The role of a customer success manager i.e. a CSM has transformed drastically in recent decades. For starters, it’s no longer grounded to its traditional role of transforming customer engagement. Instead, it aims to forge strong relations with customers such that it helps businesses grow, making it an important pillar of growth. Today, the responsibilities of a CSM have become very demanding. It expects them to coordinate between different departments, onboard new customers, advocate for the company, drive renewals, encourage upsells and cross-sells, build deeper relationships with the customer, have the ability to produce reports on all activity at a moment’s notice, and so much more! In a job that challenges and expects someone to be at top of all things all the time, how does this get done?
In every successful customer journey, there comes a point when you know that your customers are ready for more. But imagine a troubling scenario where the upsell hints are being missed or lost in the data. This can be really frustrating when your customers have already been deriving value from your products or services for months. They are comfortable and satisfied in the current engagement but could certainly benefit from more. This is the critical point in the mutual business relationship but either the signals are lost or the subtle indicators of a golden upsell opportunity are left undetected and unacted upon!
As a marketer in 2021, you must have observed the rapid changes in the last decade. Today everyone in your target audience has access to complete information, and customers increasingly know the exact details of what they want. One of the new challenges for marketers is to project value accurately, even within the smallest details of a product or service. Without this level of attention, it can feel like game over.
No matter how advanced artificial intelligence gets, it is still a drop in the vast ocean of human intelligence. Human intelligence is a result of consistent learning from experiences that help them gain knowledge and comprehend their surrounding situations, whereas AI learns from data and its programmed interpretations. Machines cannot think on their own, instead, they are programmed to consume data to mimic and simulate human behavior. However, rational decision-making is still a very human trait, and hard to mimic.