As more and more consumers depend on digital channels, a lack of empathy can increasingly damage brands as online shoppers simply take their hard-earned cash elsewhere. Indeed, research by PwC revealed that 32% of consumers said they’d stop doing business with a brand they loved after a single bad experience. Meanwhile, when people feel valued, organisations gain up to a 16% price premium, plus increased loyalty.
Technology is essential, but we should never forget it’s also just an enabler. Human touch remains the other critical part of the equation. So, it follows that concentrating solely on technology doesn’t improve the customer experience (CX) (aka human experience) by itself. Instead, it’s about developing a team culture focused on winning the hearts of their digital customers. Then taking advantage of technology and CX data to iterate digital journeys that offer emotional connections on par with our expectations for face-to-face interactions.
To do this, companies must be customer-centric, data-driven and empathetic.
Prioritising humans over numbers
Companies are au fait with using quantitative tools to understand the digital customer experience: gathering data and analysing it via dashboards, charts, and graphs, however, this doesn’t get to the core of how people interact with products and services.
By looking at a graph, you can’t tell how frustrated customers are when they scroll through confusing design elements or rage-click on broken features. Data alone doesn’t help you empathise with what the person is experiencing. Even if your data experts or analytics team can empathise, that isn’t enough. Relying on a few siloed people is unlikely to help the wider company develop insights and find ways to better serve customers.
And so, a disconnect emerges between collecting data and understanding your customers. The good news? The issue isn’t insurmountable.
Turning impersonal data into customer empathy
The disconnect is less prevalent in the bricks-and-mortar world. Why? Most customer interactions are face-to-face, so acting on data is far more intuitive than in the digital sphere.
To paint a clearer picture of what this means: if shoppers keep bumping into a display on the way to the fitting room, the manager doesn’t need a spreadsheet to realise they should move the display. They empathise with the customer and take immediate action to remedy the situation.
If eCommerce businesses are to become truly customer-focused, they need to do more than observe what’s happening. Instead, they must inject a healthy dose of empathy into their data analysis. That means delving into the ‘why’.
For example, let’s suggest that more people than usual are abandoning their shopping carts at checkout. That indicates a problem, but identifying impactful fixes takes more information and an empathetic approach. With that in mind, imagine you’re armed with the following additional facts:
- Most shoppers are ditching their carts while attempting to enter their email addresses.
- Your checkout process only accepts verbatim emails, so if a person accidentally adds a space at the end, their submission is rejected.
- Most customers who don’t end up following through with their purchase hit space after inputting their emails.
This data provides a more complete picture. You feel an emotional connection with your customers and understand their frustration, making it easy to visualise the experience and implement a solution.
Of course, empathy alone isn’t enough to run a business but by identifying customers’ struggles and understanding their impact, ‘quantified empathy’ develops. Also known as empathy at scale or analytics with heart, it’s about recognising pain points and assessing the effect on metrics like revenue. Isolated insights become a thing of the past, and you drive forward with a customer-centric approach. By humanising otherwise impersonal data, teams make more strategic, revenue-generating decisions based on evidence and data coupled with empathy.
The journey to empathetic data-driven decisions
Reaching this stage involves technologies, but organisational culture also plays a role: ensuring your employees want to help customers and are equipped to do so. If you rely on just a handful of highly skilled analysts for insights, it’s harder to build a customer-focused, data-orientated culture. Why? Because the tools are in too few hands.
Indeed, it’s hard to develop empathy (let alone solutions) if you’re a customer support agent who must wait days for answers to data-related questions. Therefore, company-wide access to collaborative, real-time data insight tools is a must. In turn, voices and teams become more aligned rather than in competition.
Becoming a data-driven enterprise takes more than simply rolling out software; it involves rethinking every employee’s relationship with data and customer experiences. To facilitate that, workers need a common source of data, which in turn naturally dismantles work siloes. At the same time, your unified dataset must support front-end experiences for an array of users, from digital marketers and store assistants to the C-suite. These players have varying needs; they use quantified empathy to improve customer experiences in different ways.
By implementing these enhancements, rapid and iterative CX improvements are possible – essential if businesses are to keep pace with the increasingly unpredictable digital-first world we’re living in.
Injecting quantified empathy into your analytics
The concept of data being able to generate emotion seems alien to many of us. The meeting of binary language and the very essence of what makes us human feels like a stretch, and yet it’s vital to understand what hundreds of thousands or millions of visitors to your site are doing.
To meet (or exceed) customer expectations, quantified empathy is key, as is a single version of data that’s easily accessible to all workers. Only then can you identify and prioritise what matters most to customers and react with speed and confidence to enhance their experiences.
