A digital twin of a customer is a virtual representation of a real-life customer that can be used for a variety of purposes, such as marketing, customer service, and product development. The digital twin is created by collecting data about the customer, such as their demographics, purchasing history, and online behaviour. This data is then used to create a detailed profile of the customer, which can be used to better understand their needs and preferences.
One of the main benefits of a digital twin is that it allows companies to personalise their interactions with customers. For example, a retailer can use a digital twin to recommend products that are likely to be of interest to a particular customer, or a bank can use a digital twin to identify customers who are at risk of defaulting on a loan.
Another benefit of a digital twin is that it can be used to improve customer service. For example, a digital twin can be used to predict when a customer is likely to need assistance, and to route them to the appropriate customer service representative. In addition to these benefits, a digital twin can also be used to improve product development. For example, a car manufacturer can use a digital twin to simulate how a particular customer will interact with a new car model, and to identify potential issues before the car is built.
Now let’s get back to the source of my envy. HR departments sit on so much employee data, but we were never able to optimise the use of this data. I felt jealous because for many years, I was unable to do what my colleagues in sales and marketing could do – create digital twins of people.
But with advanced people analytics, this is about to change.
There is no doubt that HR has more data about an individual (an employee) than sales and marketing teams have (customer). In HR, we have an employee’s CV and personality data (gathered via recruitment), full employment history with us (via payroll) which tells us where the employee lives, if they are married, how many dependants they have, and even how much leave they have taken and for what reasons. Additionally, we have performance data, training data and employee listening data (engagement). In fact, we have so much data that sales and marketing teams should be jealous about the richness of individual data we have.
Through advanced people analytics, we can create digital twins of employees (DToE). By using individual data, we can create virtual representations of employees and use it to understand their needs and preferences. Through DToEs, we can personalise the employee experience throughout the employee life-cycle. HR can predict future employee behaviour and adjust engagement around that. For example, we can predict which employees are at risk of leaving the company and engage with them pro-actively. We can develop or amend HR policies like rewards and benefits, training, succession planning around actual individual needs and interests and move away from the one-size-fits-all approach we normally follow.
In the same way digital twins of customers can cultivate customer loyalty and spend, so can our digital twin of employees be used to cultivate engagement, loyalty and productivity.
Overall, a DToE is a powerful tool that can be used to improve the employee experience, increase productivity, and reduce HR costs by focusing on interventions that will guarantee a higher ROI.