How to avoid a one-size-fits-all dataset to get the consumer insights you need
by Pat Criss on February 21, 2023
Social media has become a powerful tool for businesses to connect with their audiences. With billions of people worldwide using platforms like Facebook, Instagram, and Twitter, social media is a giant well of consumer data. Companies across the globe use social media analytics and social listening solutions to access this data so that they can learn about their target audiences.
Social media platforms and their respective datasets are not a one-size-fits all solution.
Here’s why: all social media intelligence platforms give you access to social media data, along with an array of analytical tools and capabilities. However, it is crucial to remember that not all social listening platforms are created equal – largely because not all social media datasets are created equal.
Related: How to use social listening for social media intelligence
You need to make sure that the social listening tool you invest in gets you the kind of insights you need. In other words, the quality of your social media insights depends on the quality of the dataset that your social listening provider makes available to you.
So, how do you avoid a one-size-fits all social listening dataset?
You need to ensure that you are not just getting a large volume of data, but actually equipping your social media insights team with a diversified dataset.
What is a diversified social dataset?
To truly understand and engage with your audience, you must use a diversified dataset so that you can accurately identify them through social media data.
A high-quality, diversified social media dataset needs two main things.
First, you need data from various sources. This includes multiple social media channels, blogs, and news sources. Social media users live on multiple channels, and converse in different ways. To truly understand your audience, you must also understand how those audiences differ so you can meet them where they live online and in the most authentic way possible.
For example, a search into “craft beer” shows that the conversation has sizable volume on three different channels (Figure 1). Instagram has 57% of the post volume, but there is significant volume on Twitter and Pinterest as well.
Second, you need granular data about the posts: your dataset should capture information about the author posts so that you can truly and accurately glean audience-level data such as sentiment, author demographics, geographic location, etc.
Figure 1: Channel distribution of the online conversation around craft beer; Infegy Atlas data.
Reasons to have a diversified social media dataset
Find your entire audience for accurate audience insights
One of the main reasons why a diversified dataset is critical is because social media itself isn’t a community of identical people: users of different ages, genders, ethnicities, and socioeconomic backgrounds all use social media in different ways.
If you only collect data from one platform, or from one demographic group, you will not get an accurate picture of your entire audience. This can lead to inaccurate conclusions and ineffective marketing strategies for you and your clients.
Imagine that you’re working with a client who needs product and marketing insights into audiences interested in cooking or crafting (Figure 2). Where do you naturally assume that people with an interest in cooking or crafting live on social media?
It’s actually best not to assume because social media insights will probably surprise you!
Social listening data shows that 50% of the conversation on “cooking” happens on Twitter (upper graph). Channel distribution for the conversation on “crafting” (bottom graph) however, shows that a whopping 66% of that conversation happens on Pinterest.
Figure 2: Channel distribution of the conversation on “cooking” (upper graph). Channel distribution for the conversation on “crafting” (bottom graph); Infegy Atlas data.
This can be the case with audience demographics as well. For example, imagine your company or brand wants to reach a younger audience. You might understandably assume that younger social users are on Instagram and therefore only collect data from that platform. However, this would be a mistake.
The diverse dataset on Infegy Atlas shows that younger social users are migrating to TikTok and Snapchat. By analyzing data from multiple platforms, you can identify where your audience is most active and engage with them in the most effective way.
Related: Learn more about how privacy issues and decentralization of social networks impacted userships on various social media platforms.
Identify reliable trends
Another important aspect of a diversified dataset is the ability to identify patterns and trends across different platforms.
Twitter users tend to be more reactive. While Twitter is a great place to get audience sentiment analysis data about breaking news and events, post volumes generally spike during those events and then return to “normal” soon after.
In contrast, Instagram offers a wider range of content that is often more personal and curated. Posts tend to have a longer lifespan and a slower build in engagement over time. This provides a different type of data that can be used to identify long-term trends and patterns.
For example, conversations about Superbowl LVII across Twitter, Instagram and Pinterest all reveal different patterns and topics of interest (Figure 3). Twitter had a high proportion of users reacting to Rihanna’s performance at the halftime show and commercials, while Pinterest’s discussion was mostly focused on recipes and ideas for superbowl parties.
