Make Support a Competitive Advantage

Happy young woman working on laptop while talking to customer on phone. Consulting corporate client in conversation with customer using computer. Service desk consultant talking in a call center.

How many times while using a web application have you run into an issue and been taken to another website? Where you’re prompted to scramble through a database of support content. And then a chatbot pops up to asking you to describe your problem all over again. Finally, you get through to a live agent and you’re asked, “what issue are you facing?” Sound familiar? The human instinct is to close your laptop and walk away. This scenario grew x10 as remote work became a reality across all verticals in the last twelve months.

Data Silos and Legacy

Companies have made investments in tools and technologies to help them understand their customer events more deeply.  Their hope is to gain the advantages of a superior customer experience. Yet, customer support departments still struggle to get the complete picture of customer issues and behaviors at every interaction. Too little to empower their service agents with all the insights when and where they need them. Often, they have to react, taking notes and capturing information, instead of proactively helping customers in a time of need. 

Resolving or staying ahead of customer issues is all about having a real-time correlated engine in the backend, which is learning from user journey clicks, from errors within logs, to past interactions. It’s about finding the hidden nuggets across data sources and contextualizing them to be proactive and preventative. 

In the Digital World Why is Support Lagging Behind?

All the data exists within the tools and technologies that companies have invested in. It is just spread across support tiers, engineering, and DevOps. And frequently it is lost during collaboration. Your service agents are the public face of the company, especially in the digital world.  They are first point of contact for anything gone wrong. And they have a huge impact on the success of your business. Your service agents need to be empowered with real-time insights. 

According to Microsoft, 58% of consumers believe customer service affects their choice of brand, and 61% have gone elsewhere because of poor service. Salesforce research shows 84% of consumers believe the experience a company delivers is as important as the products or services it offers. Now, the customer support experience is even more important for ongoing trust and loyalty.

According to a 2021 IDC report, by 2023 more than 500 million digital applications and services will be developed and deployed — an explosion of apps in just two years that equals the number developed over the previous 40. Yet even with digital at the forefront of innovation, businesses lack the ability to connect product signals to customer issues. Not being able to do so has a huge impact on revenue and lifetime value. 

The Future is About Embracing Data and AI in the Support Process

Customer support is no longer about reacting to customer complaints. And then passing them on to technical teams while hoping for the best. It’s about making decisions and providing advice via data-driven insights, to provide the ultimate experience to the customer. Today support organizations looking to beef up their support operations by boosting their data and analytics capabilities.  And they want to harness predictive insights to connect more closely with their customers. This means anticipating behaviors and identifying customer issues before they face them in real time. 

In the new digital landscape, agents need to be able to take ownership of the end-to-end resolution process and empathize with the customer. This starts by providing them with contextual information from the integrated tool stack.  Details on product features- how the customer is interacting with them. Status on operations- can irregularities be correlated to the customer issue.  And all of this stitched together to recreate customer journey of events with insights and recommendations to resolve their issue. 

There is no need to rip and replace the tools you use today.  Instead look to see how data and insights can be brought into the tools and processes you use today. Visibility of success metrics is also important to track performance over time. Finally, ensure customer service and engineering teams are working in sync to drive productivity and product innovation.

Where to Start?

You can start by integrating your tool stack to support real-time data sharing and ensuring it has open APIs so agents can access their preferred enterprise tools for full organization-wide context on issues. Next, ensure customer service and engineering teams are working in sync with the same data to drive cost efficiencies. And you should look to improve your product out of the data-based feedback the support process can provide. These small steps can have a huge impact and drive competitive advantage in a rapidly changing business environment.

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