The exact process you can use to calculate the return varies depending upon the metric you want to measure. However, most are based around a very simple methodology. We have outlined this methodology below.
Step One: Determine if the variable has changed over time.
First identify which of the benefits you’re trying to measure. This can be any of the metrics listed in the benefits above. Next, we try to measure this over a fixed period of time. This time frame might vary by benefit (retention rates might be by year, frequency of purchases, or average order value might be by quarter).
- Use a sample of members. This might mean measuring the variable before and after members join a community. A typical interval here might be 3, 6, or 12 months. If members are spending $100 per year before they join the community and $150 per year after they join the community, that’s a measurable impact. We might track the spending habits of 100 members when they join the community, then track their spending of those same members 6 to 12 months later to see if the average spending has increased. We can analyze spending habits when they join either directly (i.e. looking at customer files) or via surveys (asking members to estimate their spending with the company in the previous 12 months and completing the same survey a year later).
- Run an experiment. A more accurate method is to run an experiment. This usually involves segmenting customers at random into two groups. Half are invited to join the community, while half are not. This removes the self-selection bias (i.e. members who join a community are more likely to increase spending/buy more/be more loyal). Then we compare the differences in this behavior over a period of time.
This can be used for almost all the variables mentioned. These variables include retention, lead generation, spending levels, customer satisfaction, etc.
The critical step here is to first benchmark current (or past behavior) and then compare this with future (or now current) behavior to determine whether this has changed since joining the community. This will usually mean identifying the increase or decrease in behavior change (e.g. spending/retention rates/CSAT) per individual community member
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