Long waiting times increase the total costs of customer contact in several ways at once. Not only do direct personnel costs rise because employees spend more time on each contact, but you also lose customers, generate repeat contact, and damage your reputation. Especially for service organizations with a high contact volume, waiting times are therefore one of the most underestimated cost drivers. In this article, we answer the most frequently asked questions about waiting time and its financial impact on your contact center.
What are the hidden costs of long waiting times?
The hidden costs of long waiting times in customer contact are significantly larger than they appear at first glance. In addition to the visible costs of extra personnel and longer call times, high waiting times lead to repeat contact, customer churn, reputation damage, and higher pressure on employees. Together, these factors form a cost item that often remains invisible in reports in practice.
Many organizations only measure the surface: the number of calls, the average handling time, and the occupancy rate. But those who look deeper see that a customer who waits too long often calls back, sends an email, or contacts via another channel. This so-called repeat contact doubles the workload without the problem being solved any faster.
In addition, there is the effect on customer retention. A customer who structurally waits too long drops out. In sectors such as utilities, housing associations, or education, this does not always mean direct loss of turnover, but it does mean increased complaint pressure, escalations, and reputation damage that brings indirect costs.
How does waiting time influence customer behavior?
Waiting time influences customer behavior in three measurable ways: customers drop out early, contact more often via other channels, or become more negative in their assessment of the service. This behavior increases the pressure on the contact center instead of reducing it, creating a negative spiral.
When a customer stays in the queue for too long, the chance increases that they hang up and call again. This increases the total contact volume without more questions being resolved. Customers who contact via multiple channels at the same time also end up in different systems, leading to double work for employees and confusion for the customer themselves.
The relationship between waiting time and customer satisfaction is direct and measurable. Even a waiting time of a few minutes can negatively color the perception of the entire service, regardless of how well the conversation goes afterwards. For organizations where customer contact is business-critical, this carries extra weight.
What is the relationship between waiting time and personnel costs?
High waiting times almost always lead to higher personnel costs in the contact center. When customers call back more often or contact via multiple channels, the total contact volume increases. More volume means more required capacity, higher workload per employee, and ultimately more deployment of personnel to clear the backlogs.
The relationship also works the other way around: a shortage of personnel causes longer waiting times, which triggers repeat contact, which further increases the workload. This is one of the most common vicious circles in customer contact environments. Employees who are structurally under pressure also make more mistakes, leading to more aftercare and a higher average handling time per contact.
Insight into this mechanism is crucial for a fair business analysis of your contact center. Those who only look at the costs of an extra employee miss the bigger picture of what waiting time structurally demands in terms of capacity.
When do waiting times become a business-critical risk?
Waiting times become a business-critical risk the moment they are structural, affect customer retention, or endanger the organization’s service delivery. For organizations with legal accessibility standards, such as government agencies or healthcare providers, this can also lead to compliance problems and reputation damage at the board level.
There are three signals that indicate waiting times have become a strategic problem:
- Structural repeat contact: customers call or email multiple times for the same question, indicating insufficient accessibility or insufficient problem resolution at first contact.
- Rising complaints and escalations: waiting time is one of the most mentioned reasons for formal complaints, which brings management time and recovery costs.
- High employee turnover: structural overload due to high contact pressure increases absenteeism and outflow, driving up the costs of recruitment and onboarding.
The moment several of these signals occur simultaneously, waiting time is no longer an operational detail but a strategic priority that deserves attention at the executive level.
How do you calculate the actual costs of waiting time in your contact center?
You calculate the actual costs of waiting time in your contact center by adding up three cost components: the direct costs of repeat contact, the indirect costs of customer churn, and the hidden costs of employee overload. Only those who include all three get a realistic picture of what long waiting times actually cost.
Direct costs: repeat contact and extra volume
Determine the percentage of customers who call back or contact again via another channel. Multiply this by the average costs per contact. This number gives you a concrete estimate of what waiting time generates in extra contact volume, separate from the original contact volume.
Indirect costs: customer churn and reputation damage
Estimate how many customers drop out as a result of poor accessibility. In sectors with long-term customer relationships, such as housing associations or utility companies, this translates into higher complaint pressure, more escalations, and administrative attention that costs time and money. The impact on the Net Promoter Score or customer satisfaction measurements also has an indirect financial value.
Hidden costs: employee deployment and absenteeism
Calculate how many extra hours employees spend on clearing backlogs. Add to this the effect of increased absenteeism and turnover. The costs of recruitment, selection, and onboarding of new employees are significant and are rarely included in the standard cost calculation of customer contact.
Which measures reduce waiting time without extra personnel?
Reducing waiting time without deploying extra personnel is possible by dealing smarter with the existing contact volume. The most effective measures focus on preventing unnecessary contact, automating simple questions, and improving routing so that customers reach the right employee faster.
The most impactful approaches are:
- Self-service and knowledge bases: customers who can find the answer themselves do not call. A well-designed self-service environment significantly reduces the incoming contact volume.
