In the world of customer support, where quick response is the key to successful customer support, a complete shift from reactive to proactive is underway. Now, imagine a world where helpdesk software doesn’t just address issues as they arise but also takes anticipatory and pre-emptive actions and resolves them before they impact users.
Do you know what we call it? We call it a proactive mindset. Yes! Getting prepared way before the problem arises and mending the issues before they reach the end users.
Users depend heavily on the proactive service. As per Microsoft, 68% of the users favour brands that provide proactive user customer service notifications.
In this blog we will unleash why go from a reactive to a proactive approach, what is generative AI, its influence, how generative AI is beneficial for helpdesk software, how to use it and in the end the challenges of implementing generative AI in helpdesk software.
What Is Proactive IT Support
In simple words, proactive IT support means being prepared with the necessary resources and tools to alleviate the effect of downtime beforehand.
Proactive IT support refers to a strategic approach in which a service desk or helpdesk software utilises advanced technology, such as AI algorithms, to help predict some future occurrences, prepare for the remedy and, quickly lessen its effect to minimize the impact on the end user.
Implementing this proactive approach helps build robust IT support and prevent future incidents from occurring.
An issue that arises time and again with a traditional approach, the same issue cannot reoccur in a proactive setting, through continuous monitoring, providing real-time diagnosis and maintenance recommendations the systems aim to prevent the issue from becoming recurring issues.
Reactive vs Proactive IT Support
Proactive IT support is leading the reactive approach in numerous aspects. A proactive approach of course has super capabilities to mitigate the negative impacts on the users and improve the overall business.
Let’s dive into the difference between reactive and proactive IT support
| Reactive IT Support | Proactive IT Support |
| It provides solutions only when a problem arises | It utilises a predictive approach to sense threats and mitigate problems before they arise. |
| Provides quick assistance after the problem occurs | Identify the problem at the grass root level to prevent future occurrences |
| Problems occur frequently and repetitively | Provide long-term solution to the problems |
| Productivity drains after some time due to employee disengagement | Provides enhanced user experience and efficiency because of active employee engagement |
| Prolonged downtime, wastage of productive hours and increased operational costs | An efficient approach that provides preparedness in advance that avoids costly repairs and downtimes |
Generative AI
By now we all know that traditional helpdesk software is reactive. On the other hand, an AI-backed help desk already provides timely signals for upcoming IT incidents, and when it works with thousands of millions of real-world IT incident parameters assisted by large language models or generative AI, its efficiency becomes manifold better and it becomes high performant.
According to Salesforce “More than two out of three (68%) say generative AI will help them better serve their customers”.
What is Generative AI
Generative AI is a type of Artificial Intelligence that can mimic and create new, original content built on the models it’s trained on.
Before AI could be useful in the organization that generates vast amounts of data and resources, where the data scientist would analyse those large sets of data.
it’s a tool not limited to those organizations but can be practically used by anyone. For example, It can help students in their homework, and graphic designers to create their tasks in a matter of seconds which would earlier take them days to weeks to create. Employees can summarise their worksheets of data and create a report to send to their management teams.
In addition to delivering AI-powered proactive support, Generative AI also automates other tasks such as incident detection and reduces extra burden in analytics and manual threat mitigation.
Application of generative AI in helpdesk software
The integration of generative AI has helped helpdesk software by enhancing self-service options to personalise customer interaction. Helping agents to scale their tasks and providing sentimental analysis to create outreach strategies that can result in stronger agent-customer relationships.
Tailored Customer Interactions
Generative AI analyses customer inquiries and provides a tailored solution based on their needs. This approach improves the customer experience, making the interaction more human-like and less like standardized procedures. Businesses are already using this approach to create better and more efficient customer interaction.
Bridging Language Gaps
Companies with global presence have language constraints and that becomes the biggest roadblock for their business. Generative AI provides solutions to everything by providing real-time translation and creating responses in multiple languages. This feature allows companies to interact and do business with each other and also interact with customers from any part of the world.
Advancing Self-Service Options
Self-service portals and FAQs have become popular and handy as customers seek quick solutions to their problems. Generative AI has taken self-service to another level by creating comprehensive and useful self-help guides. This not only helps reduce the burden of the agents but also empowers the customer to find the solution to their problems on their own.
24×7 support with chatbots
To take care of the demands of the global clientele, the business must provide round-the-clock support. Generative AI takes care of it, offering personalised responses to the user whether they are sitting in the USA or India. This level of responsiveness enhances brand trust, a key factor every customer is looking for.
Quick access to knowledge-based articles
Time is of great importance and every moment counts when your customers want immediate and relevant information. Generative AI plays a crucial role in curating customized content and suggesting content to users at the time of the need, that is instantly, whether that’s troubleshooting manuals or FAQs. So, it makes sure that the users get customised solutions to their problems.
