ChatPandas | First contact resolution - ChatPandas

First contact resolution

High first contact resolution, none of the disappointments 

First contact resolution is one of the most important metric of call center performance, if not the most important. FCR is crucial to measure the quality of customer service, to determine the efficiency of call center agent and thus an important factor in profitability of a call center. FCR reduces operating costs, improves customer and employee satisfaction, increases sales opportunity and improves NPS. The importance of FCR metric is so high that it is often used as an enterprise wide metric for performance accountability.

What is FCR and how is it calculated?

FCR is the ability of a call center to resolve queries, questions or problems of the customer in the first attempt, eliminating the need for follow ups. First Contact Resolution rate is the percentage of customers who resolved their queries on the first call or contact.

FCR Formula

The formula that we use for calculating FCR is based on calculating the number of customer inquiries solved on first call divided by the total number of customers with the inquiry multiplied by 100. 

FCR = (Number of customer inquiries solved on first call/ Total number of inquiries x 100)

Steps to measure FCR

To measure FCR, we take the following steps:

Defining Time Span

The first step we take is we define the time period during which the FCR is being calculated for. This can be a specific time period of days, weeks, months or can be a targeted time.

Data Compilation

We make sure to measure to all elements to make the measurement more effective. We calculate ACD, IVR and CT reports which include performance evaluation of agent, agent groups and different departments. We compile call work reports of all agents, collect data of customer surveys, performance management and quality monitoring tools. We also collect data of outbound calls which include call log details, customer’s information, query details, agent information, and satisfaction level scores which we also list in the CRM system along with other information like tracking DNIS.

Sifting Data

All unnecessary data has to be sorted and sifted to make sure useful data can be found in time. The data which doesn’t fall in the specific time frame, specific geographical location has to be sorted out. Calls with incorrect data, irrelevant calls and wrong numbers have to be removed from our logs for future references.

Total call count

We keep a record of all inbound and outbound calls which includes repeat and abandoned calls as well as outbound calls to the customers. It is important to calculate total call count as it will be used in FCR formula for calculating it.

Fragmenting Repeat Calls

Since we also included repeat calls in our total call count, in this step we remove all the repeat calls which include calls by the same customer in the time period assigned. We also compile the repeat call data in our pre defined window which helps in measuring FCR rate. 

Segmeting calls 

We also segment calls based on the query asked be it technical support, sales, order processing, billing, general inquiry, complain or manufacturing. This helps agents understand the best solution in response to the query asked.

Digital Recipe

In this step we apply formulas for time period, department, call type and FCR. This gives us a complete picture of handling different variables which ultimately improves call performance and pin points inefficiencies in the query resolution process.

Improvement in FCR

Once we measure FCR, now is the time to improve it. We have developed a complete plan to improve FCR. 

Benefits of FCR

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