money and reduce the need for human interaction with customers. And while they have succeeded to some extent, some also developed a reputation for mis-interpreting customer requests, giving wrong answers, and standing as an impediment between customers and their needs. This article from uxdesign.cc does a good job of explaining many of the reasons why the chatbot-as-human-replacement strategy often fails.
Today, experts predict that a new generation of chatbots will be focused on dramatically increasing the reach and productivity of human agents. Imagine, for example, an AI-guided application that predictively suggests solutions and pushes information to customers under an agent’s control. In this article from CMO Australia, contributor Vanessa Mitchell bluntly predicts that in the future, the purpose of AI chatbots will be to augment human interaction, not replace it.
2. AI and predictive marketing
Competitive pressures are forcing marketing teams to target their efforts more efficiently than ever. This means that AI can serve as a natural extension to better targeted marketing efforts which, in turn, can lead to happier and more engaged customers. According to CIO Magazine contributor Philip Kushmaro, artificial intelligence now has the potential to predictively improve market segmentation, targeting accuracy, and improved interactions with actual customers.
3. Better content curation
How many of you out there love getting marketing emails?
The answer might be higher than you think when the content truly benefits people. When a shopper gets targeted discounts based on the things he actually purchases, a consumer gets content or offers keyed to a recent life event, or a psychotherapist gets information on new research or publications targeted to her clinical specialty, AI has the potential to help marketing actually make customers happier. In a recent article in MarTech Advisor, Lucidworks’ Lasya Marla notes that by learning patterns in content consumption, artificial intelligence can improve the marketing content you receive as well as your online experience as a customer.
One caveat for AI: garbage in, garbage out
As futuristic as AI sounds, its value is based on a relatively simple premise: AI applications fundamentally learn from data rather than programmed instructions. When a chatbot suggests a solution, or an AI application targets a market, their responses are based on the analysis of large amounts of past data. This is where the fields of AI, machine learning and data quality have begun to intersect.
The promise of artificial intelligence starts to fall apart when bad data leads to flawed predictions. For example, incorrect or bogus contact data – which represents as much as 25% of the average contact database, according to SiriusDecisions – can completely change the interpretation of a demographic and its purchasing behavior. (Of course, we can help with that.) The same is true for all of the other inputs that drive machine learning processes, making formal oversight of data quality more important than ever.
We’ve seen bold predictions about AI and customers in the past – and many of the areas discussed above still remain in the realm of future trends – but there is a renewed sense nowadays that AI now has real practical applications in the customer experience space. More important, capabilities such as these have the potential to become competitive requirements. It is an exciting time in AI, and the field is well worth keeping an eye on from here.