Figure 3: Word cloud showing top topics in the discussion around Superbowl LVII shows how the conversation across channels differ; Infegy Atlas data.
By having access to both Twitter and Instagram data, a marketer can identify when certain topics are “hot” and being talked about across Twitter, while also seeing how that same topic is resonating with people on Instagram over a longer period of time.
The combination of these different platforms and their unique user behaviors can provide a more complete understanding of a particular trend or event, allowing for more informed decision-making and ultimately leading to more effective marketing strategies. It is also critical you stay up to date on emerging platforms.
Diversifying datasets to include different platforms is essential to get a more comprehensive understanding of consumer behavior and better trends for audience insights.
Related: How to choose the right social listening provider for your brand or business
Find unexpected audience segments
A diversified dataset also allows you to identify and target sub-groups within your audience. Again, the better the dataset, the better your audience analysis and segmentation.
For example, a company that sells outdoor gear might find that their target audience is primarily made up of middle-aged men who enjoy hiking and camping. However, by diversifying their dataset, and pursuing social media audience insights a little further, they might discover an audience segment of women who enjoy scenic photography and inspirational art, who also share an interest in hiking and camping (curated experiences on platforms like Pinterest and Instagram generally provide surprising audience insights!)
Access to a diversified dataset would allow the company to tailor their marketing strategies, current and future product offerings, and gain client loyalty with this audience subgroup.
Avoid biased data
In addition to the benefits outlined above, a diversified dataset also helps mitigate the risk of biases in the data.
Social media platforms are not immune to biases, and these biases can be amplified if data is only collected from one platform or demographic group. By diversifying the dataset, these biases can be identified and addressed, leading to more accurate conclusions about the audience.
Figure 4: Source bios of those commenting on a recent, potential gas stove ban on Twitter.
The linguistic analysis of the Source Bio data from people discussing the recent potential gas stove ban on Twitter shows that a huge majority of them self-identified as politically conservative (Figure 4). If you restricted your dataset to just Twitter, you would have an analysis of a conversation that is biased by political preferences.
Related: Learn more about what social media analytics revealed about audiences discussing the potential gas stove ban.
Ultimately, a diversified dataset is crucial when identifying audiences through social media.
Don’t miss out on finding your true audience
Diverse data gets you accurate and trustworthy insights that can drive business outcomes for your brands and your client’s brands. By collecting data from multiple platforms and demographic groups, businesses can get a more accurate picture of their target audience, identify patterns and trends across platforms, and target specific sub-groups within their audience.
If you’re worried you might be leaving dollars on the table by missing out on post volume, surprise audience segments, or even conversations from your target consumers, reach out today to schedule a free demo of Infegy Atlas, our consumer intelligence platform.
We’d love to give you a tour of the platform so you can check out its speed and diverse dataset for yourself!
- March 2023 (2)
- February 2023 (4)
- January 2023 (2)
- December 2022 (3)
- November 2022 (5)
- October 2022 (3)
- September 2022 (3)
- August 2022 (2)
- July 2022 (1)
- June 2022 (1)
- April 2022 (1)
- March 2022 (1)
- January 2022 (1)
- December 2021 (1)
- November 2021 (2)
- October 2021 (1)
- June 2021 (1)
- May 2021 (1)
- April 2021 (1)
- March 2021 (1)
- February 2021 (1)
- January 2021 (2)
- November 2020 (1)
- October 2020 (2)
- September 2020 (1)
- August 2020 (2)
- July 2020 (2)
- June 2020 (2)
- May 2020 (1)
- April 2020 (1)
- March 2020 (3)
- February 2020 (2)
- January 2020 (2)
- December 2019 (2)
- November 2019 (1)
- October 2019 (1)
- September 2019 (2)
- August 2019 (2)
- July 2019 (2)
- June 2019 (2)
- May 2019 (2)
- April 2019 (1)
- March 2019 (2)
- February 2019 (2)
- January 2019 (1)