Big data analysis for an engaged online community

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big data for an engaged online community

It is important for every business to be able to connect authentically with its target audience. This even becomes more valuable when we remember that we live in a “consumer-led market age”. Therefore, companies wants to improve the client’s journey looking forward to connect and increase brand trust and loyalty. Hence, companies invest in create their own online community. The company groups people with common interest to interact with each other primarily. It can be a community for the whole brand or for a specific product or service. First, the consumer is invited to become part of the brand and influence on it. Once there, members can post, comment on discussions, give advice or collaborate. As a result, this creates authenticity and trust which are key components of an authentic connection that can lead to loyalty.

While is true, a community can begin as a profitable medium, it succeed if participants are truly involved and engaged. This especially true if you plan to use your community on an ongoing basis. This means find ways to keep members participating frequently and providing quality information.

The active participation of users generates an enormous amount of data, varied and at velocity. In other words: Big Data. Therefore, applying machine-learning techniques together with predictive analysis is of great help to the moderator. How?

 

Detects, predicts and prevents disengagement

The company recruit people to be part of the community where there will be diverse activities to participate. Then, the moderator helps them to participate in activities, asking for help or ideas to use among themselves. As a result, participants ask questions or give suggestions that companies might never come up with. Together with these comments, suggestions or ideas, opinions and feelings are shared. When these are analyzed, we get to know the popularity and viability of an idea or opinion. Also it helps to detect topics with active participation and valuable insights. With this information the moderator will know what topics to explore or publish that keep interested and involved the user in the long term.

Automatic learning techniques identify patterns in past data that explain future behavior. By applying it to the community, it is possible to determine user participation and feedback habits. And with that, its possible to predict what leads to user disinterest and what causes poor quality participation. By having the power to predict, the moderator could anticipate and prevent disinterest. He will manage the community effectively in participation by meeting members expectations.

Keeping the participants interested and engaged is no easy matter. To be honest, it requires effort, creativity and interest of the moderator. By combining his abilities with the Big Data analysis, he can proactively correct behavior and prevent consumer disinterest. Then the community will provide insights that truly empower your business.

 

Sources:

Entrepreneur 

Insite