How do you identify automation opportunities with product support metrics?

When working with third-party or SaaS products, one interesting metric I always look for is % cases referred to vendor. A high number of cases needing vendor engagement indicates we either have a buggy product or, more likely, a training opportunity for the support team.

Ignite innovation by leveraging product support metrics to uncover automation opportunities. Foster a data-driven mindset, diving deep into metrics to identify repetitive tasks and inefficiencies. Embrace creativity and collaboration, brainstorming with team members to envision automated solutions. Embody a spirit of experimentation, piloting new automation initiatives and iterating based on feedback. By embracing the power of automation, you transform challenges into opportunities for efficiency and growth, paving the way for a brighter future where every task is streamlined and every effort is magnified.

Identify automation opportunities in product support, gather relevant metrics and analyze support processes. Identify repetitive tasks, time-consuming processes, error-prone activities, and customer pain points. Prioritize automation opportunities based on frequency, impact on customer experience, complexity, and feasibility. Research automation technologies like chatbots, AI-driven ticket routing, and NLP solutions. Develop prototypes for automated solutions and test them in a controlled environment. Continuously monitor and iterate on automation implementations to address any shortcomings or emerging opportunities. This structured approach can optimize support operations, improve customer satisfaction, and drive operational efficiencies.

Identify repetitive tasks in customer support metrics. Prioritize high-volume and time-consuming activities. Collaborate with IT to assess technical feasibility. Start small, automate gradually based on effectiveness.

If you are not taking care of your employees, how do you expect they will take care of any customer? People are not numbers, it's not all about KPIs. That's leading to a quantity over quality situation.

By examining a set of KPI sets in the support domain you can always learn something about process flow issues, and start with re-evaluation of the actual process, KPI alone can't give you enough details to identify automation opportunities. After which you can evaluate workflows for each processes, and even if you find decent opportunity, there is a question if it needs to be automated, in order to have good product support human touch is essential. An example I have seen in the past is trying to over-complicate by introducing automation. This and many contributions are full of chat responses. And in need of a clear audit. :) Same story here.

Automation is very key to improving customers' support experience. One of the ways I do explore this is by using automation to manage customers expectation by creating different templates to set the right expectations. This templates are basically used to automate email communication for Initial Response, Follow ups, case escalation, and case closure. With these templates, I could manage customers expectation properly while meeting other support metrics like Initial response time, Case health, and this also helps to improve the customers experience and satisfaction rate.

Resolution time with known article link rate would suggest high opportunity for automation. Clearly customers are calling for help with known issue. Why? Can’t they locate article themselves? They lack skills to implement it or they don’t understand it? Another example would be to look at proportion of cases closed with articles vs cases closed with no article attached. Are we not documenting solutions which could be re-used? Do we struggle with mapping customer’s issues with known issues? Basically, such comparison can be used to dig deeper and understanding whether we need to change behaviors of our staff, or whether we deal with abnormal volume of unique issues which we can’t even diagnose properly?

To automate customer support, it is important to first understand why customers are reaching out for assistance. Create a list of all the issues that customers commonly face and possible solutions for each one. Issues that can be resolved by providing info or a ref to an existing policy should be the first ones to automate. Repetitive customer issues should also be automated since they take up a lot of time for support rep. Reopen rate of ticket signify negative NPS, understand the issue of the customer before getting to resolution. Create a knowledge base of FAQs for all the common issues and integrate these into your ticketing system so that they are displayed to customers before they raise a ticket.

Las métricas se tienen que contextualizar para obtener un indicador significativo y actuar en consecuencia. Hay al menos 3 lapsos para poder tomar decisiones: 1) Definir las métricas y comenzar a recolectarlas, 2) Recolectarlas suficiente para generar estadísticas, inferir relaciones, identificar patrones y lograr un dimensionamiento y finalmente 3) Utilizarlas para crear indicadores útiles para la gestión y la mejora. Las personas se sienten bien cuando resuelven su problema las áreas de soporte o cuando los escuchan, turnan sus casos y les dan seguimiento. La decisión de usar métricas y KPI, implica un compromiso a definir procesos, capacitar al personal, apego al proceso, medición para poder realizar una mejora continua.

