By Swati Sahai

Research has found that Americans spent more than 900 million hours on hold in a single year. That adds up to 40+ days on hold for every person over the course of a lifetime! For a business, that means high costs and inefficient call center operations. Call centers, therefore, want to improve first call resolution rate, reduce call volume, and excel at customer service while reining in high costs.

There has been a concerted effort to move customer interaction towards lower cost digital channels and away from voice calls in recent years. However, customers usually escalate to voice calls when companies are unable to resolve issues through digital channels.

In this scenario, it becomes important for call centers to excel at customer service and reduce cost-to-serve without negatively affecting the customer experience.

The detailed steps provided in this post will help achieve all these goals.

1. Employ Customer Journey Analytics

Customer journey analytics can be the breakthrough that call centers need in order to deeply understand customer service journeys. This is the first step to improve first call resolution rates, reduce call center volumes and build successful digital customer interactions that don’t lapse into voice calls.

Previously, companies would either attribute customer service escalation to the last interaction or resort to customer surveys to learn why customers escalated to voice calls. Both of these methods have severe limitations. Customer journey analytics is a far more accurate way to understand what’s really happening during customer service journeys and where the failure points are.

But how exactly will customer journey analytics work in a call center operation? Here are the nuts and bolts.

Complete Guide to Call Center Metrics and Analytics eBook

Integrate Structured and Unstructured Data Easily

Integrating customer interaction data across channels such as IVR systems, chat transcripts, website, social, messaging, etc. has always been a challenge for call centers. This is due to the underlying infrastructure, channel and process silos.

Main challenge to track customer journeys and improve first call resolution

Using customer journey analytics, you can integrate your structured data (website, CRM system) with your unstructured data (transcripts from web chat, audio call recordings, chatbot transcripts). This process is done rapidly, easily and without first requiring customer identity matching, schema setup or fixed field mappings for different event types.

Advanced customer journey analytics platforms have built-in ETL capabilities that allow you to extract data from your system in the format that is easiest for you to use.

Start with a Hypothesis of the Most Common Failure Points in the Customer Service Journeys

To leverage customer journey analytics to its fullest extent, start with your hypothesis of the most common failure points in customer service journeys.

Use journey analytics to discover how many actual customers are taking those customer service journeys—in other words, put real numbers behind your hypothesis.

For instance, a telecom company could hypothesize that an existing customer moving to a new house is a service journey that usually starts on the website but frequently escalates into a phone call to the customer care center.

Improve first call resolution rate, accelerate self help and reduce volume

Using a customer journey analytics platform, the telecom company discovers that those who want to inquire about whether they can bring their equipment to their new home are much more likely to eventually end up escalating to a voice call, compared to those who want to confirm if their channel lineup will remain the same in their new address.

Now you have actionable data on the biggest failure point in this customer service journey. With this data in hand, you can conduct a thorough analysis of why customers are failing to resolve the equipment issue on their own and take the necessary steps to improve this customer interaction.

Discover Cross-Channel Customer Service Journeys to Understand Where Calls Originate From

telecom journey analytics use case
A North American telecom company uses Pointillist to identify poor performing self-help channels and prioritize them for improvement.

The analytics team at a leading telecom provider is tasked with analyzing self-help mechanisms to reduce call volume and cost to serve.

Customer behaviors vary across different channels. Contact centers today have data to determine the aggregate customer movement but not the insight into customer journeys across channels.

Discovering cross-channel journeys yields a treasure trove of valuable insights including where the call originated from, the intent of the call, and the efficacy of customer service channels.

As contact centers make a concerted push towards self-service, discovering cross-channel journeys becomes even more important.

For instance, a common customer service flow could be from website to IVR systems.
By visualizing this information within a customer journey analytics platform, you can also learn the following:

  • What task was the customer trying to accomplish?
  • How many customers took that path?
  • What percentage of customers who took that path eventually churned?
  • The revenue impact of the churn

An important insight from discovering cross-channel journeys is the relative effectiveness of different customer service channels. You could learn, for example, that customers with billing problems move from website FAQs to voice call twice as fast as from chat to a voice call.

This analysis reveals not only where the calls originate from but also where to target investments to get maximum ROI while keeping customer satisfaction unchanged.

The in-depth context that customer journey analytics provides is a big help in routing inquiries to the right agent. It allows you to organize incoming message flows in such a way that, given their context, they can be dealt with by the agent who has the best skills to resolve the issue in the first contact.

Use Predictive and Proactive Self-Service to Reduce Call Volume

Using customer journey analytics insights, predict when an escalation is likely to occur and use it as an opportunity to proactively provide self-service to customers.

In the telecom example we used earlier, proactive self-service would mean creating an easily accessible guide to walk customers through equipment changes when they move to a house.

Tag Your Customer Service Touchpoints

Employing customer journey analytics in your call center operation has the added benefit of tagging all your customer service touchpoints. This will help in anticipating escalations and in turn improving your First Call Resolution (FCR) rate.

Once you remove the silos from your website, mobile app, chatbot, and other touchpoints, you will better understand customer behavior, pain points, and drop-offs, and be prepared for escalations from self-service to voice calls when they do occur.

2. Measure Customer Satisfaction (CSAT) Frequently to Improve First Call Resolution

Customer satisfaction is directly related to your First Call Resolution Rate. By measuring CSAT frequently, you know whether your CSAT (and therefore FCR) is trending in the right direction or not.

Moreover, as customers increasingly use digital interaction channels, while ease-of-use may go up, customer intimacy, trust and therefore customer satisfaction may come down.

