Disrupter 8 – Household Customer Service Approach: Using Predictive Analytics in Customer Service

By Mandeep Singh Kwatra, HGS VP Solutions and Capabilities

Earlier this year, HGS released a white paper on this year’s 10 customer experience disrupters—those that are sure to alter the CX landscape this year. Over the next couple of months, we’ll dedicate a blog to each of these CX game changers. Here we dissect Disrupter No. 8, the Household Customer Service Approach, highlighting use of predictive analytics to optimize customer service, for consumers and companies alike.

Top 10 CX Disrupters

Over the years, customer service professionals have done an excellent job collecting customer data on every call such as the customer’s first name, last name, serial number, account number, and address. However, customer service has fallen short in  linking customer records by family or household. Why is knowing exactly who makes up the household important?  The answer is the value this information provides in previously untapped cross-sell or upsell opportunities. In coming months, expect to see more companies leveraging the power of predictive analytics: knowing the household could be key to this strategy.

Each household has people in different roles. You may be in touch with some customers from a household who use your product or service; however, they may not be the influencers in that house when it comes to purchasing decisions.  Connecting customers to each other within the household presents companies with many new cross-selling and upselling opportunities. When some members of the household are already familiar with your brand, selling becomes easier than within the context of a typical new customer acquisition with no familiar influencers to power the decision.

Once customer service succeeds in connecting customers to households, predictive analytics presents opportunities to study patterns for possible cross sell and up sell opportunities. With the knowledge of which household a customer belongs to, predictive analytics can be used to gauge major household events and shopping behavior within the entire household. Predictive analytics holds the capability and power to preempt situations and signal brands beforehand about possible customer behavior. A recent study by Forrester, on behalf of Everstring, found that 78% of marketers see their prospects’ buying journeys becoming more complex and nonlinear. Predictive analytics is helping marketers make sense of an increasingly complex world where customers hold the reins most of the time.  Companies can meet these expectations if they can forecast customer expectations and behaviors before they  even appear on the horizon.

Predictive analytics in customer service will eventually make customer service more efficient by making it easier to link customers to households and anticipating customer requests and issues in advance. Blending this with customer service professionals who are prepared and empathetic can lead to optimized and personalized customer service.