We know that online communities can spark change, galvanize advocates and drive innovation.
Google ‘online community’ and you get over 2 billion results. They’re part and parcel of the modern internet. The broadest and simplest way to think about them are as digital spaces where people interact over time. Places where people come together for a purpose and create a network, enabled by a technological platform. As such, the term can refer to a vast array of different things.
INSIGHT CREATES BUSINESS CHANGE
In this report we concentrate on brands building online communities to better understand their customers
and create better products, services and marketing.
Because, just as technology has enabled customers to talk about brands, even when they’re not together, it has also enabled businesses to build ongoing relationships with their customers, via insight and marketing departments.
COMMUNITIES ARE CONFUSINGLY DIVERSE
Any term so open to interpretation is likely to lead to confusion. How do you manage expectations of stakeholders when one person is using “community” to refer to a group of 5000 customers giving quantitative feedback on new product features, while another is referring to their open innovation network of 150 customers, students and experts co-designing breakthrough new services? Both are valuable, but very, very different.
TIME TO TIGHTEN TERMINOLOGY?
We believe the industry needs to get stricter with existing terminology, while still innovating around needs that aren’t met by current models.
A lot of jargon confusion happens simply because the existing models don’t quite match business needs.
CUTTING THROUGH COMPLEXITY
Even when we focus on business intelligence, insight and market research, the term “online community” has many meanings. Perhaps this is due to how broadly and flexibly the term is used
elsewhere in business and society. Whatever the reason, even experienced practitioners clash when it comes to language. If you work in insight, marketing or innovation, your “online community” might
vary on any of the following:
Open vs private
run by an
Small (50-500) vs
Qual focused vs
quant vs both
Interrogating briefs and designing the right approach.
The blurred lines today
A key example of jargon confusion is over what’s known by the term “panel” and “community.” Businesses need robust quant data to inform decision making, while also relying on qual insight to give the “why” behind the “what.” As a result, the line between communities and panels has become increasingly blurred.
Classically, panels were seen as a digital space with large numbers of participants, making them better for quant; whereas communities were seen as smaller, more intimate spaces (300-500 members) and better for qual.
Increasingly though, the language of the industry has become blurred. Pick three different pieces of thought leadership on the subject, three different case studies or three different agencies’ websites. Chances are you’ll see three different and conflicting definitions.
However, our client interviews and our own experience warn of the danger of trying to do both qual and quant in the same place.
If you substantially increase the number of people in a digital space in order to get a seriously robust sample size, there’s a trade-off. You don’t get the same level of depth and intimacy across the community as a whole. And trying to achieve the benefits of a panel and a community in the same place can be problematic.
You can put this down to a digital version of Dunbar’s Number 2,3 – the idea that we can only comfortably maintain 150 stable relationships before intimacy and connection is lost. Or, more pragmatically, think of panels as a supermarket and communities as a pub. You can find more people in the supermarket, but if you want a more in-depth conversation, you might want to go to the pub. They’re different tools in your toolbox.
A more useful definition, therefore, could be to focus on the nature of the interactions with consumers and use cases for each kind of space. Panels are largely useful for feedback, validation and forecasting; the participant experience is episodic and blinded. Communities are useful for discovery, exploration, co-creation and feedback; the participant experience is ongoing, empowered, transparent, and relationship-based.
From these definitions it’s clear that the need for both continues.
Think of panels as a supermarket and communities as a pub. You can find more people in the supermarket, but if you want a more in-depth conversation, you might want to go to the pub.
You can end up with the worst of both worlds…not quite good enough qual, and not quite good enough quant.
One interviewee noted that their preference was “to have both a permanent separate community and panel, as it allowed greater specializm and higher quality work, but that this was also typically the most expensive option”.
However, other clients have found the “Hive” approach useful. They can have members that number in the thousands, when agregated, but the members were split off into different communities, often around demographics, to create a more intimate experience.
You’ll note throughout this report that we share examples from both communities and panels. This is because our interviewees talked about both in the same breath, demonstrating how close the concepts are in different clients’ minds. And there are some useful, transferable lessons and success principles that can be learned from both.
Regardless of what other models develop in the future, if we don’t get a little clearer about what we’re talking about when we say online communities, we’re in danger of annoying participants, not meeting business needs and damaging the reputation of our industry.
COMMON WAY TO COMBINE AND ACCESS COMMUNITIES AND PANELS:
Completely separate panel and community. Results can be integrated in analysis and reporting but they are separate entities.
Permanent panel and permanent community. Interlinked but the members of each are treated differently.
Master panel-sized group from which smaller and temporary communities are recruited.
Several separate communities, aimed at different ages, segments or geographies, that allow you to aggregate quantitative data across all.