Using Big Data to Reduce User-Generated Content Risks
For the past few years, user-generated content has been a blessing for marketers. According to research, consumers respond to user-generated material much more favorably than brand-created content. Why? external reliability. Your clients and consumers can promote you more effectively than you ever could.
85% of consumers are more affected by visual user-generated material than by brand-provided images or films, according to a marketing study funded by Gap. According to a survey, 84% of respondents said that user-generated content had influenced their buying decisions. On social media, user-generated material is excellent for attracting loyal followers. According to a poll, 52% of users return to a website after interacting with user-generated content. This is around 2.5 times the rate at which users return to websites without user-generated content.
User-generated material has a lot of advantages, but there are also some drawbacks. The good news is that big data can be used to both leverage and reduce these risks. It’s important to keep in mind that user-generated information about your company is important to monitor. However, with website reviews, Google rankings, and SEO traffic metrics to consider, this is far more labor than humans can handle.
Here are a few of the most significant concerns associated with user-generated content that big data can help with.
Liability dangers for unreliable followers
When users publish content on your website or social network, there are some liability issues. Despite being minimal, these hazards nevertheless exist.
Theoretically, brands are shielded from the dangers associated with client conduct on their website. Brands are not liable for the content that third parties distribute on their websites, according to the Communications Decency Act. The safeguards provided by this law, however, are ambiguous. Brands may be held accountable for user-posted content if they are aware of it. If they have previously restricted offensive information, it will be simpler to demonstrate this standard.
This implies that brands must adopt an all-or-nothing approach. Either they need to be very strict about removing offending content, or they need to stop moderating completely. If the brand draws a lot of spammers or people who publish hostile or disparaging content, the latter strategy may be dangerous. Additionally, offensive language and abuse can seriously damage a brand. Companies are frequently accused of discrimination if one comment is removed for being hostile or bigoted while another is not.
Fortunately, big data can assist brands in more effective content censorship. They can find harmful content on their platforms using powerful data mining methods and quickly remove it.
User-generated content must be accurate before being used in advertisements
If a brand doesn’t share or support user-generated content, they are typically not held accountable. Once they begin aggressively marketing it, their responsibility increases dramatically.
This is a problem Quiznos encountered when they asked for customer films, comparing them to Subway. Customers’ videos contained some factual facts that Subway deemed defamatory. Subway said Quiznos was responsible for defamation since it utilized the footage in its own advertising campaign.
Brands find it much simpler to verify claims made in user-generated content thanks to big data. By doing this, they can clean the content before using it in their own advertisements. It increases their own credibility and reduces the possibility of facing civil defamation claims.
Preventing enraged clients from stealing publicity
User-generated content campaigns’ trajectory is not always within brands’ control. When asking consumers to use #MeetTheFarmers to share their tales on Twitter three years ago, McDonald’s was forced to learn this lesson. Even after the campaign was abandoned, customers started telling unfavorable stories about McDonald’s.
By anticipating public perception, big data can assist brands in avoiding these mishaps. Before allowing customers to have a say in a user-generated content strategy, they might concentrate on forging closer ties if the general opinion is unfavorable.
It may appear that using user-generated content will help you gain a large audience. To maintain a good brand and reputation, it is crucial to know the hazards involved, as this article has noted. Utilize big data to help you in this continuing effort.
Frequently asked questions:
What is an effective method for acquiring user-generated content?
Regardless of the nature of your content, video is a tremendously effective approach to generating UGC. In ways that other forms of media can’t, it can help you, and your audience connect.
How can generating material from users improve engagement?
Users are also providing you with information as they create content, including details about their experiences and journeys. Beyond that, they are attentive and likely to respond to future inquiries. Utilize UGC to learn more about your audience’s expectations and motivators by getting to know them better.
What does user-generated material serve as?
Because users rather than authorized brand personnel create the content, UGC fosters brand loyalty. Companies can increase customer trust by prioritizing their audience and inviting them to contribute to the creation of the brand’s image.
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