Customer Sentiment Assessment
Customer sentiment analysis is about understanding the customers beyond the statements. That is delving deep into their emotional state. The collaboration between generative AI and humans makes it possible to perform sentimental analysis to create outreach strategies. Ultimately it leads to the creation of stronger relationships and the ability to make needed and timely adjustments based on valuable emotional feedback.
Automated ticket routing and categorization
A strategically routed ticket can tell the difference between a satisfied customer and missed opportunities. Generative AI’s work is to ensure that all the problems reach the right department and a specialist who has the right set of skills to solve the issues. It results in a quick resolution and happy customers as well.
Efficient agent task assignment
Every agent possesses a different skill set. Generative AI sees it before allocating tasks based on the skillset and speciality of the agent. This makes sure that the assigned tasks align with the skills of the agent which ultimately results in high-quality support, which further improves the brand name.
Use cases of generative AI for Helpdesk Software
The most effective utilization of Generative AI is its ability to automate repetitive tasks, gathering information from a knowledge base and streamlining post-call processing. Below are the use cases of generative AI. Let’s dive deeper into each of the use cases.
Smart email sorting and routing with Generative AI
Support teams often utilise shared inboxes to handle customer conversations, this allows them to reassign tickets based on the expertise or who attended the customer previously. Generative AI takes this process one step further by automatically routing and sorting the tickets for agents based on
- Who interacted with the customer previously
- Queue length
- Based on customer rating
- Based on customer sentiments for example assigning irritated customers to agents who can calm them
This helps boost the overall efficiency of support-related operations, gives quick resolutions and helps businesses manage support teams more effectively
Anticipatory customer support
What can make a customer happy? Well, personalised advice and follow-ups regarding the product or configurations they have just bought. Yes! A big yes for it. This approach will empower your customers as they can avoid common mistakes and they can understand how the product works without contacting the support team. Through this approach, you can educate your customers and also provide them with proactive support by providing the solution before it arises.
Instantly retrieve info from your knowledge base
You know what you won’t have to train bots to supply up-to-date information to your customers. Because your bots can pull data from your knowledge base as your data source. It can extract relevant information from your FAQs, catalogue etc. This will save configuration time for the bots. And you can pick up the existing information into your data source to build a bot that functions immediately.
Streamline repetitive tasks
Repeat tasks such as password reset, onboarding and offboarding, account unlock can be frustrating and mundane.
With agents and HR becoming busy with more important and strategic work, remote employees can become frustrated if they come across these issues time and again.
Generative AI can become a helping hand by automating all these repetitive tasks and providing quick and straightforward solutions to users in real time.
Automating Note Taking
Taking note of what the customer is saying is one of the important aspects of call handling. However, indulging in note-making can impede their ability to achieve listening which is again an important part of call handling.
Call note automation addresses this challenge by automatically taking note of the key details. It helps agents actively take part in listening and unburdens them to manually record everything.
Agents can easily refer to these notes rather than going through the vast and lengthy transcript.
Streamline Post Call processing
When an agent ends a call with a customer, they have to go through a post-calling process after that. It generally involves creating a contact summary and uploading a call summary and deposit code to CRM.
Generative AI can automate the entire process and this makes it super easy for agents to get a hold of what happened in the previous calls.
Challenges in implementing generative AI in helpdesk software
Generative AI has changed the world. And it’s here to stay. It has benefitted us in several ways but there are some downsides too. Let’s look at some challenges it presents in the content below.
Managing Ambiguity and variability in customer queries
Customer queries can vary in terms of structure and intent. Attaining precision in understanding customer intent becomes challenging for generative AI.
Bias and inclusivity
AI tools can become biased owing to the biases present in the training data that can result in partial responses during the customer conversation. It needs constant monitoring to make sure that the generative AI produces an unbiased response.
Scalability
Scalability remains a challenge for generative AI. It can handle customer service on a smaller scale. As the volume of customers increases it can’t scale its capability up to that level and the accuracy remains a challenge.
Addressing out-of-domain queries
Again, generative AI is tailored to handle particular domains and tasks in particular situations. Generative AI may struggle when out-of-domain queries are asked.
Transparency and Explainability
According to HubSpot “55% think Generative AI tools like ChatGPT sometimes offer incorrect information, while only 42% think they’d be able to tell if the information they get from tools like ChatGPT is wrong” There is a lack of transparency in some of the generative AI tools. Which becomes a hurdle as they are incapable of adapting to some customer service situations. Customers sometimes find it difficult to trust AI-generated responses
Conclusion
Generative AI is a powerful tool which has the potential to transform customer service and streamline the work of customer agents. However, it is at the beginning stage and there are challenges involved around its implementation and accuracy.
We can’t say it is the one-size-fits-all-all-support solution at this stage. But again, we can’t also deny the benefits it presents in customer service.
As this technology grows, companies should leverage generative AI to build a stronger market presence and stay ahead of their competitors.
