Ever been to a restaurant, ordered one thing and received another? It’s fair to assume that you weren’t dying to return. Or ever been put on hold for a frustrating amount of time, only to be told to wait on hold for longer whilst transferred to the “appropriate” department?
These are experiences that the majority of every day customers have unfortunately had to endure. There is a growing intolerance on the part of customers to have fragmented experiences when doing business. And there is a price to pay for doing so. Research with the CMO Council found nearly half of North American and European consumers will abandon a brand and take their money elsewhere if they repeatedly encounter “a poor, impersonal or frustrating customer experience across channels of engagement.”
The digitally savvy customer of today wants access to everything, anytime, anywhere and on any device. And brands cannot opt out from the disruption that digital technology creates. They need to be available for their customers in the fashion that they need. They need to be able to respond to the changing demands of their customer.
However, the first challenge brands face is that they don’t really have a clear view of who their customer actually is. Pragmatically, this means that brands must invest in processes and systems which create a holistic view of their customer and find insights which can be used to personalise every interaction – from marketing and sales, through to delivery and billing.
The path to personalisation
Achieving a personalised customer experience requires using context to tailor every interaction, whether with a customer or a with a system. As a basis for context you need information which answers three key questions:
1. What have they done? This can come from internal systems, or from outside of the enterprise. By looking at the past – what they’ve purchased, where it was delivered, when and how they paid, what they posted on social media, how their last customer service issue was resolved? Brands can build a historical backdrop for the current interaction.
2. What are they doing? This is the real-time insight which is only revealed by looking at data which is often unstructured and underused. Server logs can reveal current browsing behaviour, app-based geo-location data can reveal where customers are and even the channel which they are choosing to interact on carry implicit signals which can be used to create context.
3. What are they likely to do? Businesses can make use of artificial intelligence (AI) solutions to analyse past and present data to predict future behaviour or desired outcome. This serves as the basis for anticipating the customer’s need.
These three sets of information become the context for the interaction, helping employees or systems decide on the right offer, the right greeting or the right message.
The fine line between personal and creepy
Many companies fall into a trap of believing that a hyper-personalised experience is always better, but this isn’t always the case. Overdoing it can feel invasive to the customer. In fact, our research shows that most privacy concerns among customers stem from a lack of transparency, and that the fastest way to lose a customer is to use their data without their knowledge.
The best approach is to allow each individual to decide how personalised they want their experience to be, by offering them transparency about what data is being collected and asking their preferences for how it is to be used. This consent-based approach builds trust with the customer and allows them to individualise their experiences based on exactly what data they are willing to share, which is ultimately the experience they are looking for.
Catering to the customer of tomorrow
Customers have never fundamentally changed. They have always wanted a consistent buying experience and the best price they can get. However, the tools at their disposal to secure both of those things have changed tremendously in recent years and the pace of that change continues to increase. The web, social media and chatbots have placed the power of information – products, prices, reviews, etc. – squarely into the hands of the customer, challenging brands to transform their customer engagement models.
The flip-side of this transformation, however, is that customers are leaving extensive digital footprints which allow savvy businesses to compile rich customer profiles. By employing AI, these profiles can be used to understand the individual, creating context for each interaction. This customer data can also be analysed in aggregate to identify trends and opportunities upon which brands can capitalise.
All interactions with customers now present brands with opportunities to collect data. If they fail to use that data to deliver excellent services, customers will go elsewhere. Customers are looking for a personalised approach that supports them when they’re looking for help while also rewarding them for loyalty. Aim to overshoot their expectations to be rewarded with repeat business.