How To Conquer Customer Churn with AI
We’re living in the age of the customer. Thanks to the proliferation of data, customers are more informed than ever before. There’s been a seismic shift in the power dynamic between businesses and customers. Armed with empowerment, customers are demanding that customer experience be put on a pedestal. According to research by Walker, customer experience is slated to overtake price and product as the key brand differentiator by the end of 2020.
With this shift in the cosmos, customer churn is top-of-mind for all businesses. Forward-thinking companies are recognizing the value of leveraging artificial intelligence to avoid hemorrhaging customers. Artificial intelligence can be a game-changer in conquering customer churn. Here are four strategies to prioritize when harnessing the power of artificial intelligence for churn reduction.
Dirty data is the Achilles heel of artificial intelligence tools. There’s a common adage among machine learning and artificial intelligence experts that a 10% improvement in data is more impactful than a 100% improvement in the effectiveness of algorithms. Duplicate data, inaccuracies, and omitted information can all cloud your ability to discern the nature and extent of customer churn. More than one quarter (27%) of business leaders aren’t sure how much of their data is accurate. This can be a recipe for disaster.
Data hygiene is a prerequisite for artificial intelligence success. Before you take action and delve deep into analyzing churn, it’s critical to assess the quality of your data and establish a realistic baseline of your company’s data hygiene. If your baseline is subpar, it’s well worth the effort to invest in data cleansing solutions before putting churn models into motion.
Forward-thinking businesses proactively prevent data hygiene issues from rearing their ugly heads. B2B data decays at a staggering rate of 70% per year. By investing in data enrichment solutions, you’ll be able to proactively avoid falling victim to data decay. While data cleansing and data enrichment can pack a big punch, the single most effective way to boost data hygiene is to eliminate manual entry by embracing machine learning and artificial intelligence tools that automate data entry. Human error represents the most common cause of dirty data.
Customers are rarely overt about their intentions to churn. According to research by ThinkJar, an advisory and research think-tank focused on Customer Strategies, only one in 26 unhappy customers (less than four percent) will complain, the rest simply churn.
Armed with artificial intelligence, companies can pinpoint the precise reasons for customer churn. The virtue of artificial intelligence tools is their ability to supplant black-box analyses and assess a host—perhaps millions—of factors associated with customer churn. Using artificial intelligence, companies can determine the saliency of a wide range of factors underlying churn propensity, including demographic data such as age and location, firmographic data such as industry and decision making power, and sociographic data such as preferences and behaviors.
In a world of omnichannel customer activity, artificial intelligence empowers businesses to look holistically at all customer interactions, including offline and online interactions, to discern churn indicators. Artificial intelligence-powered tools that leverage natural language processing, for example, are able to perform sentiment analyses and assess customer reviews, emails, and even phone calls for tone and terminology indicators of churn.
Ideally, customer churn assessment should be conducted in real-time or as close to real-time as feasible. 33% of U.S. consumers say they’ll consider switching companies after a single poor customer experience. An astounding 85% of customer churn due to poor service is preventable.