In fact, a recent survey of U.S. retail bank customers by Forrester echoed this finding:

“Speaking to a representative in person or over the phone evoked the greatest amount of positive sentiment for customers.”

– Forrester U.S. Banking Customer Experience Index 2018 Report

Keeping track of CSAT scores is, therefore, vital.

3. Measure Customer Effort Score (CES) Regularly

Measure Customer Effort Score to understand the touchpoints where customers have to expend the most effort. High Customer Effort Scores usually indicate common failure points in the customer service journey, leading to costly escalations to the call center.

Measure Customer Effort Score Regularly to Improve First Call Resolution

Fixing these failure points will result in reduced call volumes, increased efficiency of self-service channels and also better ROI on your customer service investments.

4. Analyze and Segment the Cause of Repeat Calls

To improve First Call Resolution rates and reduce call volumes, it is important to isolate the cause of repeat calls.

It is important to keep in mind that a problem that takes too many calls to resolve is more inefficient and costly for a company than a problem that takes a longer call to resolve.

Segment the cause of the repeat calls into different buckets such as technology problems, agent performance problems, or underlying process problems.

This analysis and segmentation will lead to a faster resolution of the repeat calls and eventual reduction in the volume of overall calls.

5. Authorize and Incentivize Agents to Reduce Call-Backs

First Call Resolution rates are higher when you authorize your agents to collaborate with other teams or individuals directly to solve problems in real time. In effect, you promote “total contact ownership.” When a single agent handles the call from start to finish, the resolution is faster and the customer satisfaction is much higher.

Incentivizing agents to prioritize resolving a problem in the first call has a strong impact on reducing the number of call-backs. Agents are often measured on Average Handle Time (AHT), which is a measure of the time spent by an agent to handle a request.

This may sometimes lead agents to handle a request as quickly as possible, without ensuring that the problem has indeed been solved.

To change this mindset, explain the importance of improving the FCR rate and its positive effects on the call center operation. If needed, incentivize performance based on FCR rate.

A high First Call Resolution rate not only increases customer satisfaction but only promotes agent satisfaction. When they solve issues on the first contact, agents are reported to be far more satisfied and less stressed, than when dealing with an unhappy customer who has made a second or third call.

6. Provide the Right Training to Agents to Improve First Call Resolution

Giving the right training to call center agents is absolutely essential in order to improve First Call Resolution and reduce call center volumes.

A study by service and support industry consultant MetricNet found that the biggest driver of FCR is agent training hours. Investment in agent training pays off in terms of improved FCR rates and consequently, higher customer satisfaction.

One of the biggest drivers of improving first call resolution is agent training

Image source: MetricNet

The first level of training to an agent is on the company’s product and services so that they are thoroughly equipped to answer any query related to a product/service without needing expert assistance. Having a product knowledge base handy often helps.

Cross-train agents on the functions of other teams or departments so they are better equipped to navigate a complex issue and connect a customer with the right resources as quickly as possible.

Similarly, training agents to isolate and get to the core of the problem is essential to improve First Call Resolution. Agents must be trained to clearly ask customers whether the issue has been resolved and not rely on their own judgment.

A simple question, like the following, before the end of the interaction, can do the trick:

“Have I fully resolved your problem? Is there anything else I can do for you today?”

This gives customers to ask more questions and clarify any doubts, instead of having to call back. It also results in higher customer satisfaction.

Training should also include ‘next issue avoidance’ so that agents can anticipate follow-up inquiries based on the current customer problem.

7. Make Customer Data Available to Agents in Real Time

Dashboard for call center agents to show customer data in real time

Providing agents with a customer dashboard that has a 360 degree or a single customer view in real time allows them to have the most information possible to resolve problems in the first contact. It empowers them to provide consistency and continuity in every interaction.

Agents can use these dashboards to access purchase history, customer preferences, conversation history, during a live conversation to handle customer requests.

When every customer interaction with a company is contextual and shows that a company knows who they are and what they need, customers are far less frustrated by the time they reach a human interaction. This not only results in increased customer satisfaction and higher FCR rates, but also provides relief to agents and therefore increased job satisfaction.

8. Make Digital Interfaces More Human-Like to Accelerate Self-help

Customers like a personal touch. Adding conversational interfaces (such as video tutorials) to static self-service content will go far in accelerating the adoption of self-help channels among customers.

Similarly, training chatbots to be more human-like will result in higher customer satisfaction and reduced call escalation. AI-powered virtual assistants can shadow an agent’s work and learn from their customer interactions until they are able to take over an entire conversation without a customer feeling much of a difference. These technologies may be nascent today but are rapidly evolving.

9. Use AI to Improve Process Efficiencies

Artificial intelligence can automate entire call center processes such as account onboarding or filing claim, leaving only the most complex issues to be handled by humans.

AI can also streamline processes by extracting insights through text analytics, speech analytics, and sentiment analysis to discover trends in data and problems that impact customer satisfaction and retention.

All of this results in reduced call volumes (and therefore reduced cost-to-serve), improved First Call Resolution Rate, enhanced customer satisfaction and a greater return on investment.

To Summarize

Smart companies always view individual interactions in the larger context of customers’ cumulative experiences with the business. They understand the typical milestones in customer journeys and understand how call centers play a role.

Using customer journey analytics and artificial intelligence, in combination with traditional methods like comprehensive agent training, is the best way to improve first call resolution, reduce call center volume, optimize processes and accelerate lower-cost digital self-help methods.