Organisations have struggled with the growth in customer contact volume and complexity as the Covid-pandemic accelerated digitalisation and made digital channels mainstream almost over night. Contact volumes keep on increasing as expectations for service quality rise. Needless to say, efficiency in managing customer support ticket queues is turning into a major factor when it comes to competitive advantage.
Overtime work is not a sustainable nor a cost efficient way for taming long ticket queues, but it often is the only way to tackle the huge ticket backlog and to ensure the availability of customer service. If the root causes that cause the queues cannot be eliminated, the the ticket backlog will - for sure - pile up again.
If your goal is to get rid of the tradition of overtime work in managing ticket queues, identifying failure demand can be the most effective starting point for achieving that goal.
Customer service is usually contacted because some part of the service does not work for the customer and they do not manage to solve the situation through the self-service channels offered: there is a delay in delivery, there is a problem in invoicing or the renewal of the order cannot be done.
Failure demand, thus, occurs when customers unwillingly and reluctantly have to return to the service as their problem cannot be solved or the solution offered solves only partially the problem at hand. In other words, failure demand accounts for those customer contacts that have been made about the same issue several times - possibly even in several different channels.
Such contacts and situations are extremely frustrating for customers, burden customer service staff and most likely will increase the customer service costs.
Actually, the number of contacts that count as failure demand is very high. According to international studies, for example, in the financial industry, up to 30-60 per cent of all customer contacts are failure demand. For telecommunications operators, failure demand can account for more than 70% of all contacts.
In order to permanently reduce long support ticket queues, it is important to identify the root causes that cause failure demand in the first place. In other words, companies need to recognise what are customer problems that repeatedly remain unresolved. Only when the root causes have been discovered, it is possible to analyse why those problems cannot be solved. You see, failure demand always suggests that the work is organised in the wrong way, since it does not enable serving the customers according to their needs.
But is this task easier said than done?
Repairing the biggest and also the hidden defects in the service is probably the goal of each company. Who wouldn't want to offer their customers a smooth service experience, and even to implement this smooth service at a moderate cost.
In reality, identifying the right development areas related to customer experience is a challenging task. Today's companies can have thousands or even tens of thousands of customer contacts a week, as well as several different customer service channels where these contacts are handled. Finding the right development areas can sometimes feel like looking for a needle in a haystack.
Of course, different technologies are being used to classify problem areas. Every customer service team surely has a contact classification technology in place to show what the customer's problem is related to: delivery, invoicing, the product itself, etc.
However, these classification technologies are not able to demonstrate the volume of failure demand in customer communications, nor the root causes for failure demand. And it is precisely by identifying and analysing failure demand that would make visible the weaknesses of the organisation that repeatedly and unnecessarily lead to customer contact.
Identifying failure demand has previously required lengthy consulting processes, during which customer contacts and customer service's ability to solve customer problems during the first contact have been manually reviewed and analysed. However, manual analysis work is neither scalable nor cost-effective. In addition, if the actual development work can only be started after months of analysis work, the customers' everyday lives may already have changed in relation to the starting point considering the rapid pace in today's economy and society.
Luckily, consultancy is not the only possible option anymore. Aiwo is the first service provider in the market that offers unique technology for identifying failure demand. This is a significant innovation in the field of customer service, as it will greatly accelerate the discovery of root causes and a situational picture of failure demand. The technology also enables real-time monitoring of the effectiveness of development activities.
Of course, the identification of failure demand does not in itself eliminate the sources of failure demand. However, it guides you to the right development areas, which are usually related to something completely different from the customer service team's efficiency in handling support tickets.
And the sooner the sources of failure demand can be identified, the sooner changes can be made to the service that will help provide customers with exactly the service they need. This, in turn, has really positive effects both in terms of cost development and customer and employee experience.
According to a customer experience survey by Genesys, the number of customer contacts has almost doubled between 2020 and 2021. Everyday employees working in customer service have also recognised that customer contact volumes have been increasing for a long time now. Therefore I dare say that the volume of failure demand has also increased. If hiring more people in the customer service team is not an option, overtime work will continue to be one of the only options to tackle the huge ticket backlogs. Both of them are a costly way to solve the problem.
However, there is no use in optimising work for tasks that should not be done in the first place. A better way of managing the support ticket queues would be to minimise the volume of failure demand. In other words, organise work and the whole system in such way that enables resolving customers' issues during the first contact. Identifying failure demand is an efficient way to find the right areas for development to achieve this goal.
We would love to hear your thoughts on our newest failure demand feature: do you find it useful or how could it serve your purposes even better? Book a time for a demo and I'll walk you through it.