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The Key to a Better Customer Experience Is Hiding in Plain Sight

In today’s digital economy, delivering seamless, personalized customer experiences is key to market leadership. But keeping up with mounting and evolving consumer expectations for tailored, frictionless journeys is difficult. It requires an in-depth understanding of consumers’ needs, desires, and behavior – and that, of course, means amassing rich customer data.

Among the most valuable – but often-ignored – sources of customer insights is the data gleaned from customers’ interactions with product content. Product content has long been viewed as part of a checklist of necessities to go live with a product, rather than the business-critical resource more and more enterprises are discovering it to be. In fact, when customers engage with the user manuals, guides, knowledge articles, community discussions and other content enterprises produce, they leave behind a goldmine of data that can illuminate both friction and opportunity in their product experiences. Armed with this information, enterprises can address pain points, build on core strengths, and enable self-service for a better overall customer experience.

With consumers online and working from remote locations more than ever one year into the coronavirus pandemic, eliminating friction points and improving self-service has become imperative. Pandemic-era consumers are increasingly willing to change their behavior and switch their brand loyalties for a better experience, as a recent McKinsey & Company analysis documented.

Read More: 3 Ways to Close Automation Gaps with Field Service Solutions

As enterprises seek to boost customer satisfaction, decrease churn, and equip users with the tools they need for smooth product experiences, data-driven insights from product content offer a path toward achieving these vital metrics while alleviating the burden on customer support teams and generating significant cost savings.

Empowering Self-Service

Enterprises and their strained customer support departments have an obvious interest in making self-service easier, given that support teams tend to experience burnout more acutely than others in an enterprise.

But self-service is also what customers themselves are asking for. Indeed, 81% of consumers will attempt to resolve a problem themselves before taking it to a customer service team. When users are trying out these DIY fixes, they’re usually sifting through product content – yielding a treasure trove of data for enterprises to mine.

This is where data regarding customers’ searches across all product content hubs (apps, chatbots, documentation portals, manuals, and the like) comes in handy. Tracking which terms and subjects are being searched (and with what frequency), the search click-through rate, total searches, and so on helps enterprises understand what aspects of the customer experience are less intuitive and more problematic for users, and how easily users are able to use the product overall.

When it comes to determining how successful their customer experience is, enterprises should consider customers’ self-service success rate an important KPI. This can be ascertained based on the number of visits to a help site or community that did not result in opening a ticket as well as the number of overall visits to the site and how many resulted in a support ticket. As a rule of thumb, enterprises should aim for a success rate of 75%.

Providing a Netflix-Style Experience

For many customers, their vast stores of technical product content double in size every 16 months. In general, there’s no shortage of content for enterprises to track and analyze to fuel the kind of tailored, intuitive experience customers have become accustomed to in using consumer products like Netflix.

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Just as the streaming giant’s subscribers receive personalized recommendations based on their interests and viewing history – often pre-empting the need to extensively browse or search the platform – customers should be able to access a hyper-personalized product content experience that enables a consistently smooth customer interaction.

What would this look like? Customers wouldn’t have to navigate their way through pages of irrelevant enterprise connectivity support questions, for example. Instead, the company would know which problems a customer has troubleshooted in the past and intuitively recommend relevant answers – providing an intuitive experience that radically reduces the need for costly customer support.

Read More: Organizations Have Options for Deploying Data in the Cloud

Easing the Support Strain

How can product content data help ease the strain on customer service teams, eliminate the need for new hires, and drive greater cost savings for the enterprise?

The fewer new cases customers open (case creation rates) and the higher the rate of queries customers open but then abandon (deflection rates) – usually because they have solved the problem on their own – the better an enterprise is generally performing in terms of self-service. Comparing these metrics across different products and offerings can help organizations identify gaps and opportunities in the customer-product experience.

Consider the case of a cybersecurity company seeing case creation rates of 10% related to its data privacy software but of 70% about its malware detection software. This provides a clear indication that the support documentation for their malware detection software either needs to be improved or made more accessible to users, and that the customer experience around the malware software is severely lacking.

Reducing Customer Churn

Keeping customers satisfied and preventing churn is essential at any time, but is particularly crucial in a pandemic-fueled climate where customers are forced to operate more independently, loyalties are being upended and patience for subpar experiences is thinner than ever.

Tracking customers’ content satisfaction scores via feedback mechanisms can be an insightful way for enterprises to gauge how well their content enables customers to troubleshoot problems and to optimize accordingly. For instance, if an internet service provider sees that technical content for its fiber network coverage plan has a high satisfaction score, while its broadband/DSL plan has a lower content satisfaction score, then the enterprise knows where to focus its content optimization efforts to keep customers on board, thereby improving the broadband/DSL experience for its already hard-won customers.

Average customer effort scores provide another good measure of how smooth a customer’s encounter with a product content is. This indicator shows how easily customers were able to resolve their issue (based on data gleaned from pop-up feedback prompts). If customers struggle to resolve their issue, this frustration will likely brew and edge them closer to churn and enterprises should refine their content to make the product experience more user-friendly.

Customers have made it clear: They crave quality, customized experiences, and they prefer to resolve any issues on their own. By tapping into the power of their product content data, enterprises can meet today’s consumers where they are, streamline support operations, and generate genuinely improved customer experiences that drive results for the customer and the business alike.

Read More: 5 Ways in Which AI is Revolutionizing Finance & Insurance

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