Source CX Industries IT Support and Helpdesk Got To Track Them All: Going Beyond KPIs To Uncover Meaningful Insights

Got To Track Them All: Going Beyond KPIs To Uncover Meaningful Insights

Since the 1990s, the management of IT and helpdesk departments has relied heavily on KPIs. Quantitative metrics such as call resolution times, user satisfaction scores, and number of tickets closed have traditionally been the primary methods used to benchmark performance — often to the exclusion of more qualitative indicators.

While many companies recognized that this approach often overlooked the nuances of stakeholder interactions and the rich insights they could offer, conducting deeper qualitative analysis was traditionally a resource-intensive and costly prospect. However, in recent years, the rise of affordable AI analysis tools has created new opportunities to go beyond KPIs and develop a more holistic understanding of user preferences and behaviors.

In this 5-minute read, we’ll explore:

  • The importance of shifting from quantitative to qualitative metrics
  • Skills challenges involved in successfully implementing AI tools
  • The practical applications of AI technology in IT/helpdesk operations
  • How to balance automation and human involvement in support
  • Outsourcing as a viable option to personalize support at scale

Evolving from quantitative to qualitative metrics

Now, businesses can draw on a wider range of user-centric metrics to better understand how well their helpdesk or IT functions are serving stakeholders — either internal or external — rather than focusing solely on how the team is performing.

AI sentiment analysis offers deeper insights into how users genuinely feel about the service they receive. This technique allows companies to track subtle shifts in sentiment over time, providing a proactive means to address issues before they escalate. Automated triage systems allow businesses to categorize, prioritize, and route service requests in real-time based on their urgency and complexity — ensuring that critical issues are addressed promptly. And by analyzing past interaction data, predictive models can forecast future stakeholder needs and behaviors. This forward-looking approach enables companies to anticipate and solve potential problems before they arise, thereby enhancing the overall user experience.

These AI-enabled techniques mean that for the first time, companies can track progress against their ultimate goal — stakeholder satisfaction — rather than broader indicators such as response or resolution time. By focusing on these qualitative aspects, businesses can cultivate deeper, more meaningful relationships with their service users, which, in turn, can lead to improved efficiencies and long-term business success.

AI and data analytics – the game changers

The arrival of AI and data analytics tools in helpdesk and IT support functions — from chatbots to predictive analytics and sentiment analysis — is reshaping how stakeholder interactions are managed and understood.

However, integrating these sophisticated tools isn’t without its challenges. According to a recent article by McKinsey, “With cost pressures rising at least as quickly as service expectations, the obvious response—adding more well-trained employees to deliver great service—isn’t a viable option.” Instead, companies should prioritize the introduction of new skills and roles within existing IT and helpdesk teams — there is a growing need for specialists who can manage AI systems, interpret their outputs, and act on the insights they provide.

Managed correctly, this re-evaluation of the role of human agents in IT and helpdesk operations — and the introduction of specialized technology to support their work — can have a significant impact. The same article gives the example of a bank in Asia that, having introduced AI-powered decision-making, automated intent recognition and resolution, and enhanced monitoring against stakeholder engagement targets and SLAs, achieved substantial service improvements within the first 12 months alone.

The report reveals the extent of these improvements, stating, “The transformation resulted in a doubling to tripling of self-service channel use, a 40 to 50 percent reduction in service interactions, and a more than 20 percent reduction in cost-to-serve. Incidence ratios on assisted channels fell by 20-30 percent, improving both the customer and employee experience.”

Practical applications in IT and helpdesk settings

The adoption of AI and data analytics applications in IT and helpdesk functions offers many practical benefits. For instance, AI-driven tools are being used to enhance ticketing systems, where they analyze incoming requests and automatically route them to the appropriate department, suggest potential solutions, or in some cases resolve the ticket automatically without the need for human input. As well as delivering faster resolution times, this also frees up human agents to handle more complex queries.

AI can be leveraged to provide more personalized support. By analyzing past interactions and user profiles, AI systems can adapt responses and solutions to individual needs, offering a more nuanced and tailored support experience. This increases the quality of interactions, increasing stakeholder satisfaction and reducing the number of touchpoints needed to resolve an issue.

