Reducing contact volumes without compromising the customer experience: myth or reality?

Reducing contact volumes can therefore be compatible with a good customer experience, but it depends on how the journeys are designed.

In most contact centers, a significant share of interactions relates to simple and predictable requests. Customers often reach out to track a request, retrieve a document, update personal information, or understand an administrative process. Analyzing contact reasons usually shows that many of these requests are recurring and could be handled without a call or a message to an advisor. It is also common for customers to contact support even though the answer is already available on the company’s website.

When repeated at scale, these requests create simultaneous pressure across the entire service. This becomes even more visible during peak periods, such as billing cycles, technical incidents, or the launch of a new service. Without proper routing mechanisms or self-service options, these peaks can quickly overwhelm teams and degrade service quality. They keep advisors busy with low-value tasks, increase handling costs, reduce reachability as answer rates drop, and extend AHT. The more time teams spend on avoidable requests, the harder it becomes to absorb peaks and respond quickly to customers who genuinely need assistance, which can quickly impact overall customer satisfaction.

From the user’s perspective, the experience is not optimal either. The customer has to contact support, wait, explain their need, and sometimes be transferred to another representative. For a simple request, this effort quickly feels disproportionate. The longer the journey, the higher the risk of frustration.

The real challenge is therefore to better distribute requests across channels, using the most appropriate channel for each need and reserving human intervention for situations where it truly adds value. When a customer can find information, complete a task, or track progress in just a few seconds, there is no longer a need to contact customer service. The company reduces avoidable volumes, improves team availability, and protects its key performance indicators.

In this context, self-service, AI agents, and visual IVR play a key role. They not only help reduce avoidable contacts but also improve key customer service metrics such as cost per contact, first contact resolution rate, reachability, and customer satisfaction. The performance of a contact center now relies on effective journey orchestration across tools and channels to deliver the right solution at the right time. These approaches guide users from the very beginning of their journey, reduce unnecessary contacts, and simultaneously improve reachability, service quality, and operational efficiency.

Self-service now plays a key role in structuring customer service operations. In many organizations, it represents the first step in a journey orchestrated across multiple channels and tools. It is no longer just about providing information online, but about designing journeys capable of resolving part of users’ needs without human intervention.

When well designed, self-service acts as a first layer of request handling. It provides immediate answers to the most common situations while guiding users toward the right action. Customers remain autonomous and progress at their own pace, without time constraints or dependency on advisor availability.

For organizations, the main benefit is qualitative. Self-service helps better distribute interactions between digital channels and human advisors. Teams can then focus on requests that truly require analysis, expertise, or more personalized support.

The value of self-service therefore depends on the quality of the journeys provided. Content must be clear, processes easy to understand, and users should be able to quickly identify the right action to take. When intelligently integrated into the customer journey, self-service improves both operational efficiency and the overall user experience. Its effectiveness also depends on user adoption. Journeys must be visible, easy to understand, and genuinely useful. When customers can easily identify these solutions, they naturally use them, and avoidable contact volumes gradually decrease.

AI agents now play a central role in structuring customer service operations. Their role is no longer limited to automatically answering a few simple questions. They are now actively involved in request routing and in shaping customer journeys.

A few years ago, automation tools mainly relied on menu- or button-based logic. Users had to select an option from predefined choices and navigate often rigid flows. This approach worked in some cases, but quickly showed its limits as soon as a request fell outside predefined scenarios.

AI agents (next-generation AI chatbots) have changed this paradigm. Thanks to natural language processing (NLP) and intent detection, they can understand what customers express in their own words. Interactions become more natural, and routing to the right solution is significantly faster.

Another major evolution lies in access to company knowledge. The quality of responses strongly depends on the quality of knowledge bases and underlying data. When information is well structured and kept up to date, AI agents can deliver more accurate and relevant answers. They are no longer limited to fixed scenarios. They can now leverage documentation and business data to retrieve relevant information before generating a response. This approach often relies on mechanisms known as RAG (Retrieval Augmented Generation). The agent retrieves information from available sources and then builds a response tailored to the customer’s request.

In contact center environments, particularly within CCaaS platforms such as Kiamo, these agents can be directly integrated into omnichannel journeys. They analyze the request from the very beginning of the interaction, identify the underlying need, and guide the user toward the most relevant option. In some cases, the answer can be provided instantly. In others, the agent prepares the handover to a human advisor by qualifying the request and passing along key information.

