Neither social media nor online research communities are new platforms for businesses to communicate with consumers over. Still, there is no denying that social media has grown in recent years. And it’s offering a huge variety of new data mining possibilities. As Rebecca Carson states, social media is “breaking the boundaries of data extraction by revealing the powerful insights social listening and analytics provides for brands.”
Social media is clearly an extremely valuable source for raw, unfiltered, consumer data just waiting to be taken advantage of by businesses looking to better align themselves to consumer needs. However online communities can act in a similar way and are set up for the express purpose of gathering information for analysis. So which is the better platform to data mine? Social media or online communities?
Mining Social Media
Data mining is a fantastic tool that can extract predictive knowledge from this readily available source of consumer insight. One study into the topic of data mining in social media stated that it enabled the researchers to “predict the impact of an individual published post” and allow businesses to “[tailor] the promotion of products and services more.” Making the most of every post boosts profits according to this study, since the predictions help brands alter each post to be more impactful on the intended audience. Because these posts are the first point of contact with many potential customers, increasing public awareness initially via promotions and reviews posted to social media channels will intrigue consumers and entice them to find out more about the company and the other products. While this approach is fairly basic, it can be extremely impactful on the bottom line.
There have been a few notable resources on how to mine the information from social media for the sake of social intelligence within a business. Sandra Gittlen’s article on CIO really delves into how social media can be used to inform marketing decisions and boost a company’s sales or brand awareness. This is a very useful result of data mining in social media and one that Gittlen thinks many brands don’t take advantage of as much as they could. Data mining identifies profitable opportunities that might not be obvious at first glance and also provide conclusions that minimise the risk factor within certain campaigns or promotions.
Through discussions, review pages, and general posts about to the company in question, data mining provides the researcher with the ability to identify comprehensible patterns of information from social media activity. Through this one system of information analysis companies can be more reliant on the information gathered and results provided since the data collected is from a source that provides direct contact with the views of consumers.
The main technique of collecting this data for the purposes of data mining is called scraping. Web scraping automates how a human would go through and collect information on the internet, which can then be analysed for the purposes of market research. There are rules on social media and other websites about when and what can be scraped. These rules can be found by typing in the website name, for example ‘facebook.com’, and then adding ‘/robot.txt’ to the end of the URL. This will display the rules and regulations for scraping that particular website. However, since the Cambridge Analytics Scandal in March of this year, general data protection regulations have been significantly tightened, making it harder for companies to gather the large-scale amount of data desired from social media.
Mining Online Communities
One major difference when scraping information from social media and online communities is consent. Since the Cambridge Analytica scandal, Facebook has set regulations so that you can only scrape public (and private by individual consent) data at certain times of the day when the traffic isn’t as high; this means that the data collected is consensual and at a time when it won’t impact the performance of the social media channel. Due to the many issues surrounding consent, this is where online communities come in to their prime.
There are different tools which create an online community on a market research platform. Our own include BlogsMR, SocialMR, and ForumsMR. When added to a platform, these tools enable users to interact with each other similarly to how they do on a social media platform, only this time with a guiding purpose. Users know they are being monitored and they know they are here specifically to give insight into a company or a specific product.
In terms of online discussions, insight communities and other collaborative conversation tools, data mining allows researchers to analyse a large amount of data gathered from a customised online community. This way, researchers can pick who their target audience are and invite recipients that fit the criteria to take part in the research.
Researchers will then be able to ask the invited audience members questions about their perceptions and wants, and instead of trawling through that data, the data mining tool will pick up on the key words and trends in all of their answers. Within forums and blogs, participants have more free reign, but because it will be on a dedicated research platform, the likelihood is that these discussions will still be on relevant topics. Participants may even come up with questions that were not in the initial scope, perfect for passive data gathering.
Which platform is best for data mining?
Social media minimises participant involvement, which could be a both a benefit and a hindrance. With this in mind it is possible to reach customers who might not normally take the time to participate in online communities. This opens up data that may not have otherwise been available. However, it is also possible to gather lots of data that isn’t relevant to the research goal. It’s also possible to use social media to advertise market research opportunities and therefore as a community building tool.
Online communities allow researchers to customise audiences and questions. Online communities also maximise participant involvement, meaning researchers definitely have their, but also the sample bias of those who are willing to participant.
Mining the information from both platforms is definitely possible. However this approach produces a lot of data to interpret and many of influences to factor in. It might just be worth it depending on how much data is required.
Social media and online communities both have their pros and cons, and picking which platform to use primarily is heavily dependent on marketing needs. However I believe that it would be unwise to pick one and discard the other completely, since they are both very valuable sources of information in their own way. While one platform may have more benefits for your marketing needs, mining both platforms will give you a good set of data that will cover all bases.
The original version of this article appeared on the FlexMR Insight Blog and can be accessed here.