There is also a KPI created when a customer bypasses the entire chatbot list and all automation solutions to get directly in contact with the support service team: the ratio of problems resolved by the chatbot to the number of clients opting to skip to the support team is an important KPI to measure the efficiency of our automation solutions.

By implementing automation, customers can be handled quickly and accurately, ensuring they receive the information they need. The impact of automation should be reflected in positive growth in customer NPS, reduction in churn rate, and an increase in referrals from satisfied customers. This, in turn, can lead to positive reviews on platforms such as Google and Trustpilot. Additionally, a decrease in the number of calls and tickets received can result in cost savings for the support function.

To evaluate automation impact, compare support metrics before and after automation. Measure time and cost savings, customer satisfaction, and team productivity. Automation can enhance product quality and usability by streamlining feedback collection and bug reporting. Monitor automated tools like chatbots and self-service portals, optimize workflows, and maintain a balance between human support and automation for seamless integration.

Begin by measuring and comparing support metrics and KPIs before and after implementation. Assess time and cost savings from automating repetitive tasks and solutions. Gauge improvements in customer satisfaction and loyalty. Monitor team productivity and morale enhancements as automation frees up time for more engaging tasks. Evaluate how automation contributes to product quality and usability through streamlined feedback collection and bug reporting processes. Continuously track the performance and feedback of automated tools. Optimize automation workflows based on ongoing analysis, ensuring seamless integration with human elements. By leveraging product support metrics and KPIs, you can refine automation processes over time.

To measure how automation affects product support, start by measuring things before using automation. Look at efficiency measures like how long it takes to finish a task and how many support tickets come in to understand the impact on workload. Check if customer satisfaction scores go up to make sure the improvements match better customer experiences. Also, see if automation is saving money by looking at changes in support costs. Include feedback from customers for both numbers and insights. Keep checking regularly and adjust based on the results to make sure support keeps getting better.

With Generative AI, the support function will soon be redundant. Just make a good knowledge base and connect your system and AI will take care of ticketing and calls where the information is available on realtime. We are working on similar lines where our tools will not only identify the dept of issue but will also help get close the ticket by following up internally as well as externally. Future is AI.

One metric is the amount of manual effort required to complete a task. If a task requires a lot of manual effort, it may be a good candidate for automation. Another metric is the frequency of the task. If a task is performed frequently, it may also be a good candidate for automation. Finally, the complexity of the task is also important. If a task is complex, it may require more manual effort and be more difficult to automate. However, even complex tasks can be automated with the right tools and processes.

?Recuerda que la automatización no solo se trata de mejorar los números, sino también de liberar tiempo para que tu equipo se enfoque en tareas de mayor valor agregado y brinde un servicio aún más personalizado a los clientes! ?? La combinación de tecnología y habilidades humanas es la clave para un soporte de productos excepcional. ?Sigue adelante y sigue innovando! ?? #Innovación #Automatización #SoporteAlCliente

As métricas de suporte ao produto revelam oportunidades de automa??o. Analise volume de tickets, tempo de resolu??o, tipos de problemas e canais mais usados. Utilize chatbots, base de conhecimento e softwares para automatizar tarefas repetitivas e otimizar a experiência do cliente. Monitore o tempo de resposta, volume de tickets e satisfa??o do cliente para avaliar o sucesso da automa??o.

AI is not the be-all and end-all of IT support and should never be considered anything other than a tool for sorting data. AI's strengths lie in sifting through volumes of data to give a clearer view of what that data means, but the actual function of a support desk needs a human aspect. People don't like talking Chatbots and interactive AI, and you cannot replace the human quality of having someone knowledgeable enough to fix issues and show the end user better ways to work and attention to detail to make them feel supported. Service desk technicians are already fearful for their roles in an industry where IT is being sanitized by business modeling, and the service desk technician is at risk of becoming just a "gig economy" role.