Community Building

Segmentation - The simpler way to improve your community marketing

Segmentation - the simpler way to improve your community marketing

The Biggest Challenge Of Community Marketing

We built our communities with so much passion for the purpose it supports. Be it a Android User group, an iOS Developer syndicate, Social Impact forum or even a brand-focused one such as the Nike Runners Club or a cricket team fan assembly such as the Royal Challengers Bangalore, they all mean something very important to the people involved.

We imagine the possibilities our communities could grow into and start broad. As a part of our community marketing efforts, we email all our lists asking them to spread the word, call everyone on our phonebook and ask them to tell 10 of their friends, send messages to our close friends and expect them to join in and rejoice. Sooner, we understand even our closest of friends did not join in. Sad and dejected, we start thinking about advertising on Social Media , Mobile apps, Web ads, Radio spots and many more. If we get the desired results, we jump up in joy and if we don’t we feel sad about burning our budgets out.

Either we would run out of marketing money and close our communities down or we are forced to cut down on our expenses and bring our reach down. Unless some brands whose interests match our purpose are funding all our experiments. And in such a case, the brands would dictate the terms and we become mere coordinators of their engagement initiatives.

Learning From The Losses

Where on one side we strive to get more people onto our communities, on the other we are faced by people leaving without knowing what made them quit on us. However small or big a community we run, we always see some people leave without stating any reasons. Does that mean they don’t have a reason at all? Does that mean it can be passed off as normal?

Failures are bigger teachers and they teach us what did not work. If we have a system to observe the various aspects of the process, the results would disclose a certain pattern of what brought in the failure, in the first place. Some patterns might be very evident and some might be so obscure that it’s difficult to make sense until we look close enough.

To refine this and make sense of the success and the setbacks, we would need to dig deep and analyze our community marketing efforts. And that can be done best with segmentation. If we know the subsets, we can treat the problem in hand, with more ease and information.

Spotting The Subsets

Considering we have decided to prepare ourselves to gather the data from every person who joined us and left us, we would need to divide the entire community into segments that can be made sense of. Some of the very popular primary classifications used are:

The main bases of segmentation

The main bases of segmentation, image from tutor2u

1. Demographic

Were those who left the community from a certain age group? Are those who are refering their friends to join in, all working in a particular industry? Do male members interact on our forums better than the women in the room?

There are quite a few questions that can determine the behaviour patterns of our community members, which can help us infer on broad reasons.

2. Geographic

Given the fact that there are so many communities today evangelizing almost the same purpose as ours, the members have a plethora of options in front of them. Community marketing efforts being location-specific will help. Geolocalization are a great factor of segmentation today. With the ease of recording the geographical information from mobiles and handhelds, the gathering of such data per member is not difficult at all. This would help us put efforts in gathering people who are homey with a certain location. The same data can be also used to group people in the same geography together for better bonding, thus reducing the probable attrition.

3. Psychographic

When we observe close enough, we will realize that some members only interact on content that is technical in nature, while some might be all in on game scores. By recording these observations, we would have a fair idea of the likes and dislikes of the members. Not only would this help us up the engagement in the most sought after topics, it would also help us plan initiatives that could be more successful fundraisers helping achieve the objectives of our communities.

Thus, interests become a very important factor to set distinct classifiers to determine the common behaviour within the segments.

The Inference

While subsetting is not the silver bullet to making every community work smoothly, observing and recording alone will not drive results that we would like to see. This would just help us arrive at the ideal Member Persona who would stay, contribute and grow with the community. And this is very important.

When we match the Member Persona (i.e. the various behaviours the ideal member of our community should exhibit) to our goals to improve our community marketing and engagement, we start seeing more positive contributors coming in and that helps our communities become more relevant and result oriented.