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When a viral tweet can diminish a brand's reputation, and a pattern of negative reviews can shutter a business, the importance of the customer experience cannot be overstated. Drawing on customer support analytics can help organizations obtain crucial insights into their customers' expectations, gauge whether those expectations are being met, and drive customer experience improvements across the organization.

The impact of support on the customer experience

According to research by PwC, 73% of customers base purchasing decisions on the quality of the customer experience. Support agents regularly engage with customers on the verge of dissatisfaction, which places them in a unique position to impact the overall relationship between the organization and its customers. It is the agent's job to show empathy, demonstrate a clear understanding of the problem, and provide an effective solution. All of this is more easily achieved when agents have access to accurate and meaningful data.

Many customers grow frustrated when they have to repeat their problem to multiple agents in search of resolution. Contextual analytics empower an agent to enter the conversation with a foundational understanding of the issues, and knowledge of the resolutions that have already been attempted. This ensures they're moving the customer toward potential solutions, rather than dragging them back to square one.

With customer satisfaction (and loyalty) on the line, efficiency is vital at every stage of the support process. Metrics like first response time and average time to resolution provide managers with essential insights into the performance of their teams and processes. Informed by this data, they can ensure support team resources are properly allocated so no customer request slips through the cracks. This is particularly important in the age of social media. Research shows churn rates are 15% higher for companies that consistently fail to respond to social media support requests.  

Support analytics and self service

That said, the power of customer support analytics goes beyond informing live customer interactions. In some cases, analytics can help customers circumvent live interaction altogether. According to the Harvard Business Review, 81% of customers will try to resolve their issues through self-service platforms before contacting a live representative. For companies that provide effective self-service resources, that's a preference that should be welcomed rather than feared.

Using qualitative data such as support ticket keywords and common help topics, organizations can build extensive knowledge bases populated with relevant help documents. Drawing upon common requests, questions, and concerns, they can create targeted solutions for customers to access at their convenience, without ever having to wait on hold. Many organizations have already incorporated self-service platforms into their customer support strategy, leading to a 5-10% increase in customer satisfaction scores, alongside a 15-20% reduction in operational costs.

Opportunities for proactive solutions

Given the impact of support on customer retention, it's understandable that many organizations see customer support analytics as a protective measure. But failing to recognize the proactive opportunities afforded by the data would be a wasted opportunity. Armed with details about customer pain points, questions, and preferred modes of communication, an organization can fortify its efforts across departments to provide personalized and highly effective customer experiences.

In particular, research and development teams stand to benefit from insights into the challenges customers face. With access to support analytics, these teams can refine their strategies to ensure future product releases and upgrades incorporate the most in-demand features, integrations, and customizations. By anticipating the needs of the customer, truly motivated R&D teams may eventually be able to offer products and services that preempt the need for a customer support call in the first place.

When applied to sales efforts, the proactive approach can have an even more direct impact on revenue. Support analytics can be used to alert sales teams when a customer is seeking services beyond the scope of their current offering, or when they've simply outgrown their current version of a product. This information leads to more up-sell and cross-sell opportunities. Further, when salespeople are kept in the loop about specific customer requests and challenges, they become more adept at offering solutions before problems even arise. It's a lucrative tactic; preemptive sales can increase an organization's revenue by 30%.

Fostering customer relationships

It is an established fact that a happy customer is more likely to become a repeat customer. When a brand regularly provides top-tier customer service, optimized by relevant data, it creates an environment where customers are more amenable to sales efforts and product offerings. To foster this environment, organizations should aim to promote a customer service mindset beyond the support department. Aided by support analytics, an organization can ensure every interaction, product release, and marketing campaign addresses the needs of the customer, earning good will and loyalty in the process.

Sales teams that recognize the value of building relationships are already embracing the customer service mindset. In the era of CX, rushed and generic sales tactics no longer provide a path to success. Instead, sales teams need to tailor their approach to each relationship and demonstrate an accurate understanding of the challenges customers face. Support analytics allow them to accomplish this task in a way that is authentic, and ultimately more effective.

When an organization proactively manages its customer experience over time, its brand image often thrives as a result. High levels of satisfaction lead to brand advocacy on social media and positive online reviews. And today, that's important. A recent study found 79% of consumers trust online reviews as much as personal recommendations from friends and relatives.

By now, an excellent customer experience is no longer a perk of doing business with an organization; it's a prerequisite. Analyzing customer support data is an essential first step to building a base of happy and loyal customers. But to realize the full value of the data, it's important to apply it beyond the support team. When the data is accessible across departments, customer support analytics can play a key role in organization-wide growth.

Zoho offers a suite of intelligent enterprise business software, including an award-winning CRM suite, the industry's only comprehensive analytics and BI platform, and a powerful low-code development ecosystem.