- Intelligent call routing: by sending customers directly to the right employee or department based on their question or customer profile, the average handling time decreases and the first-contact resolution increases.
- Chatbots and virtual assistants: for frequently asked and simple questions, automated assistants can handle a large part of the contact volume independently, without an employee needing to be involved.
- Proactive communication: informing customers before they contact you themselves, for example about the status of an application or a known malfunction, prevents a large wave of incoming questions.
- Process automation: repetitive tasks in the back office, such as processing forms or updating customer files, cost employees a lot of time that they cannot spend on customer conversations. Automating these tasks gives capacity back.
The combination of these measures yields the most in practice. One single adjustment has limited effect; a coherent approach where channels, routing, and automation are aligned with each other reduces waiting times structurally.
How Pegamento helps in reducing waiting times and customer contact costs
We help Dutch service organizations to structurally reduce waiting times and to make the total costs of customer contact transparent and reduce them. Our approach always starts with a thorough analysis of your current situation: where do waiting times arise, what are the actual causes, and what costs are involved?
What we offer:
- Business case and analysis: we map out the hidden costs of waiting time and build a well-founded business case for improvement, so that you can create internal support.
- Omnichannel contact center solutions: we integrate telephony, email, chat, WhatsApp, and other channels into one clear environment, without separate systems and without complex supplier management.
- AI and Agentic AI: we implement intelligent assistants that independently handle simple questions, provide routing, and support employees. What used to be RPA, we now position as Agentic AI: self-thinking assistants that do not just follow instructions, but take independent initiative.
- Process automation: we reduce manual work in the back office so that employee capacity is freed up for customer conversations that really matter.
- One point of contact: from analysis to implementation, management, and continuous optimization, you arrange everything with us. No silos, no complex supplier management, but a total package under one roof.
We work with proven modules that we combine smartly based on your processes, systems, and objectives. No costly customization, but a smart combination of proven building blocks that connects to your organization.
Do you want to know what waiting time actually costs your organization and which steps yield the most first? Contact us and we will be happy to think along with you.
Frequently Asked Questions
What is the maximum waiting time before customers drop out?
Research shows that most customers are willing to wait a maximum of 2 to 3 minutes before hanging up and calling again or switching to another channel. This differs per sector: for urgent matters, such as malfunctions or healthcare questions, the tolerance limit is significantly lower. It is therefore wise to measure your own abandonment rate per time slot and channel, so that you know exactly where the pain points are in your specific situation.
What is a realistic percentage of repeat contact and how do I know if my contact center suffers from this?
In practice, the repeat contact percentage at many contact centers is between 20% and 40% of the total contact volume, but this is rarely actively measured. A simple way to detect this is by looking at how many customers contact again within 24 to 48 hours with the same customer number or about the same subject. If this percentage is above 15%, repeat contact is almost certainly a significant cost driver in your organization.
Which KPIs should I track to signal waiting time problems early?
The most valuable KPIs for signaling waiting time problems early are: the average waiting time per channel, the abandonment rate (percentage of customers who hang up before answering), the First Contact Resolution (FCR), and the repeat contact percentage. Combine these metrics with employee satisfaction scores, because rising absenteeism or falling employee satisfaction is often an early signal that the contact pressure is running too high. Those who only manage on occupancy rate miss the broader context.
Is reducing waiting times also relevant for organizations without commercial customer contact, such as municipalities or housing associations?
Absolutely, and sometimes even to a greater extent. Organizations without a direct competitive incentive may run less risk of customer churn, but they more often deal with legal accessibility standards, political pressure, and a high volume of complaints that requires management time and administrative attention. Moreover, municipalities and housing associations operate with public money, making inefficiency in customer contact directly visible in the budget. Reducing waiting times is therefore both a quality and an accountability issue here.
How do I start improving waiting times if I don't know exactly where the problem lies?
The best starting point is a thorough analysis of your current contact flows: how many contacts come in per channel, at what moments do volumes peak, and what are the most common reasons for contact? It often turns out that a relatively small number of contact reasons is responsible for a large part of the volume. By first tackling that top 5 of contact reasons, for example via self-service or proactive communication, you quickly achieve measurable results without large investments in extra personnel or technology.
What are the most common mistakes when implementing chatbots or self-service to reduce waiting times?
The most common mistake is deploying a chatbot or self-service solution without linking it to the actual contact reasons of customers. A generic FAQ page or a bot that is too limited in its design frustrates customers and ultimately increases the contact volume instead of reducing it. Always ensure that the self-service solution is based on real customer data, that there is a clear fallback option to an employee, and that the solution is continuously optimized based on usage data and customer feedback.
How do I convince internal management or the board of the need to invest in waiting time reduction?
The strongest internal business case combines hard financial figures with strategic risks. Calculate the costs of repeat contact, estimate the effect on customer satisfaction scores, and quantify the personnel costs associated with overload and turnover. Add to that the reputation risks and any compliance risks, and you have a story that appeals to both the CFO and the Customer Contact Director. An external party that helps in drafting a well-founded business case can significantly accelerate this process and strengthen the credibility of the analysis.
