Artificial Intelligence (AI) has been heralded by many organisations as the answer to a myriad of business tasks, such as data analysis, stock management and customer service. Behind the scenes, AI is being used to drive automation and efficiencies that make businesses more responsive to customers in relevant ways to augment staffs’ abilities, and empower them to have more personalized and helpful interactions. AI is also being harnessed to improve the customer experience by intelligently listening and responding to customer feedback and making connections that would most likely elude a human.
In recent years, brands have started to take the journey approach they’ve applied to customers — viewing their interactions as a series of distinct, yet connected experiences – and applying it to employees. Employees sit at the intersection of your business and your customers’ experiences, and thus have a unique perspective on what’s working, what’s not, and most importantly, why. AI can be utilised to ask employees for their perspective at key moments, for example, immediately after they’ve resolved a customer concern to support in improving overall customer experience.
Learning from the customer journey
Customer demands continually change, with shifting expectations and competitors creating new barometers, metrics and points of comparison each and every day. Nearly all brands survey customers about their experiences, and to a widely varying extent, use that intelligence to make improvements. While this myopic approach may have worked in the past, it will not continue to work in the future. Consumers interact with increasingly sophisticated technologies through multiple channels on a daily basis, and in the process, gain increased expectations of timeliness, personalisation and ease. For example, dating site apps provide user-friendly, intuitive experiences, whilst many banks offer mobile banking to enable customers to lot into a personalised mobile app and move money with scan of their fingerprint. This means when a customer interacts with a brand and the experience is perceived as more difficult or even archaic in their use of technology, their view of the laggard brand will be tainted. Despite its clear benefits, only one in five businesses across the globe, out of 3,000 surveyed by MIT Sloan Management Review, have adopted some form of AI in their operations. Those brands that readily adopt AI will have a vast range of data at their fingertips and will be able to make critical business decisions much more easily and provide experiences that meet customers’ continually changing expectations.
Forward looking brands are already turning to AI to drive automation and augment human interactions to be more responsive to customers in relevant ways. For example, AI technologies embedded in customer experience feedback can aide in channelling customers to the “right” customer service agent with the suitable emotional and professional background, armed with the customers’ past and recent history, as well as recommendations on how to best engage. Emerging “whisper bots” may serve as virtual real time counsellors, analysing a customer’s words and tone, and then providing coaching to front line staff in the moment of interaction.
Empowering employees with AI
Leveraging AI to empower your employees is one important application of this technology. Wise brands are also harnessing AI to bring employees even deeper into the customer experiences. Specifically, it can be used to prompt follow up questions within an employee and customer experience feedback programme, keying in on what the employee is saying, analyse the data individually, and in aggregate, and then report this intelligence to the relevant people and places across the business who can make changes and key into opportunities. For example, if the AI senses a spike in employees mentioning that customers are calling in with questions on how to operate a product and finding that the problem stems from a part that’s malfunctioning, information can be automatically routed to product, marketing and customer care. Not only does this address customer satisfaction and efficiency issues, employees experience less frustration and a higher level of satisfaction in their own jobs.
The key is harnessing AI across a full range of listening, analysis and reporting processes – in an always-on, systematic fashion – to what employees have to say about both their own experiences, as well as the customer experience. Giving them ownership, as co-creators of the business’ success, creates a fundamental shift in the way employees view and engage in their own jobs, in the success of the brand, and in the relationship with the customer. It’s a non-zero-sum game.
Beyond making efficiencies, AI can be used to understand how employees are faring along their own journeys and professionals and help prevent turnover. The biggest challenges when it comes to understanding employees’ attitudes towards their work and the wider business is keeping open communication. By applying the same technologies and practices more common in customer listening to more systematic and deliberate employee listening, businesses can keep up a continuous flow of understanding about their employees and gain valuable insight into their engagement levels and whether they’re likely to leave the business or perhaps be a key candidate for promotion.
Employee turnover is a key area that if tracked and better understood, major savings can be made. There comes a certain time in the employee journey when they begin to question if they’re a right fit in the organisation. This rings especially true in high-turnover industries like retail, food and hospitality. Predictive technology can determine when an employee’s engagement drops and use this to proactively intervene and provide critical support, reducing turnover and lowering the costs of replacing human capital.
With high training costs and the potential for reduced workload with new staff, retaining employees – even in high-staff volume sectors – is much more cost effective. By closely analysing the employee journey brands can better understand why an employee becomes engaged or disengaged, whether they’re a new hire or a long-time employee.
AI also works to spot patterns in historic data to predict future behaviour. If the data shows that engagement falls at a certain point for specific roles or at distinct milestones, then there is the opportunity to try to change that pattern, and break that cycle. If there is something more profound, for example the company often acts as a stepping stone for millennials in their careers, then being mindful of this pattern can help ensure that recruitment is set up to deal with this engagement curve. As a result customers don’t suffer due to unpredictable employee churn, and their satisfaction does not take a downturn.
Artificial Intelligence should be seen by organisations as a key area of investment over the next five years. Besides improving operations, it can help analyse the points of truth along an employee journey, inform employers about why and when an employee becomes disengaged, and alert managers so they can take the most effective course of action.