This evolution is fundamentally changing how interactions are handled. AI agents have become a layer of intelligence that streamlines journeys and contributes to the overall orchestration of interactions across channels and systems within the contact center. They reduce friction for users and improve the quality of exchanges when human intervention is required.This capability also relies on the level of trust placed in AI-generated responses. Organizations must ensure that the data used is reliable, that knowledge bases are up to date, and that journeys remain well controlled. These systems can also be continuously improved through the analysis of real interactions and user feedback, progressively refining intent understanding and response relevance.

The phone remains one of the most widely used channels in customer service. In 2025, 72% of French consumers say they trust phone advisors, a figure slightly up compared to 2023 (70%), according to the DialOnce & Kiamo 2023-2025 Barometer. It provides quick answers and allows direct interaction with an advisor when situations are complex. However, it also generates a large volume of simple requests that could be handled more efficiently through digital journeys.

Visual IVR directly addresses this challenge. It introduces a digital interface into the phone call and transforms what is often a linear journey into a more interactive and intuitive experience.

When a user calls from their smartphone, they receive a secure link via SMS that opens an interface directly on their screen. Instead of listening to voice menus and navigating through multiple options, the customer can visually identify their need and access the right action more quickly.

This approach changes the logic of phone-based journeys. Users can immediately understand the available options and choose the most relevant one based on their situation. They can access information, enter a self-service journey, be guided by an AI agent, or request to speak with an advisor.

For organizations, the benefits go beyond simply reducing call volumes. Visual IVR helps improve routing quality from the very start of the interaction. Users find the right solution faster, and advisors receive better-qualified requests.

For a long time, the idea of reducing contact volumes was seen as incompatible with a good customer experience. Many organizations believed that delivering high-quality customer service necessarily meant handling ever-increasing volumes of calls, emails, or messages. Reducing contacts was often associated with a decline in service quality or an attempt to limit access to advisors.

In recent years, this reality has significantly evolved. Thanks to improved digital journeys, the integration of self-service, and the emergence of more advanced tools such as AI agents and visual IVR, it is now possible to handle part of these requests differently. Simple interactions can be resolved faster through autonomous journeys, while advisors focus on situations that truly require human expertise.

Customers generally do not want to contact support if a faster and simpler solution is available. Most users are primarily looking to solve their issue as quickly as possible. When an answer is immediately accessible online or a task can be completed in just a few clicks, contacting an advisor often becomes unnecessary.

When a customer has to call for a simple request, the experience can quickly deteriorate. Waiting times can be long. Voice menus can be difficult to navigate. Users may have to explain their situation multiple times before getting an answer. In such cases, the effort required from the customer becomes unnecessarily high. Every unnecessary step in the journey creates additional friction whether it is waiting, repeating the issue, or navigating multiple options before reaching a resolution.

The goal is therefore not to limit access to advisors, but to offer more efficient journeys from the very start of the interaction. When customers can immediately access the right information or action, resolution is faster and the experience becomes smoother.

This shift is fundamentally transforming the work of customer service teams. Advisors are no longer primarily handling repetitive requests. Their role is evolving toward more analysis, guidance, and resolution of complex situations, increasing the value of each interaction. When advisors are no longer overwhelmed by high volumes of repetitive requests, they have more time to analyze situations, support customers, and provide tailored solutions. Interactions become more meaningful, and the value delivered to the customer increases.

What once seemed like a myth has now become a reality for many organizations that are rethinking their customer journeys.

For a long time, reducing contact volumes while improving customer experience seemed contradictory. Many organizations still associated service quality with the ability to handle ever-increasing volumes of calls or messages.

Today, tools are easier to deploy, more intelligent, and more autonomous. Self-service, AI agents, and visual IVR already make it possible to guide users more effectively and resolve part of requests without human intervention.

The next step lies in agentic AI. Unlike traditional AI assistants that mainly respond or route requests, these agents are capable of taking action. They can chain multiple steps within a journey, interact with various business systems, and execute tasks to resolve a request end-to-end. However, this transformation is still ongoing, and these approaches are still being deployed and refined. Organizations need to analyze interactions, identify friction points, and continuously improve their journeys. This ongoing governance of customer journeys is becoming a key factor in fully leveraging these technologies. It paves the way for contact centers where automation no longer stops at answering, but actively contributes to resolving requests.

The challenge is no longer to limit access to customer service. It is about designing smarter journeys so that customers can find the right solution faster, while reserving human intervention for situations where it truly adds value.