Early on in most consultancy projects, we run a survey.
You can find an example from one client here.
In a survey, we’re looking to validate/refute our ideas and identify clear member segments.
The member segments are the most valuable part.
A common mistake here is to look only at the aggregated data (i.e. the 1266 answers below).
What we need to do is dive deeper here and see if there are any clear segments.
SurveyMonkey makes this easy. You can create custom filters for each answer and compare them side by side.
For example, when we looked at how relevant one client’s customers found the community and filtered by the amount of time they’ve been using these products, we got the answers below:
It’s not a precise science, but we can clearly see some clusters starting to form here based upon how long they’ve been using the client’s products and how relevant they find the content in the community.
We can see a relative newcomer group, an intermediate group, and a veterans group respectively (note, we might want to dive a little more into the newcomer group and see if there is a difference between <1 year and the rest).
Once we know what attributes divide our audience, we can use this as the basis for establishing community objectives which aim to best harness their potential within the community.
For example, we might create different spaces for newcomers, intermediates, and veterans (in this case, we focused on newcomers and veterans).
The next step is to combine the filters above (i.e. select all the intermediates together) and use the quantitative data from each to determine the unique needs of each group.
One of the very useful things about SurveyMonkey is it shows you where there are statistically significant differences between groups.
This lets you zero in exactly on what each distinct group likes and dislikes about the community, what parts of the topic are of most interest to them and what they most want to see in the community.
The hard part is finding the segments in the first place. Length of time using the products or in the community is just one example. Usually, we create a lot of unique filters based upon survey answers and play around with the data until we find the ones which really show clear differences.
It could just as easily be level of participation (lurkers, top members etc..), specific interests within the sector, location, or any other variable. Once we have these, you can dive deeper into member interviews with 3 to 5 members of each group to get an extremely detailed understanding of what each wants.
Developing the right member segments becomes the very foundation upon which you should be building your entire community strategy. If you don’t have them, you can sign up for our Strategic Community Management course beginning on Mon 17th and we’ll help you build them.