How To Store Social Media Data For Analytics

More than 2.5 quintillion bytes (that is 2,500,000,000,000,000,000) of data is created every day, says DOMO’s Data never sleeps report from 2018. Data is growing rapidly, and social media is contributing to the surge. An estimation is that, in 2020, 1.7 megabytes of data is created every second for every person on the planet.

These numbers are from internet users searching for information on a search engine, signing up to a social media network, posting a tweet, comment or a status update, a photo in a relevant channel, watching a video, downloading a song, and so much more, resulting in the proliferation of data.

Data has and will continue to be a key asset for businesses for it helps observe market trends, understand customer pain points, improve customer experience, enhance a product feature, et cetera.

Social media data is a gold mine of information. It shows how your target audience engage with your content, the type of content they engage with the most and more. It is possible that most of your social media followers will offer opinions, share their sentiments, provide product feedback and ask for recommendations.

Every reaction or engagement (like, retweet, share, comment) is a piece data that, if mined, provides valuable insights about your brand and your products, and reveals market trends and customer behavior.

Storing social data

Before businesses analyze data to make key business decisions, it needs to be collected and stored in a way that’s easier to manage and access. It’s also essential that the data repositories are protected against cyber threats to ensure confidential and key data isn’t stolen or damaged.

Social management applications

Social networks do not sleep, and data is generated round the clock, which is why a social management tool is key to monitoring the conversations about your brand.

Handling social media data also requires storage solutions that can provide information in real-time, which is achieved with the help of social media tools and applications.

They store all your brand mentions on social networks, enabling you to group conversations and profile mentions with special filters to identify those most important to your brand.

Being able to manage large volumes of social data is another key facet of social tools.

Data warehouse

Storing your social media data in separate tools, in other words siloing your data, is detrimental to deriving key information for your social marketing strategy.

All your tools collect and store data separately but if you were to change services at any point, you might lose all the data stored in the tool.

Centralization and ownership of data sets not only overcome the limits of data silos, but they are effective for analytics. Once all your data is centralized, in a data warehouse, the plethora of Business Intelligence (BI) tools can help glean actionable insights.

Data archiving

Data is almost always delivered in real-time, with social media data being a prime example.

Archiving your social media data is essential to performing analytics to gain customer insights. To get the most out of your social analytics platform, you must group the small objects (such as tweets) into a large file for analysis.

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Ensure that you capture the context of all your archival content to make it complete. In addition, your social archival data must be searchable and navigable so that you find anything you’re looking for, from data such as a user liking your tweet and retweeting it to a conversation about your brand.

Graph database (GraphDB)

It is a data management solution that handles large sets of structured, semi-structured and unstructured data. It enables businesses to access, store and analyze data coming from different sources and is useful for integrating social media data to perform analytics.

According to an IBM survey, 57 percent of brands across industries who used GraphDB reported improved performance and speed in managing and analyzing data.

GraphDB has the capabilities to store, analyze and retrieve high-velocity data, which applies to social media networks.

The technology provides brands with a broader, deeper visibility into their data as they try to understand correlations and derive key insights.


Social media data—which at a basic level comprises metrics such as impressions, shares, retweets, comments, and on a more advanced level includes conversion rate, referrals and enquiries—is not just vital to your marketing strategy across channels but it reveals key information about your brand, your products and the sentiment shared by your customers and prospects.

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By collecting data and performing social data analytics, brands make informed decisions that boost their image online, help gain a competitive advantage, understand customer behavior, among other benefits. But initially, it’s essential to have a data management strategy which allows data (irrespective of volume, velocity and variety) to be stored and analyzed to glean actionable insights.

Author: Suhith Kumar
Suhith Kumar is a digital marketer working with Indium Software. Suhith writes and is an active participant in conversations on technology. When he’s not writing, he’s exploring the latest developments in the tech world.