I’ve been telling several friends and colleagues lately how I really feel like right now feels like one of the most exciting times to be in customer support, with so many foundational and technical changes afoot opening up new and limitless opportunities to evolve the space. Thought leaders like Gartner, TSIA and others are giving context to this, with recent research and reports regarding the rapid evolution of data and analytics capabilities shaping entirely new capabilities within service and support operations. And business leaders, seeing this, are increasingly looking at ways to move beyond traditional missions of these functions to redefine the strategies, processes and technologies that will open new opportunities for customer experience, retention, and revenue outcomes.
What does this all really mean?
Support is evolving beyond a reactive and transactional service- it can engage and add key value across the customer and product lifecycle. One example used is HotDocs, an online medical services company that helps patients connect with medical providers. They’ve been answering customer calls with good satisfaction rates, but lacked any unified view of customer data, and information was silo’d across tools and teams. They began to see this as a big missed opportunity, and undertook a plan to move to a connected platform where sales, support and product teams could collaborate with a 360-degree view of their customers, availing new and deeper insights across each of the teams could leverage this shared info.
Imagine the scenario where a new product feature is sold into a customer; support sees this and autogenerates a ‘tips and tricks’ communication with common feature information customers call about, when the customer opens the online support site, how-to articles for that feature are surfaced at the top of the page , and if the customer contacts support, an agent can open the interaction with “I see you just added this new feature, how’s that going?” – all while product and support teams have a dashboard with real-time support data on top issues by feature that includes this customer call as soon as it happens, where they can click through to see the details of what happened.
Pretty powerful, right?
What’s driving these new capabilities?
Collecting broader sets of customer and service data and integrating them effectively with normalization and shared governance has traditionally been really hard and expensive, where it was even possible. Hundreds of fields from different tools across several teams meant huge, expensive and resource intensive data stores (eg, locally operated IT infrastructure, DB architects and DBA’s, to start). So, it was easier to let support, sales and other teams each use tools that did what they needed and produce only the data relevant to each of them. Even with cloud-based common tools of the not too distant past, functional datasets were difficult to access and use outside each of their own silo’d structures.
What’s changed is that with flexible, virtual and universally scalable data storage and management solutions like AWS, Azure and others, the high cost and management limitations of integrating data pools have evaporated. So, combining disparate data sets into large, shared data lakes and doing cool things with it is vastly easier, enabling things like a shared lens of customers and their activity across any team. Together with more powerful analytics and data AI capabilities, this has become a powerful tool that can be broadly and readily used.
Using the emerging capabilities to create tangible value
Customer datasets and analytics like these unlock vastly deeper understanding of customers and any related activities to drive really impactful outcomes around customer experience. Things like:
- Improved customer retention using predictive analytics with past trends to operate proactively. If the satisfaction, sentiment and usage data show that a customer is at risk of leaving, customer service teams can see and respond proactively. At Athenahealth, we instrumented regulatory quality measures to flag issues with customer reporting data, and reached out to them to correct it well ahead of when it would have appeared within regular submission periods and been a risk to reporting deadlines.
- Reduced operating costs by leveraging support and service data to drive end to end customer journey and operational improvements, such as automations, channel strategy, ticket deflection strategy, and integrated service and marketing strategies.
- Increased revenue through conversion of better customer relationships, lower churn and higher NPS into Lifetime Value (LTV) outcomes.
The particular opportunity with support
Support is generally the highest volume of interactions that customers have (by far) with a product post-purchase. Combined with these new shared views and capabilities, every support contact across every channel or platform becomes a powerful opportunity to reinforce your product value proposition, customer experience and product/brand relationship in how, how well and how proactively they are fielded, handled and addressed. And, the rich data that support is able to produce can drive enormous value into customer and product analytics, enabling powerful feedback loops for things like product enhancements, user painpoints, feature workflow and product use case issues.
So, the opportunity to redefine the strategy, processes and technology of support, and pivot from a post-sale cost driver into a robust business and customer value generating engine has never been bigger. And that’s why right now feels like one of the most exciting times to be in customer support.