The use of AI-enabled chatbots can also improve access to self-service support, acting as a conversational interface and asking pertinent questions to help service users find the resources they need to solve a specific problem. As a result, demand on real-time channels such as email, phone, or messaging can be reduced, lowering support overheads.

In all of these cases, the advantage that AI brings to the table is the ability to streamline and automate processes while improving the user experience. In the past, the introduction of new technologies — such as replacing human call handlers with automated voice menus — has been associated with a dip in user satisfaction. In contrast, the addition of AI to key areas of the support journey makes interactions easier, smoother, and more user-centric.

Going deeper: beyond surface-level data

Modern AI and data analytics solutions enable IT and helpdesk teams to move beyond surface-level metrics and unearth actionable insights. This deeper analysis involves parsing vast amounts of data — from stakeholder service interactions to feedback on social media platforms — to uncover trends and patterns that can inform more effective service strategies. By integrating AI tools with existing service platforms, companies can utilize predictive analysis to not only react to current issues but also anticipate future challenges.

For example, as highlighted in a recent HubSpot article, AI tools are increasingly adept at predicting user behavior based on historical data, such as when they are likely to purchase a product, what features they will be most interested in, or which aspects they are most likely to need support with. This preemptive data collection can significantly reduce average handling times and streamline the service process. By blending AI’s predictive capabilities with human agents’ expertise, IT and helpdesk teams can offer a more personalized and efficient stakeholder experience, proactively addressing issues before they escalate.

Balancing technical efficiency and human empathy

While AI offers unparalleled efficiency and deep analytical capabilities, it’s the human agents who bring empathy and understanding to stakeholder interactions. The challenge lies in striking the right balance between technological efficiency and human intuition. AI-derived insights can guide human agents, but can’t replace the personal touch that is often crucial in complex or sensitive service scenarios.

For instance, an AI system might be able to identify that a user is frustrated with a service through sentiment analysis, but it’s the human agent who can empathize, provide reassurance, and offer tailored solutions.

Companies are increasingly recognizing the value of this synergy — as a recent article by HBR points out, “Despite the media narrative to the contrary, generative AI will not wipe out entire categories of jobs, such as those in customer service. Automation is ideally about unlocking human potential to do tasks differently and do different, higher-value tasks.”

The challenge is to train IT and helpdesk teams to use AI-generated insights as a tool to enhance their interactions, not as a replacement for human judgment.

The ultimate aim is a balanced approach, where AI does the groundwork by analyzing data and identifying trends, while human agents use these insights to deliver more informed and personalized service. This synergy not only enhances stakeholder satisfaction but also empowers agents, making their roles more strategic and impactful — a welcome change in a profession that experiences up to 45% annual employee turnover, according to Forbes.

On-demand, integrated helpdesk solutions

The rise of AI and data analytics also improves the business case for outsourcing IT and helpdesk functions to specialist external teams. In the past outsourcing these support functions meant that businesses had to make a trade-off — improving service availability and cost-effectiveness, but at the expense of providing a personalized service. Now AI can bridge that gap effectively.

As a result, from a user perspective, there’s effectively no difference between dealing without outsourced teams or in-house employees — all have access to the same real-time user data, records of previous conversations, and AI-generated insights and predictions on stakeholder needs and preferences.

This gives companies more options to scale their IT and helpdesk support according to demand, manage costs effectively, and benefit from the specialized knowledge of external experts — without a drop in service quality or brand perception.

Conclusion

The intersection of AI and data analytics with stakeholder service is transforming the landscape of IT and helpdesk provision — for both internal and external audiences. By looking beyond traditional KPIs and harnessing the power of AI, businesses can uncover profound insights into user behavior and preferences.

Strategic partnerships with domain experts like SourceCX can help to facilitate this transition, both in terms of identifying and implementing the right technologies for a specific use case and providing on-demand access to the expert outsourced talent needed to leverage those technologies successfully.

The future of exceptional IT and helpdesk support is not just centered on the introduction of ever more powerful AI tools — it requires companies to build new synergies between innovative technology and human expertise, to better understand their service users and create opportunities for more personalized, efficient, and proactive service.