How to Calculate the ROI of Online Communities

By Richard Millington

ROI People

Now you’re on to the final customer service benefit of a community, namely first contact resolution (FCR). FCR is so similar to agent productivity that we almost combined the two. However, we opted against it because FCR is such a widely used metric to gage success and is easy to measure for an organization. The FCR rate is the number of customer problems resolved at the first attempt (i.e. the number of calls a customer service takes to resolve the problem of a single customer).

By exposing customer service representatives to the community, they may be able to identify and resolve a larger number of calls they receive at the first attempt.

This might be through finding a similar discussion topic in the community and seeing how other customers solved the problem. It might be by building a bigger database of customer-supported solutions. It might be by becoming aware of new issues as they are emerging and preemptively developing solutions for them.

Resolving a problem at the first attempt reduces the overall number of calls the customer service team receives. This is the comparative metric we aim to measure here.

You need six pieces of information to calculate this rate. These are:

  1. Number of calls received by agents ‘not exposed’ to the community per month.
  2. Number of customers helped by agents ‘not exposed’ to the community per month.
  3. Number of calls receives by agents ‘exposed’ to the community per month.
  4. Number of customers helped by agents ‘not exposed’ to the community per month.
  5. Number of customers who call for support per year.
  6. Cost per call.

Notice above the difference between a call and a customer. A customer may make multiple calls during any given month.

Community ROI Template

You can enter the information into this spreadsheet here or follow the method below.

Step One: Measure the Impact

The best method to measure the value of improved FCR rate is to measure the difference in FCR rates between two randomly selected groups of agents who have or haven’t been assigned to a community ‘condition’. This is the same process we used in determining average call handling time. We expose half to the community as a resource, while the other half continues as normal.

If this is not possible, it may instead be possible to measure the FCR rates of agents who visit the community and, for those who do not, to identify possible differing rates. Alternatively, it might be possible to measure the FCR rates before the community was created and after the community was created. As before, the best method is a direct split test comparison.

We can either use database queries to identify what % of calls were repeat calls or use follow-up questions on the call itself to identify first contact resolution rates. If we assume a customer will, on average, only contact the organization once per month about a problem (e.g. they don’t have multiple problems in a month), we can track the number of customers who call twice during that time period.


For example, if an organization receives 16,324 calls per month from 11,405 customers, we know that 4,919 (30.1%) of these calls were repeat calls. This means the FCR rate is 69.9% (11,405/16,324).

If agents exposed to the community condition improve their FCR to 89.5%, this is a 28% difference (89.5-69.9/69.9). Note here that we’re measuring % improvement, not overall % difference. This tells us that agents exposed to the community are 28% more likely to resolve a call at the first attempt than agents not exposed to the community.

Step Two: Measure Increase in Calls Resolved On First Attempt

Now we can multiply this % increase by the number of customers who call the support line. We will need to either manually get this data from the database or use a sampling technique of a % of customers to determine how many call customer support.

This will reveal the total number increase in customers whose questions were answered at the first attempt, as shown below.


Step Three: Measure total cost savings of calls resolved at first attempt

We can now multiply this increase in calls resolved at the first attempt by the cost per call to calculate the total cost savings attributable to the community.


This reveals the total cost savings through improving the FCR rate per year.


  1. The First Contact Resolution (FCR) rate is the number of problems resolved at the first attempt. This is a widely used metric in customer service sectors.
  2. Higher FCR rates reduce the number of calls to the customer service center and increase customer satisfaction.
  3. To accurately measure FCR rate, run a controlled trial where half the agents are exposed to the community and half are not. Measure the difference between the two as a percentage.
  4. Now multiply this percentage by the number of customers who call for support per year and then the cost per call to reveal a total cost saving.
  5. This is not a perfect method. It makes assumptions about how many problems a customer is likely to have, which may be false



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