Pre-sales customer service spans activities to support a customer before they make a purchase. Data at Forrester shows that uncertainty inhibits purchase decisions – especially for online shoppers who buy products that they have never experienced in person. Many customers will abandon an online purchase if they cannot find a quick answer to their most burning questions.
Customer service organisations can intervene in the customer journey via an invitation to chat or co-browse at points of struggle or abandonment, like during checkout, or session inactivity. They also intervene opportunistically at points in the journey best suited for customers to accept a coupon, an offer, or additional advice. They accomplish this via analytics; intent models determine the best outcomes and machine learning refines them over time.
Organisations can also recommend personalised cross- sell or upsells. They use predictive models and machine learning to target customers based on buying propensity, demographics and psychographics.
AI-infused onboarding increases customer engagement
We know that properly onboarded customers are less likely to churn and more likely to purchase additional products, boosting their average lifetime value. Organisations must invest in customer education, feature discovery and in-product guidance, as these activities take the customer through the first critical steps to success. Organisations apply AI capabilities for onboarding activities such as customer activation, tracking a customer’s health and predicting customer satisfaction. In fact, they are starting to use real-time satisfaction predictors for incoming incidents to identify in-flight issues and customers who need immediate attention. They use algorithms that calculate satisfaction scores from attributes such as wait times, reply times, incident details and effort metrics, and then decide on what escalation actions to take if they receive poor scores.
AI-infused post-sales customer service builds trust
Thirty-seven percent of Australian consumers say that customer service greatly influences consumer choices of products and services. Smart companies turn aftersales service into competitive advantage, applying AI capabilities for a range of activities that span search and knowledge discovery, automating conversations via chatbots, automatic case classification that can shave off tens of seconds of call wrap-up time and contact routing.
They use robotic process automation (RPA) to automate process steps or even entire end-to-end processes, such as account onboarding or insurance claims, with humans typically only managing exceptions. In fact, AI has found great success in field service operations. AI-infused field service technologies build models to calculate the time for each technician to complete a job based on skill, personal aptitude and historical performance. They then optimise scheduling and resource utilisation to assign the right field service worker to the right job and ensure that they have the relevant information and appropriate tools when heading into the field.
AI is a journey. You can start small, and use AI to increase efficiency and reduce friction in the customer journey. As you move up the maturity curve, AI-fuelled engagement can enhance customer engagement, allow you to take proactive action and even pre-empt the need for customer service.