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How To Decrease Customer Service Contact Rate Without Risking Experience?

May 10, 2023
6 min. read
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How To Decrease Customer Service Contact Rate Without Risking Experience?

Introduction

Balancing customer experience and cost in customer service teams has been a never-ending struggle for businesses. The challenge is that the more personalised and longer the support is, the better the experience becomes, however at the same time, the cost of support increases.

While decreasing the number of issues would be ideal, it is often the most difficult to achieve. Therefore, many companies opt to reduce in-person contact rates and encourage customers to use non-personal channels instead, which helps with cost but not with experience.

Fortunately, technology is here to help. In this article, we will discuss how to decrease contact rate without decreasing customer experience.

The Status Quo: Approaches Used To Decrease Contact Rate

As companies opt for reducing their contact rate and with that their cost in customer service teams, they tend to implement methods that have a negative impact on customer satisfaction. The most common ones are the following:

  1. Make it difficult (or impossible) to find contact options

It is unfortunately a common practice in many firm’s cost cutting strategy for decreasing contact rate to bury their contact details, deterring customers from calling or writing for help. While it is indeed cost-effective in the short-term, it often leads to customer dissatisfaction, bad reviews, and finally customer churn. If customer experience is a priority, this approach should be avoided at all costs.

  1. Using chatbots or automated decision trees

Another widely used method for reducing contact rate is using chatbots. Bots may satisfy routine or straightforward inquiries, such as FAQs or account balances. However, without human backup its limits can certainly be discovered. When the customer is stuck with the bot and no one is available to take over the conversation, there is no collaboration between bots and human workforce, it may leave customers feeling frustrated and unsatisfied with the service. 

  1. Providing online tutorials for self-resolution

Companies may offer online tutorials to help customers solve issues on their own. However, these tutorials may only be effective for basic technical problems, as they lack interactivity and may not provide comprehensive solutions for complex issues. Customers who are unable to resolve their problems through the tutorials may seek support from other channels, resulting in higher contact rates.

Offering a wide range of self-service options can help lower customer service contact rate, but it is important to remember that customers mostly look for these options when they are already experiencing issues with your product or service. Of course best would be to avoid incidents at all, but in large and complex companies this is rather a distant dream than the reality. We believe that the second best would be to proactively detect and respond to incidents, so that customers don’t need to contact customer service. While this sounds logical, it’s not easy to implement. 

The Solution: Detect Incidents Proactively

Proactive detection and quick resolution of incidents can significantly decrease contact rate and at the same time increase customer experience as customers either are not even aware that they had issues thanks to the quick resolution, or get proactive and transparent communication about the status of what’s happening.

This hasn’t been possible for customer service teams in the past either as the underlying data hasn’t even existed to catch these incidents, or because it took a significant amount of effort from the engineering or data teams to set up automated monitors for such incidents. 

Luckily, this is changing now. Thanks to digitalisation, operational data is now available for businesses from usually all touchpoints of customer journeys. Furthermore, such data is becoming more easy to access and utilise thanks to the wider adoption of cloud-based data warehouses, data transformation, data monitoring tools and no-code systems that can make such data available for non-technical users. 

Using a data driven monitoring and incident management solution saves time for your customer service teams, and allows them to focus on issues that require in-person resolution, due to complexity. By this approach your team can stop the constant fire-fighting mode, without ignoring your customers’ needs. This can help you prioritise your team's efforts and provide a higher level of service, resulting in higher customer experience.

How To Implement a Proactive Monitoring & Issue Resolution System

Implementing such a proactive detection system doesn’t have to be another large implementation project. We rather recommend moving towards this direction step-by-step. As both your teams and your customers start to experience the benefits of proactivity and transparency, then you can start thinking about adding new use cases.

You can follow the following steps to implement a proactive monitoring & issue resolution system in your organisation:

  1. Understand contact reasons & root causes

To start, export a list of all contact issues from the past month and categorise them based on contact reasons, if not already done. This information should be exportable from all contact center systems, such as Zendesk or Salesforce. Ideally, agents should already categorise issues when closing them, but if not, have analysts review a subset of the issues to gain an understanding of the most common categories. Once you have a sorted list of categories, meet with your team to brainstorm potential root causes for the most frequent contact reasons.

  1. Define & prioritise use cases

After identifying the root causes for the most common contact reasons, it's important to assess the impact and feasibility of detecting these incidents based on available data. Impact can be measured by the number of potentially avoided contacts, as well as indirect impacts such as improved retention or reduced lost revenue. Additionally, consult with technical teams to determine whether the necessary data is available in the data warehouse to detect these incidents in real-time. Once you have assessed both impact and feasibility, prioritise the first use cases to be implemented. Usually it’s worth starting with high impact and low effort quick wins.

  1. Set up your proactive monitoring system for the prioritised use cases

At this stage, you will require support from your technical teams. We recommend investing additional time into setting up an effective detection and resolution system that can be reused for future use cases. The system should be flexible to allow for frequent iteration on detection rules as you gain insights throughout the process, and should include relevant integrations to send notifications to the appropriate people through the right channels, such as SMS to customers or Slack to internal teams. Ideally, the system should come with an easy-to-use interface that empowers business teams to make necessary changes themselves.

  1. Learn, iterate & and add new use cases

It goes without saying that setting up an effective incident detection system cannot be a one-time endeavour. You must continue to monitor the impact of your detection system and refine it based on feedback, such as fine-tuning conditions, changing notification channels, or adding escalation points to prevent alert fatigue. Additionally, as the organisation begins to reap the benefits of such a system, they will seek new use cases, and the system must be ready to swiftly implement them to maintain momentum.

Case Study: Implementing Proactive Delivery Delay Monitoring

A leading European e-commerce company faced significant challenges in responding to customer service inquiries, especially during busy periods such as Christmas, Black Friday, or Cyber Monday. This not only put a lot of pressure on the contact center teams but also seriously damaged the customer experience.

Upon examining the number of issues, it became apparent that one of the primary drivers of complaints was delivery delays. Despite the information being visible on the order confirmation page, customers didn't check it for live updates.

The company chose to implement proactive and transparent communication about delivery delays. Fortunately, they had detailed timestamps of each step of the delivery process (a mix of in-house and third-party couriers), which allowed them to build upon the data. The engineering team, in conjunction with the business teams, developed an internal system that enabled the business teams to quickly set up and iterate conditions and corresponding communication messages.

The company launched with A/B tested notification rules and message content to determine which ones had the most significant impact on the contact rate and customer experience. Ultimately, the initial pilot phase resulted in a ruleset in which customers received apologising messages for shorter delays and varying amounts of vouchers for longer delays. The notifications also pointed out that unfortunately, the contact center teams wouldn't be able to provide more information about the status of the orders than the order tracking page.

This development led to a 15% decrease in the number of customer service contacts and a significant increase in NPS, outweighing the increased compensation costs from the vouchers. The company still has an iterative process of testing and modifying communication and compensation rules depending on current business objectives.

About Flawless

Creating a scalable and flexible incident detection system can consume a significant amount of development capacity from already busy engineering teams. As a result, for many companies, building such a system remains a distant wish.

The same was true for the e-commerce company mentioned earlier, until they discovered Flawless - a data monitoring and incident management system designed precisely for this purpose. What makes Flawless unique is that it can be implemented in just a few minutes, thanks to its pre-built integrations with data sources and destinations. Additionally, it has a user-friendly, no-code interface, which allows non-technical stakeholders to use it.

If you’re interested in trying Flawless, you can request a free trial here.

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