How to Calculate the ROI of Online Communities

By Richard Millington

ROI People

Online communities are terrific tools to identify potential leads for your business. A lead can come in three forms: problems shared, purchase-intent behavior, or completing information. Far too many people fail to take advantage of this incredible benefit to directly generate more business for their organization.

If you’re not tracking lead identification, or even trying to identify potential leads in your community, you are losing out on a huge amount of value.

Community ROI Template

You can use the spreadsheet package or follow the steps below.

Step One: Measure the Number of Leads Identified

Our first step is to measure the number of leads identified. This might involve manual, automatic and self-generated processes. Each collection method may vary and we need to adapt our efforts to the data we have. Here are some examples:

  • Leads tagged from problems shared. In a B2B online community, members might share problems in the community or directly to the community manager, which the organization’s products or services might be able to solve. Each of these may count as a manual lead identified. These can be tagged in a CRM system (e.g. Salesforce) and then tracked to reveal the total number of sales generated from these leads. You can then look at the conversion rate, average order value, purchase frequency and retention rate of these leads (or use existing numbers for simplicity).
  • Leads identified from behavior. A member in an online community might engage in natural pre-purchase behavior that identifies them as a lead a salesperson may wish to follow-up with. These leads can be tracked automatically by matching community activity to specific purchase actions (e.g. reviewing product information, watching product videos, etc.) or manually tagged in the sales system and a report produced later. These leads are collectively known as automatically generated leads.
  • Leads identified from completing information. A member in an online community might complete a form to request more information about the product, or attend specific webinars and submit their contact information. This could be a highly qualified lead attributable to community activities. These leads are known as self-generated leads (or direct response leads).

Our first step is to measure each of these leads per month. This usually involves collecting data from a CRM system or web reports, e.g. number of people who signed up to attend a webinar related to a product). These reports are usually easy to collect. If you don’t have them set up already, begin setting them up now to measure later. The level of integration between these systems today is relatively high.


Step Two: Determine Lead Overlap

However, we have a problem here. Someone might ask a problem, sign up to attend webinars to resolve this problem, and then submit their email address via the community for more information.

A single person would thus show up as three separate leads. We need to remove this overlap either via directly determining the unique email addresses or IDs from our reports, or by sampling as large a percentage of leads as possible and determining which percentage overlaps and removing this percentage overlap.

This can be performed by multiplying the number of leads by the percentage overlap as we have shown below. This should leave the number of unique leads identified.


Step Three: Determine the conversion rate, contract size (average order value), retention rates, and total revenue generated by unique leads per year

A shortcut here is to use the same rates as existing leads from other sources. However, this doesn’t account for whether community leads are better or worse than other leads. Therefore, it’s better to calculate the conversion rate, contract size (average order value), purchase frequency, retention rates, and average gross margin individually where possible. If any of these figures are not available, we can simply use existing metrics. This will, however, be less accurate.

By multiplying all of the above, we can determine how much each lead identified in the community is worth, as shown below.


We know, in the first month, that each lead is worth $347 to the organization. Another simplification here is to calculate for one month and generalize across twelve months. This won’t be as accurate, but it provides a broad picture.

Step Four: Multiply by the Number of Leads Generated

Finally, we can multiply the above figure by the number of leads generated each month to calculate an approximate total value attributable to the community.


This shows us that the 128 leads identified in the first month will lead to $44,332 in lifetime revenue. In theory, we should also apply the net present value to this figure. We can also measure this by year to determine the total benefit per year. Once this method has been determined, it is possible to simply multiply the number of unique leads by the average profit of each lead to calculate the future profit generated.


  1. Lead identification is one of the easiest ways to increase the value of a community, but few organizations do it yet.
  2. Lead identification comes in three forms: problems shared, identifying purchase-intent behavior, and completing relevant forms.
  3. Be sure to measure lead overlap and remove this from your figures.
  4. Measure the lifetime value of each lead by multiplying the conversion rate by the average order value by the frequency of purchase by the retention rate and by the average gross margin.
  5. Combine these scores to determine the total value generated by leads in the community



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