To say we’re living in a customer-centric age is an understatement: companies who fail to prioritise the customer experience are outpaced by their CX-leading competitors by nearly 80%. Additionally, more than half of companies have experienced a serious drop in consumer trust, resulting in an estimated missed $180 billion in potential revenues, according to this Accenture study. There are numerous reasons consumers lose trust in brands they once knew, loved, and purchased from frequently, but 71% of consumers say poor customer service contributes to that trust erosion.
Unfortunately, many tactics that once served an organisation well in engendering a customer-first culture simply fail to keep up with the enormous increase in both customer data, and the use of connected devices. Two and a half quintillion bytes of data are created each day at the current pace, and Gartner predicts there will be more than six connected devices per person as early as 2020. This device proliferation and increase in data results in an overwhelming number of touchpoints that must be tracked and connected to the customer’s buying journey. It’s a tall order, but the organisations that will win are those that can use all of this data to scale the customer experience quickly, efficiently, and effectively, and all on the customer’s terms. It’s not just enough to collect data: it needs to be the right data that can be acted on at the moment.
Work With the Customer Where They’re Comfortable
The digital age has changed where, when, and how customers interact with a brand. What was once a simple cycle of seeing an ad, making a purchase, and repeating, has shifted into a looping journey with the potential for numerous friction points that can turn a customer away from a brand all too quickly. McKinsey describes this journey through four critical areas: consideration, evaluation, purchase, and post-purchase experience.
Instead of assuming a consumer will immediately be faithful to the previous brand purchased, McKinsey states that today’s buyer continues to consider new brands available to them. McKinsey adds the element of the Loyalty Loop, which fast tracks future purchases, but in order for a brand to effectively qualify for this shortcut, they must have fostered lasting loyalty with the customer. And 95% of consumers say customer service is important in their choice of brand loyalty. In other words, helping a customer find the answer they need quickly is a significant indicator of whether or not a brand has continued ownership of that customer’s wallet share.
An additional complication is an increase in possible touchpoint locations: digital searches, email, social media, websites, and more. In fact, 31% of millennial customers looking for help reach out to a company via Twitter. It’s important for an organisation to connect all relevant touchpoints to a unified customer profile in the event of a customer service interaction, or they run the risk of further fracturing the experience and the relationship.
Brands must be willing to look critically at their existing systems to evaluate if they’re truly prepared to handle the significant amounts of data, devices, touchpoints, and the unified view necessary to provide a seamless customer experience. Tools driven by AI and machine learning are the only way to ensure a business can scale to keep pace.
The expectations for customer agents have never been higher; below are ways that AI magnifies data to bolster a support team so they can create optimal customer experiences.
Automate Processes and Tasks
KPMG has estimated that the service cost reduction with Robotic Process Automation (RPA) is as great as 75%. With the average cost of service centres continuing to rise — voice is $12 per contact, and live chat is $5 per contact — shifting resources to self-service through automation and a knowledge base can result in huge savings. Automation tools can decrease costs to just 10¢ per contact.
It isn’t simply the dollars and cents saved, however, that make automation so impactful to an organisation. In one use case, automation can vastly improve worldwide organisations needing to route certain language speakers to agents who can communicate in that language. Additionally, by routing common questions and needs to a self-service portal or base that can both quickly and effectively solve a customer’s problems, agents are freed up to take on the more complex, nuanced issues that customers face.
While sceptics might be concerned about customers valuing human interaction above all else, according to this report from Statista, 88% of US consumers expect an online self-service portal. In fact, bringing numerous types of customer data touchpoints into one place — and from any resource — creates a more seamless, personalised experience for that customer. This method allows for both speed and a personalised approach to be achieved, and on the customer’s terms.
Augment Existing Agent Support
When a customer dials into a service call centre, provides significant information regarding who they are and why they’re calling and is then directed to an agent for further assistance, the worst possible scenario is that customer then having to repeat all of that information…again. When considering a customer may have also reached out through email and even social media, it becomes even more crucial to use data in the right way.
Much like being retargeted by an ad for a product you purchased yesterday, today’s customers are smart and expect organisations to be intelligent with their data. If, after interacting with a chatbot and providing all relevant data, a customer’s issue is escalated to a human agent, the customer expects an agent to already have the necessary context to properly manage the issue. That context should include relevant information like shipping numbers, previous conversations from both online and offline sources, and previous purchases made, combined into a unified customer profile.
Not only does the full customer data view aid with escalating issues directly, but it can also be used to provide recommendations to the agents before even interacting with the customer. Through AI technology, an agent can be given an automated recommendation for how to best handle the customer’s request, eliminating both time and mismanagement; thereby improving the quality, time, and ease of service for both the customer and the agent.
When AI is used to capture data for context, the technology and the human agent become critical partners in providing the right customer experience. It empowers an agent to be a true specialist, who can change the customer’s outcome in a way automation cannot. The marriage between the two is what elevates the customer experience to a level that promotes long-term loyalty.
Proactively Boost Future Outcomes
As a part of the new expectations customers have for service-related interactions, customers expect their preferred brands to be proactive in handling potential issues. For an organisation, this can be as simple as customer communication that informs of impending weather that will impact a shipment, or as sophisticated as predicting the volume needed quarters in advance based on real-time interactions. In order to accomplish this, however, all relevant data must be gathered in a location where it can be acted upon quickly.
One use case could even enable managers to get ahead of issues in the moment. For example, as a call is happening, the voices can be translated into text, then analysed and graded in real time to measure key indicators that identify a call going south. Instead of arbitrarily choosing which calls to QA, or to QA all calls after-the-fact (and risk missing the ones requiring assistance), AI and machine learning can alert a team lead exactly when to jump in and improve the customer interaction as it occurs.
Antiquated technology looks reactively at improvement; the best customer experience requires proactive use of data as the touchpoint interaction occurs, rolling it into the most personalised experience possible.
Customers who have a good experience are three and a half times more likely to repurchase, and five times more likely to recommend to friends and relatives than those customers who have a poor experience. Fifty-nine percent of respondents to the Microsoft State of global customer service report say that customer service expectations are higher than they were last year. In order for an organisation to scale to meet the growing demand, it must provide a seamless omnichannel experience that connects all touchpoints, automates tasks and processes for maximum efficiency, and proactively uses real-time customer data to further create the best experience. Doing so will empower your agents, and build the trust your customers need to remain loyal for years to come.
How Kustomer Can Help You With Data-Driven Personalization
Connecting all the data to relevant touchpoints and driving a hyper-personalised experience will change how your customers experience you and your product.
